According to resource limitation, a more realistic pest management is that the impulsive control actions should be adjusted according to the densities of both pest and natural enemy in the field, which result in nonlinear impulsive control. Therefore, we have proposed a Beddington–DeAngelis interference predator-prey model concerning integrated pest management with both density-dependent pest and natural enemy population. We find that the pest-eradication periodic solution is globally stable if the impulsive period is less than the critical value by (...) Floquet theorem. The condition of permanent is established, and a stable positive periodic solution appears via a supercritical bifurcation by bifurcation theorem. Finally, in order to investigate the effects of those nonlinear control strategies on the successful pest control, the bifurcation diagrams showed that the model exists with very complex dynamics. Consequently, the resource limitation may result in pest outbreak in complex ways, which means that the pest control strategies should be carefully designed. (shrink)

This paper investigates the exponential synchronization of complex dynamical networks based on the sampled-data control method. The sampled-data control means that the control input remains unchanged for a long time after each sampling, which can reduce the sampling number. By using the stability theory of the dynamical systems, this paper provides a novel sampling controller and estimates the bound of the sampling interval. Finally, a numerical example is given to demonstrate the effectiveness of the proposed design (...) technique. (shrink)

Systemic therapy considers the complex dynamics of relational factors and resources contributing to psychological symptoms. Negative maintaining factors have been well researched for people suffering from Alcohol-use Disorders. However, we know little about the complex dynamics of these negative factors and resources. We interviewed fifty-five participants suffering or fully remitted from Alcohol-use disorders in this cross-sectional study. The interviews focused on relational factors referring to a Support Social Network and a Craving Social Network. The CSN included all significant (...) others who were associated with craving situations. We compared the network characteristics of the group suffering from Alcohol-use Disorders to a fully remitted control group. The abstinent group with full remission named on average fewer individuals in the CSNs. They had lower social negativity mean scores in the Support Social Network compared to the non-remitted group. In the CSN, the mean scores of social support were significantly higher than the median for both groups. These findings reveal the complex interplay of relational patterns contributing to the etiology, maintenance, and recovery from Alcohol-use disorders. A successful recovery can be linked to increased social resources and reduced relations associated with craving. However, craving-associated relations represent an important source of social support. Future research should investigate this ambivalence for the systemic perspective on the explanation and treatment of Alcohol-use disorders. (shrink)

This study concentrates on adaptive event-triggered control of complex dynamical networks with unpredictable coupling delays and stochastic deception attacks. The adaptive event-triggered mechanism is used to avoid the wasting of limited bandwidth. The probability of data communicated by the network is established by statistical properties and Bernoulli stochastic variables with an uncertain occurrence probability. Stability analysis based on Lyapunov–Krasovskii functional and the stability of the closed-loop system is guaranteed. Using the LMI technique, we obtain triggered parameters. To demonstrate (...) the feasibility and usefulness of the suggested methodology, two examples are shown. (shrink)

This paper describes a traditional SIR type epidemic model with saturated infection rate and treatment function. The dynamics of the model is studied from the point of view of stability and bifurcation. Basic reproduction number is obtained and it is shown that the model system may possess a backward bifurcation. The global asymptotic stability of the endemic equilibrium is studied with the help of a geometric approach. Optimal control problem is formulated and solved. Some numerical simulation works are carried (...) out to validate our analytical results. (shrink)

This paper proposes a novel robust fixed-time control for the robot manipulator system with uncertainties. Based on the uniform robust exact differentiator algorithm, a robust control term is constructed. Then, a robust fixed-time inverse dynamics control is proposed. For the proposed control method, the fixed-time stability of a closed-loop system with uncertainties is strictly proved. The newly proposed method exhibits the following two attractive features. First, the proposed control scheme extends the existing fixed-time IDC for (...) the robot manipulator system to the robust control scheme. Second, the proposed method is strictly nonsingular rather than the commonly used approximate approach. Simulation result demonstrates the effectiveness of the proposed control scheme. (shrink)

The mathematical approach to such essentially biological phenomena as perseverative reaching is most welcome. To extend these results and make them more accurate, levels of analysis and neural centers should he distinguished. The navigational nature of sensorimotor control should be characterized more clearly, including the continuous dynamics of neural processes hut not limited to it. In particular, discrete conditions should be formalized mathematically as part of the biological process.

This paper proposes a new robotic fish which avoids the complex mechanical structure and reduces the model complexity comparing to the existing bioinspired robotic fish, giving rise to a semibiomimetic robotic fish. The generalized Lagrange equation is adopted to establish the dynamic model of the robotic fish. The controllability of the system is analyzed, upon which a trajectory tracking control algorithm is designed by using the feedback linearization technique. The simulation results show that the dynamic model (...) adopted in this paper can achieve better control performance. (shrink)

This article examines mixed ℋ -infinity and passivity synchronization of Markovian jumping neutral-type complex dynamical network models with randomly occurring coupling delays and actuator faults. The randomly occurring coupling delays are considered to design the complex dynamical networks in practice. These delays complied with certain Bernoulli distributed white noise sequences. The relevant data including limits of actuator faults, bounds of the nonlinear terms, and external disturbances are available for designing the controller structure. Novel Lyapunov–Krasovskii functional is constructed to (...) verify the stability of the error model and performance level. Jensen’s inequality and a new integral inequality are applied to derive the outcomes. Sufficient conditions for the synchronization error system are given in terms of linear matrix inequalities, which can be analyzed easily by utilizing general numerical programming. Numerical illustrations are given to exhibit the usefulness of the obtained results. (shrink)

The past two decades have seen an explosion in the methods and directions of neuroscience research. Along with many others, complexity research has rapidly gained traction as both an independent research field and a valuable subdiscipline in computational neuroscience. In the past decade alone, several studies have suggested that psychiatric disorders affect the spatiotemporal complexity of both global and region-specific brain activity (Liu et al., 2013;Adhikari et al., 2017;Li et al., 2018). However, many of these studies have not accounted for (...) the distributed nature of cognition in either the global or regional complexity estimates, which may lead to erroneous interpretations of both global and region-specific entropy estimates. To alleviate this concern, we propose a novel method for estimating complexity. This method relies upon projecting dynamic functional connectivity into a low-dimensional space which captures the distributed nature of brain activity. Dimension-specific entropy may be estimated within this space, which in turn allows for a rapid estimate of global signal complexity. Testing this method on a recently acquired obsessive-compulsive disorder dataset reveals substantial increases in the complexity of both global and dimension-specific activity versus healthy controls, suggesting that obsessive-compulsive patients may experience increased disorder in cognition. To probe the potential causes of this alteration, we estimate subject-level effective connectivityviaa Hopf oscillator-based model dynamic model, the results of which suggest that obsessive-compulsive patients may experience abnormally high connectivity across a broad network in the cortex. These findings are broadly in line with results from previous studies, suggesting that this method is both robust and sensitive to group-level complexity alterations. (shrink)

In this paper, a mathematical model was used to evaluate a dynamical hybrid system for optimizing and controlling the efficacy of plant-based protein in aquafeeds. Fishmeal, raw rapeseed meal, and a fermented meal with yeast and fungi were used as test ingredients for the determination of apparent digestibility coefficients of dry matter, crude protein, crude lipid, energy, and essential amino acids for olive flounder using diets containing 0.5% Cr2O3 as an inert indicator. Among all ingredients tested, FM had the maximum (...) ADC of dry matter, and energy. Fermented meals showed higher ADC. Amino acid digestibility reflects protein digestibility in most cases. Interestingly, protease, lipase, and amylase activities were better expressed in RM-Koji, RM-Yeast, and FM over RM, respectively. The current results deliver important information on nutrients and energy bioavailability in raw and fermented RM, which can be implemented to accurately formulate applied feeds for olive flounder. Compared with other applicable systems, the complexity of the approach implemented has been considerably reduced. (shrink)

The stabilization problem of a macroeconomic dynamical system is considered in this paper. The main features of this system are that the system uncertainties may be unknown functions of state and time but with known bounds. Furthermore, the control inputs are subject to constraints, which is a salient feature in an economic control problem. To ensure that the controls are within the specified boundaries, in our control design procedure, a creative diffeomorphism, which converts bounded controls into unbounded (...) corresponding signals by choosing an appropriate transformation function, is proposed. For the uncertain system, a deterministic robust control is designed to render the practical stability: uniform boundedness and uniform ultimate boundedness. The range of the input bounds is related to the uncertainties and can be designed according to the actual situation. Numerical simulations are performed to verify the effectiveness of the stabilization policy. (shrink)

This paper analyzes the complex historical and regional factors that contribute to the escalation of destruction from 2003 on in Darfur. Darfur is not an isolated case that suddenly erupted in violence. It is the most recent case in a long history of repeated violations by the Sudanese state against its citizens. From the use of proxy militias (the Janjaweed) to signing peace agreements that fragment and weaken the opposition, destruction in Darfur continues government strategies of divide and rule. (...) At the same time, complex regional dynamics especially between Sudan, Chad and the Central African Republic add to violence and instability within states and across borders. The paper emphasizes the speed with which during 2003–2005 over 2.4 million were uprooted from their homes and the ongoing vulnerability of internally displaced persons to attacks, disease and malnutrition. This restructuring of the population in Darfur is part of a strategy to control the populace and redistribute land and other resources. The multicausal origin of the conflict and its increasing complexity points to the difficulty of providing security for the people in Darfur and resolving the conflict. (shrink)

Translation abstractSummary: Control versus Complexity: Approaches to the Carbon Dioxide Problem at IIASA. In the 1970s and 1980s the International Institute for Applied Systems Analysis (IIASA) hosted several research projects, workshops and conferences in order to discuss the implications of rising carbon dioxide concentrations in the Earth's atmosphere. A number of distinguished scholars, some of whom later became prominent protagonists within the United Nations’ Intergovernmental Panel on Climate Change (IPCC) and sustainability communities more generally, participated in these debates. Since (...) those at IIASA did not engage in obviously related fields such as geophysics or climatology, there is a need to explain how, and via which contexts the issue entered the institute's agenda. This article examines this historical context and contrasts two competing paradigms that emerged at IIASA in order to assess and respond to the carbon dioxide question: The first approach was related to the organisation's research projects on the future of energy systems, which drew on physics, engineering, economics and applied system dynamical modeling; the second approach drew earlier research into ecological management and complex dynamical systems theory, and argued for the use of multiple methods to assess the carbon dioxide question. The first approach invoked ideas of techno‐economical control mechanisms, the second resulted in a more embedded framing of climate change as one of a larger complex of issues relating to sustainable development. Based on resources from IIASA's research repositories and institutional archive, this study retraces these competing discourse framings and outlines the specific research and modeling strategies, policies, and cultural and technological imaginaries related to them. (shrink)

Complex problem solving (CPS) and related topics such as dynamic decision-making (DDM) and complex dynamic control (CDC) represent multifaceted psychological phenomena. In a broad sense, CPS encompasses learning, decision-making, and acting in complex and dynamic situations. Moreover, solutions to problems that people face in such situations are often generated in teams or groups. In turn, this adds another layer of complexity to the situation itself because of the emerging issues that arise from the (...) social dynamics of group interactions. This framing of CPS means that it is not a single construct that can be measured by using a particular type of CPS task (e.g. minimal complex system tests), which is a view taken by the psychometric community. The proposed approach taken here is that because CPS is multifaceted, multiple approaches need to be taken to fully capture and understand what it is and how the different cognitive processes associated with it complement each other. (shrink)

Malaria is a Plasmodium parasitic disease transmitted by infected female Anopheles mosquitoes. Climatic factors, such as temperature, humidity, rainfall, and wind, have significant effects on the incidence of most vector-borne diseases, including malaria. The mosquito behavior, life cycle, and overall fitness are affected by these climatic factors. This paper presents the results obtained from investigating the optimal control strategies for malaria in the presence of temperature variation using a temperature-dependent malaria model. The study further identified the temperature ranges in (...) four different geographical regions of sub-Saharan Africa, suitable for mosquitoes. The optimal control strategies in the temperature suitable ranges suggest, on average, a high usage of both larvicides and adulticides followed by a moderate usage of personal protection such as bednet. The average optimal bednet usage mimics the solution profile of the mosquitoes as the mosquitoes respond to changes in temperature. Following the results from the optimal control, this study also investigates using a temperature-dependent model with insecticide-sensitive and insecticide-resistant mosquitoes the impact of insecticide-resistant mosquitoes on disease burden when temperature varies. The results obtained indicate that optimal bednet usage on average is higher when insecticide-resistant mosquitoes are present. Besides, the average bednet usage increases as temperature increases to the optimal temperature suitable for mosquitoes, and it decreases after that, a pattern similar to earlier results involving insecticide-sensitive mosquitoes. Thus, personal protection, particularly the use of bednets, should be encouraged not only at low temperatures but particularly at high temperatures when individuals avoid the use of bednets. Furthermore, control and reduction of malaria may be possible even when mosquitoes develop resistance to insecticides. (shrink)

Understanding the dynamics of complex ecosystems is a necessary step to maintain and control them. Yet, reverse-engineering ecological dynamics remains challenging largely due to the very broad class of dynamics that ecosystems may take. Here, this challenge is tackled through symbolic regression, a machine learning method that automatically reverse-engineers both the model structure and parameters from temporal data. How combining symbolic regression with a “dictionary” of possible ecological functional responses opens the door to correctly reverse-engineering ecosystem dynamics, even (...) in the case of poorly informative data, is shown. This strategy is validated using both synthetic and experimental data, and it is found that this strategy is promising for the systematic modeling of complex ecological systems. (shrink)

The problem of finite-time tracking control is discussed for a class of uncertain nonstrict-feedback time-varying state delay nonlinear systems with full-state constraints and unmodeled dynamics. Different from traditional finite-control methods, a C 1 smooth finite-time adaptive control framework is introduced by employing a smooth switch between the fractional and cubic form state feedback, so that the desired fast finite-time control performance can be guaranteed. By constructing appropriate Lyapunov-Krasovskii functionals, the uncertain terms produced by time-varying state delays (...) are compensated for and unmodeled dynamics is coped with by introducing a dynamical signal. In order to avoid the inherent problem of “complexity of explosion” in the backstepping-design process, the DSC technology with a novel nonlinear filter is introduced to simplify the structure of the controller. Furthermore, the results show that all the internal error signals are driven to converge into small regions in a finite time, and the full-state constraints are not violated. Simulation results verify the effectiveness of the proposed method. (shrink)

Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in (...) a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. (shrink)

A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function neural network approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics (...) of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme. (shrink)

Engineers fine-tune the design of robot bodies for control purposes, however, a methodology or set of tools is largely absent, and optimization of morphology (shape, material properties of robot bodies, etc.) is lagging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or ”soft” bodies. These carry substantial potential regarding their exploitation for control—sometimes referred to as ”morphological computation”. In this article, we briefly review different notions of computation by physical (...) systems and propose the dynamical systems framework as the most useful in the context of describing and eventually designing the interactions of controllers and bodies. Then, we look at the pros and cons of simple vs. complex bodies, critically reviewing the attractive notion of ”soft” bodies automatically taking over control tasks. We address another key dimension of the design space—whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. (shrink)

Specific to the NCSs where sensor signals can be processed centrally, a collaborative design scheme of dynamic game scheduling and advanced control theory was proposed in the present study. Firstly, by using the Jordan standard state space equation of the research object, the three elements of state noncooperative game were built, and the existence and uniqueness of Nash equilibrium solution were verified. In addition, the iterative equation of the scheduling matrix was derived by complying with the designed utility (...) function. Secondly, refer to the number of restricted states the order of sliding mode was determined. And based on it, the corresponding sliding surface was designed. Subsequently, the quadratic optimization theory was adopted to regulate the control value following the implementation of the scheduling strategy to ensure that the control quality was further enhanced in the limited network service. Lastly, a TrueTime simulation example is established to verify the effectiveness of the proposed scheme. (shrink)

This paper investigates the stabilization and trajectory tracking problem of wheeled mobile robot with a ceiling-mounted camera in complex environment. First, an adaptive visual servoing controller is proposed based on the uncalibrated kinematic model due to the complex operation environment. Then, an adaptive controller is derived to provide a solution of uncertain dynamic control for a wheeled mobile robot subject to parametric uncertainties. Furthermore, the proposed controllers can be applied to a more general situation where the (...) parallelism requirement between the image plane and operation plane is no more needed. The overparameterization of regressor matrices is avoided by exploring the structure of the camera-robot system, and thus, the computational complexity of the controller can be simplified. The Lyapunov method is employed to testify the stability of a closed-loop system. Finally, simulation results are presented to demonstrate the performance of the suggested control. (shrink)

A novel conservative chaotic system with no equilibrium is investigated in this study. Various dynamics such as the conservativeness, coexistence, symmetry, and invariance are presented. Furthermore, a partial-state feedback control scheme is proposed, and the stable domain of control parameters is analyzed based on the degenerate Hopf bifurcation. In order to verify the numerical simulation analysis, an analog circuit is designed. The simulation results show that the output of the analog circuit system can reproduce the numerical simulation results (...) and verify the correctness of the theoretical analysis. (shrink)

In this paper, a 3D jerk chaotic system with hidden attractor was explored, and the dissipativity, equilibrium, and stability of this system were investigated. The attractor types, Lyapunov exponents, and Poincare section of the system under different parameters were analyzed. Additionally, a circuit was carried out, and a good similarity between the circuit experimental results and the theoretical analysis testifies the feasibility and practicality of the original system. Furthermore, a robust feedback controller was designed based on the finite-time stability theory, (...) which guarantees the synchronization of 3D jerk master-slave system in finite time and asymptotically converges to the origin. Finally, we also give verification for the discussion in this paper by numerical simulation. (shrink)

Automatic Generation Control in modern power systems is getting complex, due to intermittency in the output power of multiple sources along with considerable digressions in the loads and system parameters. To address this problem, this paper proposes an approach to calculate Power System Restoration Indices of a 2-area thermal-hydro restructured power system. This study also highlights the necessary ancillary service requirements for the system under a deregulated environment to cater to large-scale power failures and entire system outages. An (...) abrupt change in consumer load demands and disturbances in any control region of a multiarea system causes severe fluctuations in frequency and interarea power exchanges. However, simple Proportional and Integral controllers are most prevalent in the literature to effectively resolve AGC issues, while its integral gain is smaller due to the larger overshoot in transient performance. Therefore, an attempt has been made with a novel control strategy, known as the pseudoderivative feedforward with feedback controller, is developed to keep the interarea power exchanges and the frequency to the specified limits after load changes. A PDFF controller is designed and implemented using the flower pollination algorithm to obtain optimal dynamic performance for different types of potential power flows in a restructured power system under investigation. The proposed PDFF controller localizes the zero at an optimal place that reduces the rise time of the step-response to reduce the excessive overshoot and gives much better dynamic performances as compared to the PI control structure. The Integral Square Error is considered as a performance criterion to derive the optimized gain of the PDFF control structure using FPA. Different PSRI are computed based on the transient response of the 2-area deregulated multisource system and different restoration measures to be taken are also discussed. The simulation results clearly show that the proposed approach is very powerful in decreasing the frequency and tie-power digressions under different load perturbations. (shrink)

This paper studies a simple dynamical system of stock price fluctuation time series based on the rule of stock market. When the stock price fluctuation system is disturbed by external excitations, the system exhibits obviously chaotic phenomena, and its basic dynamic properties are analyzed. At the same time, a new fixed-time convergence theorem is proposed for achieving fixed-time control of stock price fluctuation system. Finally, the effectiveness of the method is verified by numerical simulation.

The high complexity of international supply chain (SC) relationships requires mechanisms to build trust among stakeholders. Therefore, understanding the underlying mechanisms of developing and maintaining high trust levels in exchange relationships is essential to managing associated SC risks. Third-party certification (TPC) is a widely used, control-based governance mechanism in organic food production that aims to help build trust. Drawing on the concepts of trust and control, this article presents an analytical framework for assessing TPC's effects on trust–control (...) dynamics within food SCs. By using qualitative data on a buyer–supplier relationship between Cuba and Europe, this case illustrates the mutually reinforcing relationship between trust and control. We also demonstrate how trust is built across multiple levels. By considering contextual factors, the case illustrates controls' impact on building institutional trust while also pointing out TPC's limited efficacy in enhancing collaboration in SCs. (shrink)

Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium (...) traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole. (shrink)

Action theory has given rise to some perplexing puzzles in the past half century. The most prominent one can be summarized as follows: What distinguishes intentional from unintentional acts? Thanks to the ingenuity of philosophers and their thought experiments, we know better than to assume that the difference lies in the mere presence of an intention, or in its causal efficacy in generating the action. The intention might be present and may also cause the intended behavior, yet the behavior may (...) not be an intentional action; it may not be an action at all. The classic example is that of the nervous nephew who intends to kill his uncle to inherit his estate, and whose intention makes him so nervous as to drive recklessly, thereby running over a pedestrian... who happens to be his very uncle. The intention to kill is present and it causes the killing, yet the killing is not an intentional action. Rather, what appears to distinguish intentional from non-intentional action is voluntary control of the proper sort, and what distinguishes action from non-action is behavior caused in a particular manner. But spelling out the sort and specifying the manner have proven vexing tasks. (shrink)

In recent years, the problem of environmental pollution has become more and more serious, and environmental pollution has become a topic of concern. PM2.5, PM10, hazy weather, and other words about environmental pollution have become hot words and topics for the media and the public to talk about, and environmental pollution control is called for by the media and the public. This reflects the rapid development of economy and the obvious changes in people’s living standards, and people have higher (...) requirements and aspirations for their lives and the environment they live in, and their awareness of environmental protection is getting stronger and stronger; however, it also reflects that the rapid development of the economy comes at the cost of damaging the environment. This paper analyzes the current situation and governance dilemma of rural environment by means of field research from dynamic portfolio evaluation theory, explains the problems and causes of environmental pollution management under the requirement of polycentric governance, and proposes countermeasures to solve the problem of environmental pollution management in county. The paper aims to analyze the current state of environmental pollution in rural areas through literature review, villagers’ field interviews, and field research and to explain the application of polycentric governance to rural environmental pollution management in county in the region. (shrink)

Engineers fine-tune the design of robot bodies for control purposes; however, a methodology or set of tools is largely absent, and optimization of morphology is lagging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or ‘soft’ bodies. These carry substantial potential regarding their exploitation for control—sometimes referred to as ‘morphological computation’. In this article, we briefly review different notions of computation by physical systems and propose the dynamical systems framework (...) as the most useful in the context of describing and eventually designing the interactions of controllers and bodies. Then, we look at the pros and cons of simple versus complex bodies, critically reviewing the attractive notion of ‘soft’ bodies automatically taking over control tasks. We address another key dimension of the design space—whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. (shrink)

This paper focuses on the problem of target tracking using k fittest robots in a group of n mobile robots with n>k. We present centralized and distributed coordination models with all-to-all and limited communications, respectively. For the case of all-to-all communication between robots, theoretical analysis is presented to prove the exponential stability of the whole system. In real applications of robotic networks, a robot may only be allowed to exchange information with a limited number of neighbors. In such a limited (...) communication case where centralized quantity is not available, a consensus filter is used to estimate the centralized quantities in a distributed way, and a distributed competitive target tracking is thus achieved. The stability of the distributed control is also proved in theory. Finally, illustrative examples are provided and analyzed to substantiate the efficacy of the proposed models for tracking moving target in a competition manner with all-to-all communications and limited communications. (shrink)

A robust adaptive fuzzy nonlinear controller based on dynamic surface and integral sliding mode control strategy is proposed to realize trajectory tracking for a class of quadrotor UAVs. In this study, the composite factors including parametric uncertainties and external disturbances are added to controller design, which make it more realistic. The quadrotor model is divided into two subsystems of attitude and position that make the control design become feasible. The main contributions of the proposed ADSISMC strategy are (...) as follows: The combination of dynamic surface and integral sliding mode makes the system always in sliding stage by finding the appropriate initial position compared with the common sliding mode, and the complexity of explosion in backstepping method is eliminated. By introducing the fuzzy system, the unknown functions and uncertainties can be approximated which significantly improves the robustness and the tracking performance. The switching control strategy is utilized to compensate for the errors between estimated and ideal inputs; the tracking performance of the whole system has been significantly improved. The simulation results show the effectiveness of the proposed control method. (shrink)

This article is related to the issue of fixed-time synchronization of different dimensional complex network systems with unknown parameters. Two suitable adaptive controllers and dynamic parameter estimations are proposed such that the complex network driving and response systems can be synchronized in the settling time. Based on fixed-time control theory and Lyapunov functional method, novel sufficient conditions are provided to guarantee the synchronization within the fixed times, and the settling times are explicitly evaluated, which are independent (...) of the initial synchronization errors. Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms. (shrink)

We present a new viable nonlinear chaotic paradigm. This paradigm has four nonlinear terms. The essential features of the new paradigm have been investigated. Our new system is confirmed to have chaotic behaviors by calculating its Lyapunov exponents. The relations of the system states are displayed by a suggested new signal flow graph. The proposed SFG is discussed via some graph theory tools, and some of its hidden features are calculated. In addition, the system is realized via constructing its electronic (...) circuit which helps in the real applications. Also, a robust controller for the system is designed with the aid of a genetic algorithm. (shrink)

Tailoring the design of robot bodies for control purposes is implicitly performed by engineers, however, a methodology or set of tools is largely absent and optimization of morphology (shape, material properties of robot bodies, etc.) is lag- ging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or "soft" bodies. These carry substantial potential regarding their exploitation for control – sometimes referred to as "mor- phological computation" in the sense of (...) offloading computation needed for control to the body. Here, we will argue in favor of a dynamical systems rather than com- putational perspective on the problem. Then, we will look at the pros and cons of simple vs. complex bodies, critically reviewing the attractive notion of “soft” bodies automatically taking over control tasks. We will address another key dimension of the design space – whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. ----- This paper was also published in the 2014 AISB proceedings http://aisb50.org/representation-of-reality-humans-animals-and-machines/ - http://doc.gold.ac.uk/aisb50/. (shrink)

Actuator saturation phenomenon often exists in the actual control system, which could destroy the closed-loop performance of the system and even lead to unstable behavior. Our main contribution is to provide an antiwindup recursive dynamic surface control for a discrete-time system with an unknown state and actuator saturation. The fuzzy compensator is added to perform as an active disturbance rejection term in the feedforward path to avoid windup caused by input saturation. To construct output feedback control, (...) the system is transformed into the form of pure-feedback and an improved HOSM observer is designed to carry out future output prediction. Based on which RDSC is synthesized, only one fuzzy logic system is used and the controller singularity is completely avoided. In addition, the simulation and numeral examples using a continuous stirred tank reactors system with actuator saturation are provided and the results show that the strategy owns good robustness and effectively compensates for the disturbance caused by actuator saturation in the presence of a discrete-time system with an unmeasurable state. (shrink)

This paper investigates the antidisturbance formation control problem for a class of cluster aerospace unmanned systems suffering from multisource high-dynamic uncertainties. Firstly, to estimate and compensate the uncertainties existing in CAUS coordinate dynamics, an adaptive antidisturbance formation control law, which is combined by a robust adaptive control law and the second order disturbance observer, has been designed. Secondly, aiming at the adverse influences caused by the nonlinear time-varying nonlinearities existing in the formation flight dynamics, the radial (...) basis function neural network is introduced. Furthermore, considering the rapidly varying characteristics of the aforementioned formation flight nonlinearities, a novel board RBFNN has been constructed and utilized to improve the approximation and compensation performance. In virtue of the fusing of the B-RBFNN and the second-order disturbance observer-based adaptive formation control law, the rapid response rate and the higher control accuracy of the formation control system can be achieved. As a result, a novel B-RBFNN-based intelligence adaptive antidisturbance formation control algorithm has been established for CAUS trajectory coordination and formation flight. Numerical simulation results are proposed to illustrate the effectiveness and advantages of the proposed B-RBFNN-based intelligent adaptive formation control method for the CAUS. (shrink)