Distributed output estimation error observer-based adaptive fault-tolerant consensus tracking control of multi-agent systems

The purpose of this study is to discuss the fully distributed design of output estimation error observer and fault-tolerant consensus tracking control for a class of multi-agent systems with Lipschitz nonlinear dynamics and actuator faults. Firstly, based on the relative output measurements of neighboring agents, the distributed output estimation error observer is developed to adaptively estimate the state and fault information of each agent, and further overcome the difficulties of online updating the adaptive estimations of unknown hyper-parameters. Secondly, to achieve the state consensus tracking goal and compensate for the negative effects of actuator faults, the distributed fault-tolerant consensus tracking control scheme is proposed on the basis of the state estimation and adaptive fault estimation information, and has excellent robustness and consensus tracking control performance. Moreover, sufficient criteria can ensure that consensus tracking error of each agent converges to a small set near the origin. Finally, numerical simulations are provided to show the effectiveness of the proposed fully distributed algorithm.     

Fully distributed tracking control for non‐identical multi‐agent systems with matching uncertainty

This article addresses the fully distributed consensus tracking control problem of linear multi‐agent systems with parameter uncertainties. First, a new class of distributed protocol, based on the relative states of neighbors, is proposed. Theoretical analysis indicates that the considered problem can be solved if the control gain constant of the protocol is larger than the norm bound of the leader's nonlinear inputs. Furthermore, a distributed adaptive control protocol is proposed for the case without available global information. The distributed consensus tracking control problem of uncertain linear multi‐agent systems is solved based only on local information under the proposed adaptive protocol. Finally, an application in low‐Earth‐orbit satellite formation flying is provided to illustrate the theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.     

An integrated fault estimation and fault tolerant control method using H∞-based adaptive observers

An integrated fault estimation/fault-tolerant control (FTC) scheme is developed in this article for nonlinear Lipschitz systems in the presence of external disturbances and actuator failures. To address this problem, coupled uncertainties between the observer error dynamics and the control system are considered, which is conveniently ignored in control approaches based on the separation principle. An H_∞ -based adaptive observer is proposed to simultaneously estimate the system states and actuator faults without the restrictive strictly positive realness or persistent excitation conditions. The FTC is constructed by sliding mode control using the estimated states generated by the developed observer. A novel sufficient condition is derived in terms of linear matrix inequality (LMI) including both the system control dynamics and the estimation errors; then, the control parameters and observer gains are simultaneously obtained via solving the mentioned LMI based on the H_∞ optimization. Finally, a flexible joint robot is considered to illustrate the effectiveness of the developed method.     

LMI‐based adaptive output feedback fault‐tolerant controller design for nonlinear systems

This paper presents 2‐novel linear matrix inequality (LMI)‐based adaptive output feedback fault‐tolerant control strategies for the class of nonlinear Lipschitz systems in the presence of bounded matched or mismatched disturbances and simultaneous occurrence of actuator faults, including failure, loss of effectiveness, and stuck. The constructive algorithms based on LMI with creatively using Lyapunov stability theory and without the need for an explicit information about mode of actuator faults or fault detection and isolation mechanism are developed for online tuning of adaptive and fixed output‐feedback gains to stabilize the closed‐loop control system asymptotically. The proposed controllers guarantee to compensate actuator faults effects and to attenuate disturbance effects. The resulting control methods have simpler structure, as compared with most existing recent methods and more suitable for practical systems. The merits of the proposed fault‐tolerant control scheme have been verified by the simulation on nonlinear Boeing 747 lateral motion dynamic model subjected to actuator faults.     

Adaptive consensus seeking of multiple nonlinear systems

This paper considers two consensus problems of multiple nonlinear systems. In the first consensus problem, distributed control laws for multiple nonlinear systems are proposed such that the state of each system converges to a constant agreement vector with the aid of communications between systems. In the second consensus problem, distributed robust/adaptive control laws for multiple nonlinear systems are proposed such that the state of each system converges to the state of a reference system whose state is available to a portion of multiple systems. Simulation results show the effectiveness of the proposed control laws. Copyright © 2011 John Wiley & Sons, Ltd.     

Saturated observer-based adaptive neural network leader-following control of N tractors with n-trailers with a guaranteed performance

This article addresses the leader-following neural network adaptive observer-based control of N tractors connected to n trailers with the prescribed performance specifications. To propose the controller, a change of coordinates and a nonlinear error transformation are used to transform the constrained error dynamics to a new second-order Euler-Lagrange unconstrained error dynamics which inherits all structural properties of ith vehicle dynamic model. By combining a projection-type neural network and an adaptive robust technique, a novel leader-following saturated output-feedback controller is proposed to force that ith vehicle tracks a virtual leader trajectory with the prescribed transient and steady-state characteristics while reducing the actuator saturation risk and compensating all unknown dynamic model parameters, external disturbances, unmolded dynamics, and NN approximation errors. A saturated velocity observer is heuristically proposed to obviate the requirement for the velocity measurements of ith vehicle without any unwanted peaking. A Lyapunov-based stability analysis is utilized to prove that all the tracking and state observation errors are semi-globally uniformly ultimately bounded (SGUUB) and they converge to small bounds including the origin with a prescribed performance. At the end, computer simulations will be shown to validate the efficacy of the proposed controller in practice.     

Nonfragile control design for consensus of semi-Markov jumping multiagent systems with disturbances

The consensus problem for multiagent systems (MASs) with semi-Markov jumping parameters under the influence of disturbances is investigated in this article. In the first part of this article, an extended dissipative approach is used for the consensus of MASs with semi-Markovian jumping parameters and external disturbances via nonfragile controller with randomly occurring gain fluctuations. Besides, in the second part of the article, the consensus of stochastic semi-Markovian jumping MASs via nonfragile controller subject to probabilistic time-varying delay is discussed. The primary motive of this article is to develop a robust controller such that the considered MASs with semi-Markov jumping parameters achieve consensus in the presence of external disturbances. For this, the chosen problems are first converted to stabilization problems then by using Lyapunov stability theory and linear matrix inequality approach, the stabilization criterion have been established. At last, two numerical examples are worked out to illustrate the efficiency of the proposed control methodologies.     

Adaptive neural network output feedback stabilization of nonlinear non‐minimum phase systems

This paper presents an adaptive output feedback stabilization method based on neural networks (NNs) for nonlinear non‐minimum phase systems. The proposed controller comprises a linear, a neuro‐adaptive, and an adaptive robustifying parts. The NN is designed to approximate the matched uncertainties of the system. The inputs of the NN are the tapped delays of the system input–output signals. In addition, an appropriate reference signal is proposed to compensate the unmatched uncertainties inherent in the internal system dynamics. The adaptation laws for the NN weights and adaptive gains are obtained using Lyapunov's direct method. These adaptation laws employ a linear observer of system dynamics that is realizable. The ultimate boundedness of the error signals are analytically shown using Lyapunov's method. The effectiveness of the proposed scheme is shown by applying to a translation oscillator rotational actuator model. Copyright © 2009 John Wiley & Sons, Ltd.     

Fuzzy adaptive leader‐following consensus of second‐order multiagent systems with imprecise communication topology structure

The consensus problem of second‐order nonlinear multiagent systems (MAS) with imprecise communication topology structure is addressed in this paper. Takagi‐Sugeno fuzzy models are presented to describe the leader‐following MAS with imprecise communication topology structure. By designing the distributed adaptive controller, an efficient framework is proposed for the consensus control of the MAS with both uncertain parameters and input disturbances. Under the conditions that the communication topology is fuzzy union connected and the dynamics of the leader agent is unknown to any agent of followers, the proposed protocol can guarantee that the consensus errors asymptotically approach zeros. Furthermore, the proposed algorithm is extended to solve the formation control problem. Sufficient conditions are given for the consensus and formation problems of the MAS based on the Lyapunov stability theory. Finally, a numerical example and multiple pendulum systems are given to illustrate the effectiveness of the proposed control protocols.     

Optimal model‐free control for a generic MIMO nonlinear system with application to autonomous mobile robots

In this paper, the design procedure for optimal model‐free control algorithm is presented for the tracking problem of completely unknown nonlinear dynamic systems operating under unknown disturbances. The procedure includes a new structure in the context of model‐free control and data‐driven control algorithms. In the new structure, the unknown nonlinear functions are segmented into 1 unknown linear‐in‐states part and another unknown nonlinear part. The adaptive laws proposed for estimating the unknown system dynamics are regressor‐free estimation methods in which there is no need for regressor parameters and, consequently, the persistent excitation condition is not required anymore. Moreover, the main controller gains are updated online, incorporating the adapted values of linear terms in the system dynamics. A comparative study is presented to show that the proposed optimal model‐free control outperforms the state‐of‐the‐art model‐free control algorithms. In addition, the simulation results for the application of the algorithm on autonomous mobile robots are provided.     

Robust adaptive consensus tracking for higher‐order multi‐agent uncertain systems with nonlinear dynamics via distributed intermittent communication protocol

This paper considers the robust adaptive consensus tracking for higher‐order multi‐agent uncertain systems with nonlinear dynamics via distributed intermittent communication protocol. The main contribution of this work is solving the robust consensus tracking problem without the assumption that the topology among followers is strongly connected and fixed. The focus is the problem of actuator with occasional failure inputs and communication resources constraints. A novel distributed intermittent communication framework is proposed via adaptive approach. In this framework, the underlying communication topologies switch among several directed graphs with a limited directed spanning tree rooted at a leader agent. Furthermore, by introducing a strategy of actuator fault compensation inputs, a combination of robust consensus tracking protocol is designed by the different adaptive feedback controllers. It is proved that the robust adaptive consensus tracking can be achieved by using local states information of neighboring agents if the communication retention rate condition is satisfied. Two examples are presented to demonstrate the effectiveness of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive observer for a class of nonlinear systems with time‐varying delays

The adaptive observer design problems have been extensively studied in literature for both linear and nonlinear systems. Some researches have also been carried out on adaptive observer design for linear time‐delay systems, but there is no significant work on adaptive observer design for nonlinear time‐delay systems. In this work, the adaptive observer design problem for a class of nonlinear time‐delay systems is considered. The observer is designed for the nonlinear systems whose nonlinear functions satisfy Lipschitz condition. Like conventional adaptive observers for the systems without time delays, this observer also estimates both states and unknown parameters simultaneously. For this property, it will be very much useful for many real‐time systems where time delays cannot be avoided. The sufficient conditions for existence of the observer are derived using the linear matrix inequality approach. With the help of a numerical example, effectiveness of the proposed observer is demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Event-triggered adaptive backstepping tracking control for a class of nonlinear fractional order systems

This article investigates the problem of event-trigger based adaptive backstepping control for a class of nonlinear fractional order systems. By introducing an appropriate transformation of frequency distributed model, the fractional-order indirect Lyapunov method with is obtained. In addition, the event-triggered adaptive controller is developed by employing the event-triggered control approach. Meanwhile, by the proposed adaptive control scheme, all the closed-loop signals are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Finally, simulation results are provided to testify the availability of the presented controller.     

稀疏通信下分布式电源微增率一致性加速算法

基于分层控制结构,提出一种稀疏通信下的分布式电源微增率一致性加速算法。该方法无需中央控制器,借助稀疏通信网络实现分布式电源的三次分层控制并加快收敛速度。在该分层控制中,一次控制采用线性下垂控制策略;二次控制仅借助本地频率信息实现系统频率调节;三次控制考虑各分布式电源的成本微增率,利用稀疏不完备的通信网络传递分布式电源成本微增率信息,并结合非线性下垂控制实现微增率的一致性,各分布式电源能较快地收敛至等微增率点。该算法所构建的稀疏通信网络拓扑可以是任意的,对于通信网络的单双向及连通性都没有要求。仿真算例验证了该算法的有效性。     

Predictor‐based adaptive dynamic surface control for consensus of uncertain nonlinear systems in strict‐feedback form

This paper investigates the leader–follower consensus problem of uncertain nonlinear systems in strict‐feedback form. By parameterizations of unknown nonlinear dynamics of the agents, an adaptive dynamic surface control with the aid of predictors, tracking differentiators is proposed to realize output consensus of the multi‐agent systems. Unlike the existing adaptive consensus methods, the predictor errors are used to learn the unknown parameters, which can achieve fast learning without high‐frequency signals in control inputs. As a fast precise signal filter, the tracking differentiator is used in the control design instead of first‐order filters, which can further improve the control performance. Based on graph theory and Lyapunov stability theory, it is shown that the outputs of all followers ultimately synchronize to that of the leader with bounded tracking errors. Simulation results are provided to validate the effectiveness and advantage of the proposed consensus algorithm. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive fuzzy gain scheduling for load frequency control

An adaptive fuzzy gain scheduling scheme for conventional PI and optimal load frequency controllers has been proposed. A Sugeno type fuzzy inference system is used in the proposed controller. The Sugeno type fuzzy inference system is extremely well suited to the task of smoothly interpolating linear gains across the input space when a very nonlinear system moves around in its operating space. The proposed adaptive controller requires much less training patterns than a neural net based adaptive scheme does and hence avoiding excessive training time. Results of simulation show that the proposed adaptive fuzzy controller offers better performance than fixed gain controllers at different operating conditions     

Approximation-based adaptive fault compensation backstepping control of fractional-order nonlinear systems: An output-feedback scheme

An observer-based adaptive fuzzy backstepping approach is proposed for nonlinear systems with respect to fractional-order differential equations, unmatched uncertainties, unmeasured states, and actuator faults. The approximation capability of fuzzy logic system and minimal learning parameter approaches are applied to identify uncertain functions in a simultaneous manner. For estimating the unavailable conditions, a fuzzy fractional-order state-observer is extended. Applying fault-tolerant approach in a backstepping design methodology would provide a new fault-tolerant adaptive fuzzy output-feedback approach for fractional-order strict-feedback systems. This control structure would assure the considered system stability through selection of the appropriate Lyapunov candidate function. Two numerical simulations are run to exhibit the validity herein.     

Distributed Control Strategy of Microgrid Based on the Concept of Cyber Physical System

For distributed energy resources (DERs) in islanded microgrid (MG), to improve the control effect on the output voltages and frequency from droop control, a novel distributed control strategy is proposed in this article based on the concept of cyber physical system (CPS). The novel control structure is consisted by the cyber and the physical layers. In the cyber layer: firstly, the communication structures of overall microgrid and single DER are constructed; then, based on the communication structures, the influence of time-delay (delay) and packet loss (loss) on consensus control is analyzed in this article; And then, an event-triggered mechanism combined with adapt virtual leader-following consensus control (AVLFCC) and predictive compensation is proposed in this layer. It is used to solve the problem of time-varying delay and loss rate in the process of consensus control. In the physical layer: firstly, the droop control is used as the primary control on the output voltages and frequency of DERs; then, a novel secondary control method is proposed by using the event-triggered mechanism. And finally, the simulation results confirm the effectiveness of the novel distributed control strategy under communication problems (delay and loss) and during plug-and-play operation.     

Control and synchronization of fractional-order chaotic satellite systems using feedback and adaptive control techniques

In this article, we present the basic concepts of fractional calculus and control and synchronization of fractional-order chaotic satellite system . Existence and uniqueness solutions of fractional-order satellite system are discussed and local stability of the system at the equilibrium points are studied. The lowest dimension of chaotic attractor of satellite system is 2.88 which is obtained through utilization of the fractional dynamics and computational simulation. Lyapunov exponents and bifurcation diagrams are drawn to measure the existence of chaos in the system. Feedback control method for chaos control in the fractional-order satellite system is achieved. Synchronization of two identical noninteger order chaotic satellite systems are achieved through adaptive control methodology.