Adaptive output tracking of linear uncertain discrete-time networked systems over switching topologies

ABSTRACT

In this paper, we study the asymptotic output tracking problem for a class of minimum phase uncertain linear discrete-time multi-agent systems over jointly connected digraphs. As the systems contain arbitrarily large uncertain parameters, the robust feedback control technique does not work. We develop a distributed adaptive control law composed of a distributed observer and a purely decentralised adaptive control law. We first establish a stability result for a class of linear switched systems, which extends the existing results. This stability result leads to a novel distributed observer for the leader system which estimates the leader's signal using the output of the leader system locally and passes the estimated leader's signal to each follower. We then further show that the distributed adaptive control law solves our problem under some mild conditions. An example is used to illustrate the effectiveness and generality of our approach.     

Distributed control of uncertain multiagent systems for tracking a leader with unknown fractional‐order dynamics

This paper proposes distributed adaptive cooperative control algorithms for second‐order agents to track a leader with unknown dynamics. The models of the followers and the leader are composed of uncertain nonlinear components. The order of the leader's dynamics is unknown and can be fractional. Only the single output information is shared among neighbored agents. To simplify the control design, linearly parameterized neural networks are used to approximate the unknown functions. We first present an adaptive control for leaderless consensus and then extend the method to the tracking problem. Thorough theoretical proofs as well as numerical simulation are included to verify the results. Compared with relevant literature, the new approach applies to a larger variety of systems because (i) knowledge about the structure of leader's model is unnecessary; (ii) the unknown functions in different agents' dynamics can be diverse and arbitrary, in other words, the algorithms apply to heterogeneous agents; (iii) the results can be simply used without parameter calculations.     

Cooperative tracking control for linear multi-agent systems with external disturbances under a directed graph

This paper studiesthe cooperative tracking control problem for multi-agent systems with unknown external disturbances under a directed graph. The leader's input is nonzero and unavailable to the followers. Based on the relative output measurements of neighbouring agents, a novel observer-based cooperative tracking protocol is presented, where the a group of intermediate estimators are constructed to estimate the tracking errors and the combined signal of the disturbances and the leader's input simultaneously, then decentralised tracking protocols are designed based on the obtained estimates. The states of the global tracking error system are proved to be uniformly ultimately bounded. A numerical example of aircraft illustrates the effectiveness of the cooperative tracking protocol.     

Fully distributed bipartite output consensus of heterogeneous linear multiagent systems based on event‐triggered transmission mechanism

This study investigates the fully distributed bipartite output consensus issue of heterogeneous linear multiagent systems (HLMASs) based on event‐triggered transmission mechanism. Both the cooperative interaction and the antagonistic interaction between neighbor agents are considered. A fully distributed bipartite compensator consisting of time‐varying coupling gain and dynamic event‐triggered mechanism is first proposed to estimate the leader's states. Different from the existing schemes, the proposed compensator is independent of any global information of the network topology, is capable of achieving intermittent communication between neighbors, and is applicable for the signed communication topology. Then the distributed output feedback control protocol is developed such that the fully distributed bipartite event‐triggered output consensus problem can be achieved. Moreover, we extend the results in HLMASs without external disturbances to HLMASs with disturbances, which is more challenging in three cases (a) the disturbances are not available for measurement, (b) the disturbances suffered by each agent are heterogeneous, and (c) the disturbances are not required to be stable or bounded. It is proven that the proposed controllers fulfill the exclusion of Zeno behavior in two consensus problems. Finally, two examples are provided to illustrate the feasibility of the theoretical results.     

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

This paper presents a novel distributed adaptive control algorithm for uncertain higher‐order nonlinear multiagent systems subject to output constraints and unknown control directions. Regarding the latter, a generic class of cases is considered, allowing completely unknown and even nonidentical control directions. Furthermore, the communication topology is only required to contain a fixed directed spanning tree. To guarantee the output constraints and address the asymmetric directed communication topology, a new reference output using the transformation strategy is introduced for each agent, benefiting from which the consensus problem of the multiagent system is recast as local tracking control problems of single agents. Then, the distributed control algorithm is recursively established based on the backstepping technique and the Nussbaum‐type function. By leveraging the unique properties of the Laplacian matrix on directed graphs and matrix theory, it is shown that, under the proposed distributed algorithm, uniform boundedness of all closed‐loop signals can be ensured, and asymptotic consensus is achieved without violation of the output constraints. Finally, simulation studies on the angle control of single‐link robots are given to verify the effectiveness of the proposed algorithm.     

网络化多轴运动控制系统的容侵同步控制

针对网络攻击下的不确定网络化多轴运动控制系统,提出一种基于分布式中间观测器的容侵同步控制方法.首先将不确定性分解为匹配分量和不匹配分量,继而通过分布式中间观测器估计由执行器攻击、领航者的非零输入以及匹配不确定性分量构成的组合未知输入信号,进而设计基于估计值的容侵同步控制协议对匹配未知输入进行有效补偿,同时通过调节特定参数充分抑制不匹配不确定性效应,最终得到满意的容侵同步控制性能.     

Formation control for a class of nonlinear multiagent systems using model‐free adaptive iterative learning

In this paper, the problem of formation control is considered for a class of unknown nonaffine nonlinear multiagent systems under a repeatable operation environment. To achieve the formation objective, the unknown nonlinear agent's dynamic is first transformed into a compact form dynamic linearization model along the iteration axis. Then, a distributed model‐free adaptive iterative learning control scheme is designed to ensure that all agents can keep their desired deviations from the reference trajectory over the whole time interval. The main results are given for the multiagent systems with fixed communication topologies and the extension to the switching topologies case is also discussed. The feature of this design is that formation control can be solved only depending on the input/output data of each agent. An example is given to demonstrate the effectiveness of the proposed method.     

基于分布式观测器的多自主水下机器人确定学习控制

针对多自主水下机器人的一致性跟踪问题,提出一种基于新型分布式观测器的一致性跟踪策略.对于具有未知非线性动态的引导者,首先利用确定学习理论将引导者的未知动态表示为具有常数权值的径向基函数神经网络;然后,设计一种新型的分布式观测器,并证明其观测误差能够指数收敛到零的小邻域内;接着,利用观测到的引导者状态信息,通过反步法和动态面技术为每个跟随者设计分布式跟踪控制器,通过Lyapunov稳定性分析,证明闭环系统中所有信号都是最终一致有界的,且跟随者的跟踪误差能够收敛到原点的小邻域内;最后,通过仿真验证所提出方案的有效性.     

A self-tuning adaptive distributed observer approach to the cooperative output regulation problem for networked multi-agent systems

In this paper, we first propose a self-tuning distributed observer for a multi-agent system, which is capable of providing the estimation of the leader's signal to various followers without assuming all the followers know the system matrix of the leader. We then further develop a novel adaptive distributed control law to solve the cooperative output regulation problem for linear heterogeneous multi-agent systems. This control law offers two advantages in that it makes less use of the information of the network as well as the information of the leader and external disturbances, and it avoids calculating the observer gain.     

Decentralized adaptive consensus control for discrete‐time heterogeneous semiparametric multiagent systems

Different from the consensus control of traditional multiagent systems, this paper studies the decentralized adaptive consensus control for discrete‐time heterogeneous hidden leader‐following semiparametric multiagent system, in which the dynamic equation of each agent has both parametric uncertainties and nonparametric uncertainties. In the considered system, there is a hidden leader agent who can receive the reference signal, but it can only affect the states of those agents who are in its neighborhood. For other following agents, they do not know the leader's existence or the reference signal, and they can only receive information from their neighbors. Our goal is to design decentralized adaptive controllers to make sure that all agents can track the reference signal, and the closed‐loop system achieves consensus in the presence of mutual coupling relations. Due to the existence of both parametric and nonparametric uncertainties in the system, we need to estimate them separately. For the parametric part, we propose a novel dead zone with threshold converging to zero to modify the traditional gradient update law, while for the nonparametric part, we introduce an auxiliary variable including both two uncertainties to facilitate the nonparametric uncertainties compensation. Based on the certainty equivalence principle in adaptive control theory, the decentralized adaptive controller is designed for each agent to make sure that all of them can track the reference signal. Finally, under the proposed control protocol, strict mathematical proofs are given by using Lyapunov theory; then, simulation results are provided to demonstrate the effectiveness of proposed decentralized adaptive controllers.     

Distributed adaptive leader-following tracking control of networked Lagrangian systems with unknown control directions under undirected/directed graphs

This paper addresses the leader-following consensus problem of networked Lagrangian systems with unknown control directions and uncertain dynamics. For undirected graphs and directed graphs, two types of distributed control protocols are proposed without assuming that the leader's position information is linearly parameterised. It is proven that all signals in the closed-loop system are bounded, and a leader-following consensus can be achieved with the proposed corresponding protocols. These protocols are distributed in the sense that the control input for each Lagrangian system is solely based on local relative position and velocity information from its neighbourhood set and does not require additional information, e.g. acceleration or observer information of its neighbours, thus avoiding the dead-loop problem and reducing the communication burden. Simulations on networked two-link revolute joint arms are given to validate the theoretical findings.     

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

This article investigates the leader‐follower consensus problem of a class of non‐strict‐feedback nonlinear multiagent systems with asymmetric time‐varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding‐mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time‐varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean‐value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader‐follower consensus tracking control is achieved without violating the ATVSC, and all closed‐loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.     

Data rate for output feedback consensus of uncertain nonlinear multiagent systems

This article considers the data rate problem for output feedback consensus of uncertain nonlinear multiagent systems. Each agent is modeled by an nth order integrator with unknown nonlinear dynamics and unmeasurable states. An (n+2)th order extended state observer (ESO) is first designed to estimate the unmeasurable agent states and the unknown nonlinear dynamics. Based on the output of the ESO and a dynamic encoding and decoding scheme, a distributed consensus protocol is proposed. It is shown that, for a connected undirected network with nth order uncertain nonlinear agents, consensus can be guaranteed with merely one bit information exchange between each pair of adjacent agents at each time step.     

Incentive strategies dealing with uncertainty about the follower's MCDM behaviour

This paper investigates the incentive problem of two-person Stackelberg game where the follower's responses to the leader's strategy are determined based on multiple criteria decision-making (MCDM) and the follower's preference is unknown to the leader. We first focus on the single-stage (or one-shot) game and propose a minimum-deviation incentive strategy that minimizes the influence of the follower's preference upon the leader's objective function. We also present a way to construct such a strategy. Second, we investigate the multistage game where the leader uses a feedback strategy. We explore a process along which the leader extracts information about the follower's preference from the follower's responses and uses the minimum-deviation incentive strategy at each stage until he acquires enough information to know the follower's preference. Finally, we consider the multistage case where the leader can employ a memory strategy. In this case we propose a kind of memory strategy with dual functions that makes the game's outcome irrelevant to the follower's preference and necessarily leads to the leader's most desirable outcome, even though the leader does not possess any a priori knowledge about the follower's preference. We also derive existence conditions and illustrate a construction method for such memory strategies.     

Consensus tracking control of discrete‐time second‐order agents over switching signed digraphs with arbitrary antagonistic relations

This article studies the problem of consensus tracking control for second‐order agents in multiagent systems over switching signed digraphs. Compared with the existing consensus tracking works on the structurally balanced signed digraph where the antagonistic relations exist only between two independent subgroups, this article explores a more general case for the first time, in the sense that the antagonistic relation is allowed between any two agents. On the basis of the design of a cooperation‐antagonism environment‐based distributed algorithm, suitable model transformation vectors are utilized to convert the stability of original system into a product convergence problem of time‐varying superstochastic matrices. By analyzing the convergence, algebraic conditions between positive and negative weights are established to ensure that all followers can eventually reach the leader's state under switching signed digraphs with arbitrary antagonistic relations. Simulation examples are provided to demonstrate the effectiveness of our results.     

Semi‐global bipartite output consensus of heterogeneous multi‐agent systems subject to input saturation by finite‐time observer

In this paper, the semi‐global bipartite output consensus problem of heterogeneous linear multi‐agent systems is studied. Compared with related works, both cooperative interactions and antagonistic interactions between agents are considered, and the input saturation on each follower is taken into account. First, two distributed finite‐time observers are designed to recover the leader's state. Particularly, the setting time can be independent of any initial states. Due to the antagonistic interactions, estimation values are the same as the leader's state in modulus but may not in sign. Then, the low‐gain feedback technique is used to develop the distributed control law for each follower. Moreover, we summarize a framework for solving the semi‐global bipartite output consensus problem of heterogeneous multi‐agent systems subject to input saturation. Finally, examples are given to illustrate the results.     

Adaptive fractional-order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs-based distributed estimator

This paper mainly solves two major problems that are unavoidable in leader–follower formation process of quadrotor UAV group: the existence of external uncertainty disturbance and communication limited between quadrotor unmanned aerial vehicle (UAV) group. To solve the problem that only one of the followers in the leader–follower formation can obtain the leader's information, an improved distributed estimator is proposed in this paper, which can accurately estimate the leader's information for each follower. In addition, in order to eliminate the influence of uncertain external disturbance on the performance of quadrotor UAV, an adaptive estimation law is designed based only on velocity and position variables. For the attitude and position subsystem of the quadrotor UAV, a sliding surface with fractional-order term is designed. Which makes the quadrotor UAV tracking error system obtain good robustness at the stage of reaching the sliding surface and fast convergence and accurate tracking performance in the sliding stage. Based on Lyapunov stability theory, the convergence results are analyzed strictly. The results show that the algorithm can make the position distance between leader and followers converge to the desired offset. Simulation results verify the effectiveness and superiority of the control algorithm.     

An Active Disturbance Rejection Approach to Leader‐Follower Controlled Formation

This article describes the design of a linearizing, observer‐based, robust dynamic feedback control scheme for output reference trajectory tracking tasks in a leader‐follower non‐holonomic car formation problem. The approach is based on the cars' kinematic models. A radical simplification in the form of a global ultra‐model is proposed on the follower's exact open loop position tracking error dynamics obtained via flatness considerations. This results in a system described by an additively disturbed set of two, second order integrators with non‐linear velocity dependent control input gain matrix. The unknown additive disturbances are modeled as absolutely uniformly bounded time signals which may be locally approximated by arbitrary elements of a sufficiently high degree family of Taylor polynomials. Linear high‐gain Luenberger observers of the generalized proportional integral (GPI) type may be readily designed. These observers include the self updating internal model of the unknown disturbance input vector components in the form of generic, instantaneous, time‐polynomial models. The proposed (GPI) observers, which are the dual counterpart of GPI controllers [17], achieve a simultaneous disturbance estimation and tracking error phase variables estimation. This on‐line gathered information is used to advantage on the follower's feedback controller thus allowing for a simple, yet efficient, disturbance and control input gain cancelation effort. The results are applied to have the follower track a time‐delayed version of the actual leader's trajectory. Experimental results are presented which illustrate the robustness and viability of the proposed approach.     

A disturbance observer based practical coordinated tracking controller for uncertain heterogeneous multi‐agent systems

This paper presents a coordinated tracking controller for multi‐agent systems. We assume that agents are uncertain, nonidentical, and affected by external disturbances. The information available to the tracking controller is a weighted sum of relative measurements. A coordinated tracking controller based on the disturbance observer, which is known as a robust output feedback controller, is designed so that the disturbances acting on agents are attenuated and at the same time the weighted sum of relative measurements approximately satisfies a differential equation defined by the leader's dynamics, which results in practical coordinated tracking. Systematic design procedures of the controller as well as numerical simulations are provided. Copyright © 2014 John Wiley & Sons, Ltd.     

Inertia‐free saturated output feedback attitude stabilization for uncertain spacecraft

In this article, the problem of robust output feedback attitude stabilization control for a class of uncertain spacecraft is investigated, which contains external disturbances, model parameter uncertainty, unknown and uncertain inertia, controller's gain perturbations, measurement errors, and input saturation. The aim of this work is to design a dynamic output feedback controller such that the closed‐loop attitude system is stabilized, while the H_∞ norm of the transfer function from the lumped disturbance and measurement error to output is ensured to be less than a pre‐specified disturbance attenuation level, and the actual control input is confined into a certain range simultaneously. Based on the Lyapunov theory, the existence conditions of such controller are derived in terms of linear matrix inequalities. It is worth mentioning that the controller's additive and multiplicative perturbations are accounted for respectively. An illustrative example is given to demonstrate the effectiveness and advantage of the proposed control design method.