Robust Leader-Following Output Regulation of Uncertain Multi-Agent Systems With Time-Varying Delay

In this paper, the robust analysis and design of leader-following output regulation for multi-agent systems described by general linear models is given in presence of timevarying delay and model uncertainty. To this aim, a new regulation protocol for the closed-loop multi-agent system under a directed graph is proposed. An important specification of the proposed protocol is to guarantee the leader-following output regulation for uncertain multi-agent systems with both stable and unstable agents. Since many signals can be approximated by a combination of the stationary and ramp signals, the presented results work for adequate variety of the leaders. The analysis and design conditions are presented in terms of certain matrix inequalities. The method proposed can be used for both stationary and ramp leaders. Simulation results are presented to show the effectiveness of the proposed method.

H_∞ Output Feedback Control for Stochastic Systems with Mode-dependent Time-varying Delays and Markovian Jump Parameters

This paper deals with the H∞ control problems of Markovian jump systems with mode-dependent time delays. First, considering the mode-dependent time delays, a different delay-dependent H∞ performance condition for Markovian jump systems is proposed by constructing an improved Lyapunov-Krasovskii function. Based on this new H∞ disturbance attenuation criterion, a full-order dynamic output feedback controller that ensures the exponential mean-square stability and a prescribed H∞ performance level for the resulting closed-loop system is designed. Illustrative numerical examples are provided to demonstrate the effectiveness of the proposed approach.

H_∞ output tracking control for flight control systems with time-varying delay

For flight control systems with time-varying delay, an H∞ output tracking controller is proposed. The controller is designed for the discrete-time state-space model of general aircraft to reduce the effects of uncertainties of the mathematical model, external disturbances, and bounded time-varying delay. It is assumed that the feedback-control loop is closed by the communication network, and the network-based control architecture induces time-delays in the feedback information. Suppose that the time delay has both an upper bound and a lower bound. By using the Lyapu- nov-Krasovskii function and the linear matrix inequality （LMI）, the delay-dependent stability criterion is derived for the time-delay system. Based on the criterion, a state-feedback H∞ output tracking controller for systems with norm-bounded uncertainties and time-varying delay is presented. The control scheme is applied to the high incidence research model （HIRM）, which shows the effectiveness of the proposed approach.

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs,a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents＇ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered.The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.

Passivity Analysis of Impulsive Complex Networks

In this paper, we first investigate input passivity and output passivity for a class of impulsive complex networks with time-varying delays. By constructing suitable Lyapunov functionals, some input passivity and output passivity conditions are derived for the impulsive complex networks. Finally, an example is given to show the effectiveness of the proposed criteria.

Time-varying output feedback H∞control for switched systems based on mixed switching

This article investigates time-varying dynamic output feedbackH∞control problem for discretetime switched systems by using a time-varying Lyapunov function.Aswitching rule that depends on available information provided by measured output and time simultaneously is designed for the system with all unstable subsystems.Conditions for l2-gain performance and time-varying controller synthesis are obtained under this switching rule.It provides a more general framework of analyzing discrete-time switched linear systems as it contains the min-switching as special cases when dwell time is not enforced.Finally,an example shows the effectiveness of the proposed method.

Consensus control of feedforward nonlinear multi-agent systems:a time-varying gain method

In this paper,the leader–follower consensus of feedforward nonlinear multi-agent systems is achieved by designing the distributed output feedback controllers with a time-varying gain.The agents dynamics are assumed to be in upper triangular structure and satisfy Lipschitz conditions with an unknown constant multiplied by a time-varying function.A time-varying gain,which increases monotonously and tends to infinity,is proposed to construct a compensator for each follower agent.Based on a directed communication topology,the distributed output feedback controller with a time-varying gain is designed for each follower agent by only using the output information of the follower and its neighbors.It is proved by the Lyapunov theorem that the leader–follower consensus of the multi-agent system is achieved by the proposed consensus protocol.The effectiveness of the proposed time-varying gain method is demonstrated by a circuit system.

Robust H_∞ static output feedback control of discrete-time switched polytopic linear systems with average dwell-time

This paper investigates the problem of robust exponential H∞ static output feedback controller design for a class of discrete-time switched linear systems with polytopic-type time-varying parametric uncertainties. The objective is to design a switched static output feedback controller guaranteeing the exponential stability of the resulting closed-loop system with a minimized exponential H∞ performance under average dwell-time switching scheme. Based on a parameter-dependent discontinuous switched Lyapunov function combined with Finsler＇s lemma and Dualization lemma, some novel conditions for exponential H∞ performance analysis are first proposed and in turn the static output feedback controller designs are developed. It is shown that the controller gains can be obtained by solving a set of linear matrix inequalities （LMIs）, which are numerically efficient with commercially available software. Finally, a simulation example is provided to illustrate the effectiveness of the proposed approaches.

Event-triggered adaptive tracking control of a class of nonlinear systems with asymmetric time-varying output constraints

This article investigates the event-triggered adaptive neural network(NN)tracking control problem with deferred asymmetric time-varying(DATV)output constraints.To deal with the DATV output constraints,an asymmetric time-varying barrier Lyapunov function(ATBLF)is first built to make the stability analysis and the controller construction simpler.Second,an event-triggered adaptive NN tracking controller is constructed by incorporating an error-shifting function,which ensures that the tracking error converges to an arbitrarily small neighborhood of the origin within a predetermined settling time,consequently optimizing the utilization of network resources.It is theoretically proven that all signals in the closed-loop system are semi-globally uniformly ultimately bounded(SGUUB),while the initial value is outside the constraint boundary.Finally,a single-link robotic arm(SLRA)application example is employed to verify the viability of the acquired control algorithm.

EIGENSTRUCTURE ASSIGNMENT FOR TIME-VARYING LINEAR SYSTEMS

The problem of eigenstructure assignment via output feedback for time-varying linearsystems is treated, and the sufficient and necessary condition and two simple effective algorithmsare presented. Two forms of parametric representations of the set of closed loop eigenvectormatrices and the set of feedback gains with respect to the closed loop eigenvalues and twogroups of parameter vectors are established. Without any constraint to the closed loop poles,the obtained results have generalized many previous results even in the constant case, andhave also overcome their defects.

Bipartite consensus for nonlinear time-delay multiagent systems via time-varying gain control method

The bipartite consensus problem is addressed for a class of nonlinear time-delay multiagent systems in this paper.Therein,the uncertain nonlinear dynamics of all agents satisfy a Lipschitz growth condition with unknown constants,and part of the state information cannot be measured.In this case,a time-varying gain compensator is constructed,which only utilizes the output information of the follower and its neighbors.Subsequently,a distributed output feedback control protocol is proposed on the basis of the compensator.According to Lyapunov stability theory,it is proved that the bipartite consensus can be guaranteed by means of the designed control protocol.Different from the existing literature,this paper studies the leader-follower consensus problem under a weaker connectivity condition,i.e.,the signed directed graph is structurally balanced and contains a directed spanning tree.Two simulation examples are carried out to show the feasibility of the proposed control strategy.

Observer-Based Adaptive Neural Iterative Learning Control for a Class of Time-Varying Nonlinear Systems

In this paper an adaptive iterative learning control scheme is presented for the output tracking of a class of nonlinear systems. An observer is designed to estimate the tracking errors. A mixed time domain and s-domain representation is constructed to derive an error model with relative degree one for our purpose. And time-varying radial basis function neural network is employed to deal with system uncertainty. A new signal is constructed by using a first-order filter, which removes the requirement of strict positive real(SPR) condition and identical initial condition of iterative learning control. Based on property of hyperbolic tangent function,the system tracing error is proved to converge to the origin as the iteration tends to infinity by constructing Lyapunov-like composite energy function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.

Delay-dependent Wide-area Damping Controller Synthesis Approach Using Jensen’s Inequality and Evolution Algorithm

A time-delay-dependent wide-area damping controller synthesis approach,based on Jensen’s integral inequality and evolution algorithm,is developed to suppress the adverse effect of time delay on the supplemental control of high-voltage direct current(DC)transmission systems.Initially,the state-space model of hybrid AC/DC systems with time delay is derived and the delay-dependent criteria for the stability of the closed-loop system are provided based on Jensen’s integral inequality.Subsequently,initial solutions are randomly generated to overcome the difficulty of solving the nonlinear matrix inequality.Finally,the time-delay stability upper bound of the controller is optimized using the differential evolution algorithm.In comparison to popular time-delay stable controller design methods,such as the free-weighting-matrix approach,the proposed method based on output feedback realization requires fewer decision variables and is more suitable for large-scale hybrid AC/DC systems.Three examples are introduced to verify the effectiveness of the proposed method.