Hongjing Liang

Output regulation of state-coupled linear multi-agent systems with globally reachable topologies

This paper investigates output regulation problem of state-coupled linear certain and uncertain multi-agent systems with globally reachable topologies. Distributed dynamic state feedback control law is introduced to realize the regulator problem and a general global method for error regulation is established. The Jordan canonical form is used to stabilize the closed-loop control system. Sylvester equation and internal model theory are adopted to achieve the objectives of output regulation for every initial condition in the state space. Finally, numerical simulations are utilized to show the effectiveness of the obtained results.

Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays

This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the coupling configuration matrices are nonsymmetric. A mode-dependent augmented Lyapunov-Krasovskii functional (LKF) is proposed, where some terms involving triple or quadruple integrals are considered, which makes the LKF matrices mode-dependent as much as possible. This gives significant improvement in the synchronization criteria, i.e., less conservative results can be obtained. In addition, by applying an extended Jensens integral inequality and the properties of random variables, new delay-dependent synchronization criteria are derived. The obtained criteria depend not only on upper and lower bounds of mode-delays but also on mathematical expectations and variances of the random coupling strengths. Finally, two numerical examples are provided to demonstrate the feasibility of the proposed results.

Consensus robust output regulation of discrete-time linear multi-agent systems

This paper deals with consensus robust output regulation of discrete-time linear multi-agent systems under a directed interaction topology. The digraph is assumed to contain a spanning tree. Every agent or subsystem is identical and uncertain, but subsystems have different external disturbances. Based on the internal model and general discrete-time algebraic Riccati equation, a distributed consensus protocol is proposed to solve the regulator problem. A numerical simulation demonstrates the effectiveness of the proposed theoretical results.

Stochastic synchronization for Markovian coupled neural networks with partial information on transition probabilities

This paper focuses on stochastic synchronization for Markovian coupled neural networks with partial information on transition probabilities and random coupling strengths. The coupling configuration matrices are not restricted to be symmetric, and the coupling strengths are mutually independent random variables. By designing a novel augmented Lyapunov-Krasovskii functional and using reciprocally convex combination technique and the properties of random variables, new delay-dependent synchronization criteria in terms of linear matrix inequalities are derived. The obtained criteria depend not only on upper and lower bounds of delay but also on mathematical expectations and variances of random coupling strengths. Numerical examples are provided to verify the effectiveness of the presented results.

Output regulation for heterogeneous linear multi-agent systems based on distributed internal model compensator

Abstract This article considers robust output regulation of uncertain heterogeneous multi-agent systems in the case that all the agents have non-identical nominal dynamics. The directed communication graph contains a spanning tree and the exosystem is as its root. Since not all the agents can access the information of the exosystem, the distributed compensator is used for the unaccessible part. The dynamic state feedback control law and dynamic output feedback control law are proposed under this topological structure. Then we give a novel compact form and a general global method to solve the robust output regulation problem based on internal model principle. Finally, some examples are presented to illustrate the effectiveness of our results.

Nearly Optimal Control Scheme Using Adaptive Dynamic Programming Based on Generalized Fuzzy Hyperbolic Model

Abstract An effective scheme is presented to design the nearly optimal control for continuous-time (C-T) nonlinear systems. The generalized fuzzy hyperbolic model (GFHM) is used to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation (i.e., the value function) for the first time. Further, the approximate solution is utilized to obtain the nearly optimal control. The value function is estimated by only using single GFHM, which captures the mapping between the state and value function. First, we illustrate the design process for the nearly optimal control involving nonlinear systems. Then stability conditions and conservatism analysis are given, and the approximate errors are proven to be uniformly ultimately bounded (UUB). Finally, a numerical example illustrates the effectiveness of our method and an example compared with the adaptive method based on dual neural-network models is used to demonstrate the advantages of our method.

Cooperative robust output regulation for heterogeneous second-order discrete-time multi-agent systems

This paper considers the cooperative robust output regulation for second-order discrete-time multi-agent systems. Each agent could access the information with its neighbors under the directed network topology. A distributed dynamic state feedback control law is designed. A stability region is given for the discrete-time multi-agent systems, and internal model method is used for the robust output regulation problem. At last, numerical simulation is utilized to show the effectiveness of the obtained results.

Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems.

This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results.

Local stochastic synchronization for Markovian neutral-type complex networks with partial information on transition probabilities

This paper investigates local stochastic synchronization of Markovian neutral-type complex networks with partial information on transition probabilities. The coupling configuration matrices are not restricted to be symmetric. By designing a new augmented Lyapunov-Krasovskii functional and using reciprocally convex combination technique, new delay-dependent synchronization criterion in terms of linear matrix inequalities is derived. The obtained criterion depends on upper and lower bounds of delays. Numerical examples are provided to verify the effectiveness of the presented results.

Optimal control design for nonlinear systems: Adaptive dynamic programming based on fuzzy critic estimator

In this paper, an optimal control design approach based on fuzzy critic estimator (FCE) is presented for nonlinear continuous-time systems. The main idea of our study is to approximate the solution (i.e., value function) of the Hamilton-Jacobi-Bellman (HJB) equation by making use of FCE as an estimator/approximator, which is utilized to obtain the optimal control. The value function is estimated by FHM, which captures the mapping between the state and value function. Firstly, we illustrate the design process of the optimal control involving nonlinear systems. Secondly, we analyze the stability conditions and prove the approximate error is uniformly ultimately bounded (UUB). Finally, a numerical example is given to illustrate the effectiveness and advantages of our approach.