Yingchun Wang

Networked Synchronization Control of Coupled Dynamic Networks With Time-Varying Delay

This paper is concerned with the networked synchronization control problem of coupled dynamic networks (CDNs) with time-varying delay. First, both the data packet dropouts and network-induced delays are taken into account in the synchronization controller design. A Markovian jump process is induced to describe the packet dropouts. The network-induced delays are interval time varying and depend on the Markovian jump modes. A new closed-loop coupled dynamic error system (CDES) with Markovian jump parameters and interval time-varying delays is constructed. Second, using the Kronecker product technique and the stochastic Lyapunov method, a delay-dependent sufficient criterion of stochastic stability is obtained for the closed-loop CDES, which also guarantees that the CDNs are stochastically synchronized. Finally, a simulation example is given to demonstrate the effectiveness of the proposed result.

Stochastic stability analysis of neutral-type impulsive neural networks with mixed time-varying delays and Markovian jumping

In this paper, the stochastic stability problem of neutral-type impulsive neural networks (NINNs) with mixed time-varying delays and Markovian jumping is investigated. By utilizing the Lyapunov-Krasovkii functional approach and linear matrix inequality (LMI) technique, we obtain some novel globally exponentially stable results. Delay-dependent sufficient condition for the above problem is obtained, which is usually less conservative than delay-independent ones. An example is given to show the effectiveness of the obtained results.

Robust state/fault estimation and fault tolerant control for T–S fuzzy systems with sensor and actuator faults

Abstract This paper addresses the problems of state/fault estimation (FE) and fault tolerant control (FTC) for a class of Takagi–Sugeno (T–S) fuzzy systems subject to simultaneously external disturbances, sensor and actuator faults. A fuzzy-reduced-order robust state/fault estimation observer is proposed in this paper. The observer can not only estimate system state, sensor and actuator faults simultaneously, but also attenuate the influence of disturbances. Compared with the existing results, the observer has a wider application range and a lower dimension. Using the information of estimation, an observer-based fault tolerant controller is designed to compensate the fault effect and guarantee the stability of closed-loop system. In the paper, the observer and the controller are designed separately, which can avoid the coupling between them. As a result, the gain matrices of the observer and the controller can be calculated separately. At last, the simulations show the effectiveness of the proposed method.

Neural network-based online H∞ control for discrete-time affine nonlinear system using adaptive dynamic programming

In this paper, the problem of H ∞ control design for affine nonlinear discrete-time systems is addressed by using adaptive dynamic programming (ADP). First, the nonlinear H ∞ control problem is transformed into solving the two-player zero-sum differential game problem of the nonlinear system. Then, the critic, action and disturbance networks are designed by using neural networks to solve online the Hamilton-Jacobi-Isaacs (HJI) equation associating with the two-player zero-sum differential game. When novel weight update laws for the critic, action and disturbance networks are tuned online by using data generated in real-time along the system trajectories, it is shown that the system states, all neural networks weight estimation errors are uniformly ultimately bounded by using Lyapunov techniques. Further, it is shown that the output of the action network approaches the optimal control input with small bounded error and the output of the disturbance network approaches the worst disturbance with small bounded error. At last, simulation results are presented to demonstrate the effectiveness of the new ADP-based method.

Control synthesis problem for networked linear sampled-data control systems with band-limited channels

Abstract This paper addresses the control synthesis problem of networked linear sampled-data control systems (NLSCSs) with band-limited channels. First, since there exist packet dropouts when the information is transmitted through the band-limited channels, a novel compression compensation (C–C) method is proposed to ensure the integrity of transmission. Based on this method, a compound control strategy is established to deal with the data transmission synchronization problem under the band-limited channels. Then, a nonlinear switched system model with uncertainty is constructed, in which both the inter-sampler behavior and the packet dropouts behavior are considered. Furthermore, some more general stability results of the NLSCSs with band-limited channels are obtained by using a packet dropouts dependent Lyapunov functional method, and then the compound state feedback controller can be designed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed results.

Adaptive neural dynamic surface control for a class of uncertain nonlinear systems with disturbances

In this paper, adaptive dynamic surface control is investigated for a class of uncertain nonlinear systems with unknown bounded disturbances in strict-feedback form. Dynamic surface control technique is connected with radial basis function neural networks (RBFNNs) based control framework to avoid the explosion problem of complexity. The composite laws are constructed by prediction error and compensated tracking error between system state and serial-parallel estimation model for NN weights updating. Using Lyapunov techniques, the uniformly ultimate boundedness stability of all the signals in the closed-loop systems is guaranteed. Simulation results illustrate the superiority of the proposed scheme and verify the theoretical analysis.

Robust fuzzy decentralized control for nonlinear interconnected descriptor systems

A fuzzy state model for nonlinear interconnected descriptor systems is presented by applying a T-S fuzzy descriptor model. Based on the model, a robust fuzzy decentralized controller design method is given. Then, a sufficient condition is obtained in terms of a LMI. In addition, a less conservative LMI design approach is employed to find a stable fuzzy decentralized feedback controller. The effectiveness and the design procedures of the controller presented are illustrated by an example.

An SOS-Based Observer Design for Discrete-Time Polynomial Fuzzy Systems

This paper investigates the polynomial fuzzy observer design for discrete-time uncertain polynomial systems. Three classes of discrete-time polynomial fuzzy systems are studied via a sum of squares (SOS) approach. A polynomial fuzzy system is a more general representation of the well-known Takagi–Sugeno (T–S) fuzzy system. The conditions in the proposed approach are derived in terms of SOS, which is the extension of the LMI method. Hence, the conditions obtained in this paper are more general than the corresponding LMI approaches for T–S fuzzy systems. All the design conditions in the proposed approach can be symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. Numerical examples are provided to demonstrate the validity and applicability of the proposed SOS-based design approach.

Adaptive control for a class of uncertain strict-feedback nonlinear systems based on a generalized fuzzy hyperbolic model

In this study, we propose an effective method for designing an adaptive controller for a class of uncertain strict-feedback nonlinear systems with unknown bounded disturbances. During the controller design process, all of the unknown functions are accumulated at the intermediate steps to approximate the last step. In addition, only one generalized fuzzy hyperbolic model is used to approximate the total unknown functions for the system. Thus, only the actual control law needs to be implemented and one adaptive law is proposed for the overall controller design process. As a result, the controller design is much simpler and the computational burden is reduced greatly. Using Lyapunov techniques, we obtain the uniformly ultimately bounded stability of all the signals for the closed-loop system. Our simulation results verified the theoretical analysis and they illustrated the superior performance of the method proposed in this study.

H ∞ output feedback control for uncertain systems with time-varying delays

In this paper a new approach is proposed to design an H∞ output feedback controller for uncertain systems with time-varying delay. By defining a new relaxed Lyapunov parameter matrix and introducing some free-weighting matrices, convex linear matrix inequality (LMI) based sufficient conditions are established to ensure robust and exponential stability and to meet a prescribed H∞ performance level for the resulting closed-loop system. The advantages of the proposed approach are that the Lyapunov parameter matrix is relaxed and the conservatism of results is reduced largely. Moreover, due to the convex LMI form, it can be directly tested and solved the controller parameters by LMI toolbox in Matlab and iterative algorithm is not required. Two examples are given to show the effectiveness and the less conservatism of the results.