Hu Shousong

Brief Stochastic optimal control and analysis of stability of networked control systems with long delay

In this paper, stochastic optimal controllers of networked control systems whose network-induced delay is longer than a sampling period are designed for the two cases of the system with either full state information or partial state information. The controllers are shown to render corresponding networked control systems exponentially mean square stable. The optimal estimator of the system state is presented when the system has partial state information and network-induced delay is longer than a sampling period. The separation theorem is proved to still hold in such networked control systems. ? 2003 Elsevier Ltd. All rights reserved.In this paper, stochastic optimal controllers of networked control systems whose network-induced delay is longer than a sampling period are designed for the two cases of the system with either full state information or partial state information. The controllers are shown to render corresponding networked control systems exponentially mean square stable. The optimal estimator of the system state is presented when the system has partial state information and network-induced delay is longer than a sampling period. The separation theorem is proved to still hold in such networked control systems.

Uniformed model of networked control systems with long time delay

Abstract Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCS). The defining feature of an NCS is that information is exchanged using a network among control system components. Two new concepts including long time delay and short time delay are proposed. The sensor is almost always clock driven. The controller or the actuator is either clock driven or event driven. Four possible driving modes of networked control systems are presented. The open loop mathematic models of networked control systems with long time delay are developed when the system is driven by anyone of the four different modes. The uniformed modeling method of networked control systems with long time delay is proposed. The simulation results are given in the end.

Robust output feedback control for time-delay fuzzy systems with persistent bounded disturbances

The robust static output feedback control problem for a class of T-S fuzzy systems with time-varying state delay and disturbances both in the inputs and outputs is discussed. By defining a delay-dependent Lyapunov function, the robust control technique is extended to the time-delay systems, the synthetical design procedures of the static output feedback controllers are derived in terms of the linear matrix inequalities, and the robust performance is optimized by the iteration algorithms. This method can efficiently attenuate the peak of the persistent bounded disturbances, and will be more appealing in some practical applications.

Exponential stability of networked control systems with short time delay

Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems. Based on the linear time-invariant process, the mathematic model of networked control systems is set up when the sensor and the actuator are time driven, the is event driven, and the network induced delay is not longer than a sampling period. Using the optimal control theory, the discrete optimal controller of the networked control system is designed. The structure of proposed controller is simple and convenient to use. The controller can render the networked control systems exponentially stable. In the end the simulation based on the unstable inverted pendulum is studied. The simulation results show the proposed method is effective.

Decentralized robust adaptive control of uncertain nonlinear interconnected large-scale systems

This article surveys a class of large-scale systems with uncertainties and nonlinear interconnected items in its subsystems, and presents a kind of decentralized robust adaptive controller. First, a kind of robust Hinfin output feedback controller is designed for restraining the external disturbances, and then a dynamic structure adaptive neural network is introduced, which can eliminate the uncertainties and nonlinear interconnected items between subsystems, so that every subsystem is independently asymptotical stable and the whole large-scale system is consequently decentralized stable. The simulation results demonstrate the efficiency of the proposed methods.

The robustness of combination of sigmoid function wavelet neural network

The disturbing sensitivity and robustness of combination of sigmoid function wavelet neural network are discussed by making use of probability statistics and symbolic logic. If the faint perturbation appears, the robust invariability condition of wavelet neural network is obtained, and if the sensitive disturbance appears, the sensitivity formula and robustness formula are given. It is proved theoretically that to a certain extent, the more hidden wavelet nerve cells, the less robustness of wavelet neural network. Consequently, it validates analytically the intuitionistic hypothesis of the relationship between hidden layer wavelet nerve cells number and the robustness of wavelet neural network.