Ancai Zhang

Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks

This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Youngs inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks.

Stabilization of underactuated two-link gymnast robot by using trajectory tracking strategy

This paper concerns the stabilization of an underactuated two-link gymnast robot called acrobot. A trajectory tracking control strategy is presented. First, we carry out a homeomorphous coordinate transformation on the acrobot system that transforms it into a new simplified nonlinear system. And then, a desired motion trajectory is designed for the new system. Finally, we use an equivalent-input-disturbance (EID) method to design a controller that makes the new system asymptotically track the desired trajectory. This enables the acrobot to be swung up from the downward position and to be stabilized at the upright position. The proposed strategy changes the stabilization of the nonlinear acrobot system into that of a linear time-invariant error dynamic system with an artificial disturbance. And it uses a single controller to accomplish the motion control objective of the acrobot. These makes the strategy simple and efficient. Simulation results demonstrate its validity and its superiority over others.

Motion planning and tracking control for an acrobot based on a rewinding approach

This paper concerns motion planning and tracking control for an acrobot. We first introduce an artificial friction torque in order to construct a downward trajectory, and rewind it to make an upward trajectory. Then, we combine the upward trajectory with a stabilizing trajectory to make a complete trajectory. Finally, we use the pole assignment method to design a tracking controller that makes the acrobot exponentially track the whole trajectory. This enables the acrobot to be swung up from the straight-down position and stabilized at the straight-up position. Unlike the most commonly used switching stabilization control methods, the strategy presented here features a single controller for motion control in the whole motion space. It is simple and efficient. Simulation results demonstrate the validity of the method.

Existence and stability of periodic solution of high-order discrete-time Cohen–Grossberg neural networks with varying delays

Abstract This paper studies the existence and stability of periodic solution of the high-order discrete-time Cohen–Grossberg neural networks with varying delays. The properties of M-matrix and the contracting mapping principle are used to obtain a sufficient condition that guarantees the uniqueness and global exponential stability of the periodic solution. In addition, a numerical example is given that demonstrates the effectiveness of the proposed theoretical results.

Finite-time stability of genetic regulatory networks with impulsive effects

We study the finite-time stability of genetic regulatory networks with impulsive effects. Using the method of Lyapunov function, sufficient conditions of the finite-stability, in terms of linear matrix inequalities, are established. A numerical example is provided to further illustrate the significance of our results.

Robust Exponential Synchronization for a Class of Master-Slave Distributed Parameter Systems with Spatially Variable Coefficients and Nonlinear Perturbation

This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs) with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs). With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD) state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs). Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation.

Stability and stabilization of a delayed PIDE system via SPID control

This paper addresses the problem of exponential stability and stabilization for a class of delayed distributed parameter systems, which is modeled by partial integro-differential equations (PIDEs). By employing the vector-valued Wirtinger’s inequality, the sufficient condition of exponential stability of the PIDE system with a given decay rate is investigated. The condition is presented by linear matrix inequality (LMIs). After that, we develop a spatial proportional-integral-derivative state-feedback controller that ensures the exponential stabilization of the PIDE system in terms of LMIs. Finally, numerical examples are presented to verify the effectiveness of the proposed theoretical results.

Dynamic analysis of periodic solution for high-order discrete-time Cohen-Grossberg neural networks with time delays

In this paper, we analyze the dynamic behavior of periodic solution for the high-order discrete-time Cohen-Grossberg neural networks (CGNNs) with time delays. First, the existence is studied based on the continuation theorem of coincidence degree theory and Youngs inequality. And then, the criterion for the global exponential stability is given using Lyapunov method. Finally, simulation result shows the effectiveness of our proposed criterion.

Almost periodic dynamics of the delayed complex-valued recurrent neural networks with discontinuous activation functions

The target of this article is to study almost periodic dynamical behaviors for complex-valued recurrent neural networks with discontinuous activation functions and time-varying delays. We construct an equivalent discontinuous right-hand equation by decomposing real and imaginary parts of complex-valued neural networks. Based on differential inclusions theory, diagonal dominant principle and nonsmooth analysis theory of generalized Lyapunov function method, we achieve the existence, uniqueness and global stability of almost periodic solution for the equivalent delayed differential network. In particular, we derive a series of results on the equivalent neural networks with discontinuous activation functions, constant coefficients as well as periodic coefficients, respectively. Finally, we give a numerical example to demonstrate the effectiveness and feasibility of the derived theoretical results.

Global Stabilization Control of Acrobot Based on Equivalent-Input-Disturbance Approach

Abstract This paper concerns the global stabilization control of an underactuated two-link acrobot in a vertical plane using a new control method based on an equivalent-input-disturbance (EID) approach. The design procedure consists of two steps: (1) A homeomorphous coordinate transformation transforms the acrobot system into a new nonlinear system. (2) The new system is divided into linear and nonlinear parts, and the nonlinear part is taken to be an artificial disturbance. Then, the EID-based approach is used to globally and asymptotically stabilize the system at the origin. This method enables the acrobot to be swung up from any initial position and balanced at the straight-up position. Unlike the most commonly used switching control method, ours features a single controller for both swing-up and balancing control. Simulation results demonstrate the validity of the method.