A sliding mode approach to H ∞ non-fragile observer-based control design for uncertain Markovian neutral-type stochastic systems

An investigation has been made into the sliding mode control (SMC) problem for singular stochastic Markov systems (SSMSs) in this paper. By using replacement of matrix variables, a new mean square admissibility criterion of SSMSs is proposed first. Based on this admissibility criterion, the desired state-feedback controller is designed to guarantee the closed-loop system to be mean-square admissible. Then, the obtained results given in the form of strict linear matrix inequalities are applied to solve SMC problem of SSMSs. In order to illustrate the workability and applicability of the theoretic results developed, numerical examples are provided.

Sliding Mode Control of Singular Stochastic Markov Jump Systems

In this paper, a full-regulated neural network (NN) with a double hidden layer recurrent neural network (DHLRNN) structure is designed, and an adaptive global sliding-mode controller based on the DHLRNN is proposed for a class of dynamic systems. Theoretical guidance and adaptive adjustment mechanism are established to set up the base width and central vector of the Gaussian function in the DHLRNN structure, where six sets of parameters can be adaptively stabilized to their best values according to different inputs. The new DHLRNN can improve the accuracy and generalization ability of the network, reduce the number of network weights, and accelerate the network training speed due to the strong fitting and presentation ability of two-layer activation functions compared with a general NN with a single hidden layer. Since the neurons of input layer can receive signals which come back from the neurons of output layer in the output feedback neural structure, it can possess associative memory and rapid system convergence, achieving better approximation and superior dynamic capability. Simulation and experiment on an active power filter are carried out to indicate the excellent static and dynamic performances of the proposed DHLRNN-based adaptive global sliding-mode controller, verifying its best approximation performance and the most stable internal state compared with other schemes.

Adaptive Global Sliding-Mode Control for Dynamic Systems Using Double Hidden Layer Recurrent Neural Network Structure

This paper develops an adaptive super-twisting global nonlinear sliding mode control technique for n-link rigid robotic manipulators A novel control law is designed to guarantee elimination of the reaching phase and existence of the sliding mode around the surface right from the initial time Furthermore, the adaptive tuning law eliminates requirement of the knowledge about the upper bounds of external disturbances By using the proposed method, a robust controller is designed so that the tracking error of rigid manipulator is convergent to the global nonlinear sliding surface in a finite time, and strong robustness with respect to large uncertainties and disturbances is guaranteed Illustrative simulations on a two-link elbow robot manipulator and a three degree of freedom rigid manipulator are presented to show the robustness and effectiveness of the suggested design compared to other method Moreover, a simulation as well as experimental study of a rotary inverted pendulum system demonstrates the applicability of the proposed method

Design of an adaptive tracker for n-link rigid robotic manipulators based on super-twisting global nonlinear sliding mode control

This paper proposes a new dynamic PID sliding mode control technique for a class of uncertain nonlinear systems. The offered controller is formulated based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. Furthermore, this approach can eliminate the chattering phenomenon caused by the switching control action and can realize high-precision performance. Moreover, an adaptive parameter tuning method is proposed to estimate the unknown upper bounds of the disturbances. Simulation results for an inverted pendulum system demonstrate the efficiency and feasibility of the suggested technique.

An adaptive chattering-free PID sliding mode control based on dynamic sliding manifolds for a class of uncertain nonlinear systems

This paper is concerned with the stabilization problem for a class of nonlinear systems. Using the global sliding mode control approach, a novel robust control law is established to make the state of system stable and to improve the robustness and the stability of system. A new reaching law is introduced to reduce the chattering. Finally, the method is applied to chaotic systems and an example of the chaotic system is given to illustrate the advantage of the proposed method.

Global sliding mode control and application in chaotic systems

The problem of H ∞ sliding mode control for uncertain time-delay systems subjected to input nonlinearity is investigated. Using the sliding mode control, a robust law is established such that the reachability of the sliding surface in the state-estimation space is guaranteed, and the sufficient condition for asymptotic stability of the error system and sliding mode dynamics with disturbance attenuation level is derived via linear matrix inequality (LMI). Finally, a simulation example is presented to verify the validity of the proposed method.

H∞ non-fragile observer-based sliding mode control for uncertain time-delay systems

This paper is concerned with the problem of the global asymptotic stability of a class of interval neural networks with discrete and distributed delays of neutral type. Based on the Lyapunov stability theory, a novel robust delay-dependent criterion is derived in terms of linear matrix inequality (LMI). Finally, an example illustrates the validity of the proposed method.

Short Communication: Global stability analysis of interval neural networks with discrete and distributed delays of neutral type

The problem of non-fragile observer-based passive control for uncertain time delay systems subjected to input nonlinearity is investigated by using sliding mode control. A novel control law is established such that the sliding surface in the state-estimation space can be reached in a finite time and chattering reduction is obtained. A sufficient condition for passivity and asymptotic stability of the combined system is derived via linear matrix inequality (LMI). Finally, a simulation example is presented to show the validity and advantages of the proposed method.

Wenlin Li

Papers

Global sliding mode control and application in chaotic systems

H∞ non-fragile observer-based sliding mode control for uncertain time-delay systems

Short Communication: Global stability analysis of interval neural networks with discrete and distributed delays of neutral type

Non-fragile observer-based passive control for uncertain time delay systems subjected to input nonlinearity