Xianwen Gao

Controller design for time-delay system with stochastic disturbance and actuator saturation via a new criterion

Abstract This paper deals with the problem of controller design for time-delay system with stochastic disturbance and actuator saturation. By use of more appropriate Lyapunov–Krasovskii functional (LKF) and a new criterion for the domain of attraction, less conservative conditions for stochastic stability are proposed. Then, the difficulties of the domain of attraction confronted in system analysis and synthesis can be overcome. These sufficient conditions are derived in terms of linear matrix inequality (LMI). Finally, two practical examples demonstrate the validity of the given results.

Exponential stability and L1-gain analysis for positive time-delay Markovian jump systems with switching transition rates subject to average dwell time

Abstract The paper deals with the problems of exponential stability and L 1 -gain analysis for positive time-delay Markovian jump systems (MJSs) with switching transition rates. Another set of useful regime-switching model is given, which extends fixed transition rates to time-varying transition rates. By resorting to the linear co-positive Lyapunov function and average dwell time, sufficient conditions for exponential stability are proposed in terms of standard linear programming. Based on the obtained results, L 1 -gain performance is analyzed. Finally, an example is proposed to illustrate the validity of the main results.

Further results on finite-time stabilisation for stochastic Markovian jump systems with time-varying delay

ABSTRACT In this paper, we study the issue of finite-time stabilisation for stochastic Markovian jump systems with time-varying delay by considering a new criterion on finite-time stability. By constructing more appropriate Lyapunov–Krasovskii functional, some new conditions for verifying the finite-time stability of the plant as well as controller synthesis are established in standard linear matrix inequalities. The practical example about a single-link robot arm model demonstrates the validity of the main results.

Simulation and Research of Fuzzy Immune Adaptive PID Control in Coke Oven Temperature Control System

Aiming at the coke ovens temperature characteristics of great inertia, pure time-delay, non-linear and time changeable, a fuzzy adaptive PID control method is presented based on the immune feedback regulating law and the adaptive ability of fuzzy logic ratiocination. The academic analysis and simulation results of coke ovens simple model indicate the feasibility and effectiveness the control method

Stabilization for Positive Markovian Jump Systems with Actuator Saturation

This paper considers stabilization for positive Markovian jump systems in the presence of actuator saturation. Firstly, we use a Lyapunov function approach and convex analysis to derive sufficient conditions for stochastic stability and positivity of the continuous- and discrete-time cases. Then, the state feedback controller design and the estimate of the domain of attraction are presented by solving a convex optimization problem with linear matrix inequalities. Finally, numerical examples are given to demonstrate the validity of the main results.

Finite-time dissipativity analysis and design for stochastic Markovian jump systems with generally uncertain transition rates and time-varying delay

The paper is concerned with finite-time dissipativity analysis and design for stochastic Markovian jump systems with generally uncertain transition rates and time-varying delay. By constructing a more appropriate Lyapunov–Krasovskii functional, sufficient conditions for finite-time dissipativity of the underlying system are first proposed. Then, a state feedback controller is designed such that the closed-loop Markovian jump system is finite-time dissipative. These sufficient criteria are derived in the form of linear matrix inequalities (LMIs). Finally, numerical examples are given to demonstrate the validity of the main results.

Simulation Research of Genetic Neural Network based PID Control for Coke Oven Heating

With the background of coke oven heating control system, a genetic algorithm based CMAC (cerebellar model articulation controller) and PID compound control method is presented to control the temperature of coke oven. Genetic algorithm is used to optimize the initial parameter of PID controller, and CMAC neural network is combined with the optimized PID controller. With the simplified model of coke oven, simulations have been done in MATLAB for the new control method. The simulation results prove that it is feasible to apply this method in the process of coke oven temperature control

Stability analysis and control synthesis for positive semi-Markov jump systems with time-varying delay

Abstract This paper deals with stability analysis and control synthesis for positive semi-Markov jump systems (S-MJSs) with time-varying delay, in which the stochastic semi-Markov process related to nonexponential distribution is considered. The main motivation for this paper is that the positive condition sometimes needs to be considered in S-MJSs and the controller design methods in the existing have some conservation. To deal with these problems, the weak infinitesimal operator is firstly derived from the point of view of probability distribution under the constraint of positive condition. Then, some sufficient conditions for stochastic stability of positive S-MJSs are established by implying the linear Lyapunov–Krasovskii functional depending on the bound of time-varying delay. Furthermore, an improved stabilizing controller is designed via decomposing the controller gain matrix such that the resulting closed-loop system is positive and stochastically stable in standard linear programming. The advantages of the new framework lie in the following facts: (1) the weak infinitesimal operator is derived for S-MJSs with time-varying delay under the constraint of positive condition and (2) the less conservative stabilizing controller is designed to achieve the desired control performance. Finally, three examples, one of which is the virus mutation treatment model, are given to demonstrate the validity of the main results.

An improved gradient-based NSGA-II algorithm by a new chaotic map model

Gradient-based non-dominated sorting genetic algorithm II (G-NSGA-II) is successful for solving multi-objective optimization problems. However, the effectiveness of gradient-based hybrid operator is influenced by the distribution of individuals in the population. In order to solve the problem, based on the framework of G-NSGA-II, we propose an improved gradient-based NSGA-II algorithm by introducing a new chaotic map model named IG-NSGA-II. In this algorithm, a new hybrid chaotic map model is first established to initialize population for keeping the diversity of the initial population. Then, the substitution operation of chaotic population candidate is introduced to maintain the diversity and uniformity of the Pareto optimal solution set. Finally, the proposed algorithm is tested on several standard test problems and compared with other algorithms. The experimental results indicate that the proposed algorithm leads to better performance results in terms of the convergence to Pareto front or the diversity of the obtained non-dominated solutions.

Positive observer design for positive Markovian jump systems with partly known transition rates

The paper is concerned with positive observer design for positive Markovian jump systems with partly known transition rates. By applying a linear co-positive type Lyapunov-Krasovskii function, a sufficient condition is proposed to ensure the stochastic stability of the error positive system and the existence of the positive observer, which is computed in linear programming. Finally, an example is given to demonstrate the validity of the main results.