Papers by Keyword: Nonlinear System

Abstract: This paper considers the nolinear system robust estimation problem with measurement time delay. The purpose is to provide algorithm for inertial navigation system nonlinear error model in transmittion delay case. Considering that innovation regroup method can treat the measurement delay problem better with no addition of system state dimension, and decrease the system computation, therefore, that algorithm is combined with extended set-membership estimation and deduce the distrete nonlinear system extended set-membership estimation algorithm with measurement delay, realize nonlinear system varying state estimation and the treatment of measurement delay. At last, apply the algorithm to carrier aircraft in-flight alignment and validate the effecitiveness.

Abstract: Current source converter is a variable structure system due to its switching nature, so that it can easily cause the output current waveform distortion and can not be accurately track the reference current. To solve the above problems, this paper proposes a new variable structure control strategy with fan-shaped sliding domain in the current source converter control system. In the control strategy, the paper deduces the switching surface and switching control law of SMVSC, and calculates the sliding existence domain based on the mathematical model of current source converter. Finally, the simulation results show that the control scheme can make current source converter have better output current waveform, fast tracking the reference current, and strong anti-interference ability. Therefore, the control scheme is correct, effective and feasible.

Abstract: The adaptive fuzzy logic systems are constructed in this paper by utilizing the data information sampled from the inputs and outputs of unknown functions in the nonlinear systems controlled, and then output stable controller is synthesized for a class of uncertain nonlinear systems based on the universal approximation property of adaptive fuzzy logic systems. Finally, the simulation shows the validity of the method in this paper.

Abstract: In order to improve the modeling ability for nonlinear system, an Elman modeling method based on Particle Swarm Optimization (PSO) algorithm is proposed. It uses PSO algorithm to optimize the parameters of Elman network. The simulation result shows that the proposed hybrid method combined Elman with PSO algorithm has a good modeling performance with fast training rate for complex nonlinear system.

Abstract: An internal model and an inverse model of nonlinear system were established based on LS_SVM. On this basis the algorithm of internal model control for nonlinear system based on LS_SVM was put forward. The simulation results show that the internal model and the inverse model of nonlinear have high modeling precision and strong generalization. What’s more the algorithm of internal model control for nonlinear system based on LS_SVM has good control performance, strong anti-jamming ability and robustness.

Abstract: In order to accurately depict the complicated characteristics of nonlinear system by modeling, a Radial Basis Function Network (RBFNN) modeling method based on Independent Component Analysis (ICA) is proposed. First ICA is perform for extracting basic features of the training samples, and then the extracted basic features is used to establish to RBFNN model. The simulation indicates that, the hybrid modeling method proposed is better than that of another 2 methods with simple model structure, and is effective and feasible to establish for the nonlinear modeling system.

Abstract: This article discusses the global stabilization problem of nonlinear systems, based on the Lyapunov method. First discussed the situation of a class of two order nonlinear stabilization, sufficient conditions for global stabilization of the system. Secondly, we study the global stabilization of a class of three order nonlinear, got a new conclusion stabilization of the global system, and design a feedback control law of the system stabilization, at the end of this article of the global nonlinear system of general types of stabilization problem, we obtain sufficient conditions for stabilization of the system, and design the feedback control law is the system stabilization.

Abstract: Servo pneumatics is a mechatronic approach that enables accurate position control of pneumatic drives with high speed. The current study presents a comparison of two servo techniques for position control of pneumatic cylinders. One method uses a proportional valve and another method uses PWM controlled solenoid valves. Mathematical models of the system including the nonlinearities such as mass flow rate, pressure in cylinder chambers and frictional forces are presented in this paper. Using the simulation model created in Matlab-Simulink software, the two systems are analyzed for tracking performances. From the responses it is observed that the proportional valve technique has better tracking characteristics than PWM control technique.

Abstract: In this paper, a new DNA based genetic algorithm is proposed to optimize a fuzzy neural network model for a pH neutralization process. In the proposed algorithm, each individual presents a fuzzy neural network encoded by nucleotide base sequence, and modified DNA based crossover operation and three types of mutation operators are designed to improve the searching ability of the algorithm. The study on the performance for two functions shows that the proposed algorithm outperforms GA. Finally, to verify the effectiveness of the established model, it is compared with two models optimized with other methods. Comparison results show that the model optimized by DNA based GA is more accurate.

Abstract: Servo hydraulic system is important one of driving patterns of quadruped robot. While servo hydraulic system has characteristics of parameters time-varying and strong nonlinearity, so traditional PID control pattern cannot meet all the control demands well. To solve these problems, a set of control hardware is designed for a quadruped robot and a new control algorithm which can adjust PID parameters in real-time condition based on fuzzy control theory is proposed. By deducing transfer function, establishing system model and using MATLAB simulation tools to simulate the two algorithms, we compared the two algorithms and the simulation result turns out that compared with traditional PID control algorithm, the fuzzy PID control algorithm has features such as low overshoot, high stability precision, strong robustness. At the same time, the result turns out that the fuzzy PID control algorithm is much fitter for the joint control of quadruped robot.