Zhao Zhi-cheng

A new antiwindup speed controller for induction motor drive system

The windup phenomenon appears and results in performance degradation when the proportional-integral (PI) speed controller output is saturated for the motor drive system. A new antiwindup speed controller is proposed to improve the speed control performance of the motor drive system. Based on the internal model control (IMC) method, the proposed controller is designed, the parameters of which are expressed directly in the system parameters and the desired closed loop bandwidth. This simplifies the speed controller design procedure, and trial-and-error can be avoided. Some simulated results are provided to demonstrate the effectiveness of the proposed controller.

A control scheme based on discrete time-varying sliding surface for position control systems

A sliding mode control scheme for second-order discrete system is proposed using the time-varying sliding surface instead of the fixed sliding surface. The time-varying sliding surface is designed first to pass arbitrary initial states, and subsequently move towards a final sliding surface by rotating. The sliding surface rotating procedures are presented in detail. The proposed control scheme is applied to a position control system. Simulation results show that the scheme provides high performance dynamic characteristics, and is insensitive to uncertainties including parameter variations and external disturbance in the whole control process.

Internal model control based on self-constructing wavelet neural network

In this paper, a novel internal model control (IMC) algorithm based on self-constructing wavelet neural network (WNN) is proposed for the nonlinear process. The self-constructing learning algorithm is composed of the structure learning and the parameters learning. In the structure learning phase, the similarity measurement method is adopted to determine whether or not to add a new wavelet base to satisfy the identification requirement. In addition, the impact of wavelet base on the output of the network is used as the basis for deciding whether to cut the wavelet base. The gradient descent method which can adjust the learning rate automatically is applied in the parameters learning. Combining the self-constructing WNN with IMC, the networks used to identify the process model and the controller model can dynamically determine the number of nodes. So, the networks convergence speed could be increased, and the dynamic performance and robustness of the system could be improved.

A method of designing internal model PID controller for multivariable time-delay process

Aiming at the two-input two-output processes with time delays which are often encountered in the industry areas, a new method of decoupling internal model control (IMC) is proposed in this paper. With treating the whole feedback block as a generalized process, the system outputs decoupling can be realized completely. At the same time, through the selection of parameters of the additional filter in IMC-PID controller, the errors, which caused by using Mclaurin series approximating, can be weakened. So it makes the controller have retained the advantages of IMC controller more. The simulation results show that this method has a greater advantage.

Fuzzy logic control based on neural network nonlinear prediction

This paper presents a new fuzzy logic control method for time invariant nonlinear system based on neural network nonlinear prediction. It includes two parts: the neural network predictive model, which predicts the nonlinear system output; the weighted fuzzy logic controllers, which do the fuzzy operation according to prediction error between set value and predictive value, and then give out the control output. The simulation result shows that this method has excellent tracking performance, anti-interference capability as well as good dynamic and static performance indexes.