Conventional Sliding Mode Control Method Research Articles

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

Robust fuzzy neural network sliding mode control scheme for IPMSM drives

This article proposes a robust fuzzy neural network sliding mode control (FNNSMC) law for interior permanent magnet synchronous motor (IPMSM) drives. The proposed control strategy not only guarantees accurate and fast command speed tracking but also it ensures the robustness to system uncertainties and sudden speed and load changes. The proposed speed controller encompasses three control terms: a decoupling control term which compensates for nonlinear coupling factors using nominal parameters, a fuzzy neural network (FNN) control term which approximates the ideal control components and a sliding mode control (SMC) term which is proposed to compensate for the errors of that approximation. Next, an online FNN training methodology, which is developed using the Lyapunov stability theorem and the gradient descent method, is proposed to enhance the learning capability of the FNN. Moreover, the maximum torque per ampere (MTPA) control is incorporated to maximise the torque generation in the constant torque region and increase the efficiency of the IPMSM drives. To verify the effectiveness of the proposed robust FNNSMC, simulations and experiments are performed by using MATLAB/Simulink platform and a TI TMS320F28335 DSP on a prototype IPMSM drive setup, respectively. Finally, the simulated and experimental results indicate that the proposed design scheme can achieve much better control performances (e.g. more rapid transient response and smaller steady-state error) when compared to the conventional SMC method, especially in the case that there exist system uncertainties.

Time-Varying Sliding Mode Control for Discrete-Time Nonlinear Uncertain Coupled Systems via Sliding Mode Prediction

In this paper, a novel time-varying sliding mode control (SMC) algorithm based on sliding mode prediction for a class of discrete-time nonlinear uncertain coupled systems is presented. After giving a kind of time-varying sliding mode function, a sliding mode prediction model is used to predict the future information of sliding mode. By employing feedback correction and receding horizon optimization approaches which are extensively applied in predictive control strategy, the desired discrete-time variable structure control law is obtained. Under the influence of uncertainties whose boundaries are unknown, the closed-loop systems are proofed to be robustly stable. Numerical simulation results illustrate that compared with conventional SMC method, under the algorithm proposed in this paper, chattering is eliminated, the control signals have smaller peak values, and the closed-loop system possesses stronger robustness.

Simplex sliding mode control for nonlinear uncertain systems via chaos optimization

Abstract As an emerging effective approach to nonlinear robust control, simplex sliding mode control demonstrates some attractive features not possessed by the conventional sliding mode control method, from both theoretical and practical points of view. However, no systematic approach is currently available for computing the simplex control vectors in nonlinear sliding mode control. In this paper, chaos-based optimization is exploited so as to develop a systematic approach to seeking the simplex control vectors; particularly, the flexibility of simplex control is enhanced by making the simplex control vectors dependent on the Euclidean norm of the sliding vector rather than being constant, which result in both reduction of the chattering and speedup of the convergence. Computer simulation on a nonlinear uncertain system is given to illustrate the effectiveness of the proposed control method.

新しいスライディングモードを用いた宇宙用冗長マニピュレータの制御

This paper proposes two items: One is a sliding mode based on a new concept concerned with redundancy. The other is a control scheme based on that concept for a redundant manipulator in space to grasp a floating object. The previously published methods required many calculations becasuse of using pseudo inverse. To deal with this problem, we introduce a new concept of redundancy based on redundancy of sliding mode itself, and introduce a new sliding mode. This concept is combined with a conventional sliding mode control method. By using this hybrid control scheme the number of calculations is reduced to about 1/5 or 1/6 for tracking the same trajectory of an end-effector utilizing the redundancy as that of the conventional methods. And the proposed control method eliminates the necessity of the estimation of uncertain motion parameters of translational and rotational momenta by adaptive gains. Finally the effectiveness of the proposed method is verified by computer simulations for the trajectry control where the satellite angular velocity is surpressed by taking advantage of redundancy based on a new concept.