Intelligent total sliding‐mode control with dead‐zone parameter modification for a DC motor driver

Abstract

A functional-linked cerebellar model neural network (FCMNN) equipped with sine-cosine perturbed Gaussian basis functions to online approximate an unknown nonlinear term in the system dynamics of a DC motor driver is proposed in this study. The sine-cosine perturbation in the Gaussian basis functions possessing the ability of handling rule uncertainties is quite useful for real-time applications. Then, an intelligent total sliding-mode control (ITSMC) system that is composed of a computation controller and a robust compensator is proposed. The computation controller including an FCMNN approximator is the main controller and the robust compensator is designed to eliminate the effect of the approximation error introduced by the FCMNN approximator upon system stability. The online parameter adaptation laws are derived based on a Lyapunov function so that the L 2 tracking performance can be guaranteed. To reduce the parameter overtraining problem, a dead-zone parameter modification scheme is adopted so that the parameter tuning process will be stopped when a tracking index is smaller than a pre-specified threshold. Finally, the proposed ITSMC system is implemented on a 32-bit microcontroller for possible low-cost and high-performance industrial applications. The experimental results show that the ITSMC system can achieve favourable tracking performance and is robust against parameter variations in the plant.

An integral sliding mode controller based disturbances rejection compound scheme for inertially stabilized platform in aerial remote sensing

“…the ISP keeps stable at its ideal position. Thus, equation (12) can be expressed as the following state variable form…”

“…In a SM system satisfying the sliding condition, once the system states reach the sliding manifold, the system behavior is invariant to the parameter uncertainties and external disturbances. 12 Therefore, the sliding mode control (SMC) has been widely employed in the industrial applications due to its powerful ability to reject the disturbances and plant uncertainties. 13,14 Thus, the SMC methodology has been used in the stabilization, tracking, observer design, frequency domain analysis, and other control problems.…”

Comparative Study Between Classical Controllers and Inverse Dead Zone Control for Position Control of a Permanent Magnet DC Motor with Dead zone

“…In fact, it is considered one of the main nonlinearities in industrial processes, [12]. Because the dead zone can affect the performance and stability of position control systems, [13]- [15], several controllers have been proposed to try to reduce this problem, among the most used are those based on adaptative control, [16]- [21], sliding mode control [22], [23], and intelligent controllers, [24]- [27]. Although these strategies report excellent results, their conclusions are based on digital simulations and not by real-time implementations.…”

Microcontroller-Based B-Spline Neural Position Control for Voice Coil Motors

“…A trade-off problem between chattering phenomenon and control accuracy arises in [16]- [18]. A robust compensator [19], [20] is proposed by using the finite 2 L -gain control approach. However, the control effort may lead to a large control signal.…”