Nonlinear sliding mode control of a two-wheeled mobile robot system

Abstract

This paper presents a trajectory tracking control scheme for a two-wheeled mobile robot using sliding mode techniques. The stability of the designed sliding mode dynamics is analysed and reachability of the sliding mode is guaranteed in a given region with the proposed controller. A robot system including a micro-controller, the Arduino Due based on the ARM Cortex-M3, is used to implement the proposed control algorithm. Two DC motors controlled by PWM signals are used as actuators to implement the proposed feedback control. Simulation results are presented and compared with the results of practical experiments.

Sliding mode control of a differential-drive mobile robot following a path

“…The path following problem consists in tracking a desired path defined by the plane coordinates, ρ(x, y) [6]. Several control strategies have been used to tackle the path following problem, such as backsteeping [8], feedback linearisation [6], fuzzy logic controllers [1], Lyapunov methods [9], adaptive controllers [10], and sliding mode control [12] [13] [11], among others. The main drawback of tracking a trajectory defined by the position in the plane x, y is that it requires knowledge of the global position.…”

Stabilisation of time delay systems with nonlinear disturbances using sliding mode control

“…In addition, the design parameters can be obtained via LMI techniques systematically. It should be noted that one method which has proved very effective in dealing with uncertainties in the system is the sliding mode control due to its strong robustness properties against parametric uncertainties and external disturbances in the input channel, as well as its attractive features such as fast and good transient response (Zhen et al, 2014;Edwards and Spurgeon, 1998;Mu et al, 2017).…”

Attitude tracking control of rigid spacecraft with disturbance compensation

“…But it has a conservative assumption that the total disturbance should be slow varying and bounded, which means the first-order derivative of disturbance should be zero(i.e., 0 d = ). Owing to the features such as robustness to uncertainties and faster convergence, sliding mode control has been widely used in various fields, such as Zhou et al (2016), Mu et al (2017), Chen et al (2016), and Na et al (2014). In Tiwari et al (2016), the attitude tracking problem is solved by using higher order sliding mode.…”