Sliding mode control design for autonomous surface vehicle motion under the influence of environmental factor

Abstract

Autonomous Surface Vehicle (ASV) is a vehicle that is operated in the water surface without any person in the vehicle. Since there is no person in the ASV, a motion controller is essentially needed. The control system is used to make sure that the water vehicle is moving at the desired speed. In this paper, we use a Touristant ASV with the following specifications: the length is 4 meters, the diameter is 1.625 meters, and the height is 1.027 meters. The main contribution of this paper is applying the Sliding Mode Control system to the Touristant ASV model under the influence of environmental factors. The environmental factors considered in this work are wind speed and wave height. The Touristant ASV model is nonlinear and uses three degree of freedom (DOF), namely surge, sway and yaw. The simulation results show that the performance of the closed-loop system by using the SMC method depends on the environmental factors. If environmental factors are higher, then the resulting error is also higher. The average error difference between those resulted from the simulation without environmental factors and those with the influence of environmental factors is 0.05% for surge, sway and yaw motions.

Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

“…δ is consider as unknown nonlinear function or uncertainty of dynamic, (Z) is switching [ ] function. The key objective of designing SMC is to train the appropriate state desire position according to the actual joint variables, the trucking error vector will be defined is being as [3], [5].…”

“…The second part is equivalent controller ( ) which is the effect of nonlinear terms that induced reliability and used to fine-tune the sliding surface slopes [4]. In addition, SMC has two major disadvantages, namely are chattering phenomenon in control response, and nonlinear equivalent analogous functional formulation in indeterminate and uncertain dynamic parameters [5]. The rising in switching frequency of the control in discontinuous issue happened due to a phenomenon called (chattering), which can be considered as an unwanted feature that appear in the control behavior of SMC.…”

Optimization of the Performances of a Two-Joint Robotic Arm using Sliding Mode Control

“…The design of a sliding mode controller starts with the choice of a functions Si defining in the phase space, the sliding surfaces 𝑆𝑆 𝑖𝑖 = 0 that ensure the convergence of the states 𝑖𝑖 of the system to the desired values. Starting from [8][9][10], we consider the expression of the functions 𝑆𝑆 𝑖𝑖 as follows:…”

A neural network combined with sliding mode controller for the two-wheel self-balancing robot

“…Commonly, the sliding mode control method [22]- [24] includes defining the sliding surface as the system state functions and proving the trajectories of the closed-loop system reach this surface in a finite time based on stability theory. To solve the disadvantages of the common sliding mode control, we add a neural network.…”