A Natural Search Algorithm Based Optimized Sliding Mode Controller for Inverted Pendulum and Robot Manipulator System

• Published in: 2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE) pp. 1 - 6
• Main Author: Bordoloi, Nitisha
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Bacteria Foraging Optimization Algorithm (BFOA); Degree of freedom(DOF); Lyapunov Stability; Manipulators; Mathematical model; Microorganisms; Modified Particle Swarm Optimization (MPSO); Optimization; PD-SMC; PID-SMC; Sliding Mode Controller (SMC); Switches
• DOI: 10.1109/EPETSG.2018.8658800

The aim of the research work is to design a robust sliding mode controller (SMC) for trajectory tracking of inverted pendulum and robot manipulator system. In this paper, Proportional Derivative (PD) and Proportional Integral Derivative (PID) sliding surface based sliding mode controllers are designed. In order to get the perfect controller and system parameters, two natural search algorithm optimization techniques are used. Modified Particle Swarm Optimization (MPSO) and Bacteria Foraging Optimization Algorithm (BFOA) are two globally accepted optimization methods. The main objective of this paper is to determine out of MPSO based sliding mode controller and BFOA based sliding mode controller techniques, which one can give better result in tracking the trajectory of inverted pendulum and robot manipulator systems. Stability of the system is examined by Lyapunov Stability analysis.