Bio-Inspired Jumping Spider Optimization for Controller Tuning/Parameter Estimation of an Uncertain Aerodynamic MIMO System

Authors : David Ezekiel, Ravi Samikannu, Oduetse Matsebe

Pages : 205-217

Doi:10.51537/chaos.1396823

View : 26 | Download : 33

Publication Date : 2024-07-31

Article Type : Research Paper

Abstract :The practical near impossibility of empirical attempts in estimating optimal controller gains makes the use of metaheuristics strategies inevitable to automatically obtain these gains by an iterative, heuristic simulation procedure. The convergence of the gains values to the local or global solutions occur with ease. In designing controllers for the Twin-Rotor MIMO System (TRMS), Jumping Spider Optimization Algorithm (JSOA), a novel neoteric population-based bio-inspired metaheuristic approach is used to obtain optimum values for the Proportional, Integral and Derivative (PID) controllers. With the k,p,i controller gains as the decision variables, the JSOA solution to a nonlinear multi-objective optimization problem subject to some intrinsic constraints spawned optimal values for the controllers’ variables. Counter to other algorithms (deterministic and stochastic) that get caught in local minima, JSOA evolved a solution after searchingly rummaging the entire solution search space in a vectorized fashion for an optimal value. Compared with several other versatile controllers (using GA, PSO, Pattern Search and Simulated Annealing), statistical results obtained showed JSOA technique provided a unique solution and found the gains of the PID controllers, marginally in relation to the others like optimization methods.
Keywords : Jumping Spider Optimization Algorithm JSOA, Meta heuristics, Optimization, PID, Intelligent control, Dynamic system, Nonlinear system, Linearization, Pitch Yaw, Twin Rotor MIMO System TRMS