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.
Jumping Spider Optimization Algorithm (JSOA) Meta-heuristics Optimization PID Intelligent control Dynamic system Nonlinear system Linearization Pitch & Yaw Twin-Rotor MIMO System (TRMS)
Primary Language | English |
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Subjects | Control Engineering, Mechatronics and Robotics (Other) |
Journal Section | Research Articles |
Authors | |
Publication Date | July 31, 2024 |
Submission Date | November 27, 2023 |
Acceptance Date | March 7, 2024 |
Published in Issue | Year 2024 Volume: 6 Issue: 3 |
Chaos Theory and Applications in Applied Sciences and Engineering: An interdisciplinary journal of nonlinear science
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