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New Optimal PID Design Gimbal System Using Hybrid PSO-SCA Algorithm With Simscape


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DOI: https://doi.org/10.15866/ireaco.v16i4.23448

Abstract


This work describes the best design of a Proportional Integral Derivative (PID) controller for an Unmanned Aerial Vehicle (UAV) Gimbal system utilising a new optimisation approach derived from the Particle Swarm Optimisation and the Sine Cosine Algorithm (PSO-SCA). The optimal parameters of PID controller (Kp, Ki, and Kd) is determined by the newly designed hybrid algorithm. The effects of numerous iterations for the new hybrid PSO-SCA settings have been investigated using simulations in MATLAB/Simulink environment. The simulations' findings demonstrate that each PID parameter's value varies from simulation to simulation and are influenced by the iteration and the particles. The controller is evaluated to determine how it responds to overshoot, time rise, and settling time. Additionally, bode analysis was utilised to assess the system's stability following optimisation with the hybrid PSO-SCA technique. To determine the efficacy of the random learning mechanism, we evaluated the new hybrid algorithm with the PSO and SCA algorithms. The simulation result showed better performance in overshoot (0.381474 s), settling time (0.153947 s) and rise time (0.100156 s). This is due to the fact that hybrid PSO-SCA increases value search and enables the rapid and accurate discovery of good solutions. In additional, Peak gain was calculated to be 0.882 dB (9.98 rad/s), phase margin to be 83.7° (11 rad/s), and delay margin to be 0.132 s. This result indicates that the system is stable and has an excellent frequency response. The use of hybrid PSO-SCA can also provide better results when searching for comparisons with PSO or SCA alone due to the combination of global and local search functions.
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Keywords


Gimbal; Optimisation; PSO; SCA; Simscape; PID; Hybrid PSO-SCA

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References


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