Title: Adaptive speed controllers based on artificial intelligent techniques for unmanned vehicle electric propulsion system

Authors: Ahmed T. Hafez; Amr A. Sarhan

Addresses: Electrical Engineering Department, Military Technical College, Cairo, 11760, Egypt ' Electrical Engineering Department, Military Technical College, Cairo, 11760, Egypt

Abstract: Brushless direct current motors (BLDC) are used in controlling the unmanned vehicles (UV) rotors dynamics. In this paper, speed control for BLDC motor via a set of adaptive intelligent control techniques is tackled. Adaptive neuro fuzzy inference systems (ANFIS), self-adaptive proportional - integral - derivative (SA-PID) and adaptive fuzzy sliding mode control (AFSMC) are applied to control the speed of the BLDC to maintain the required speed guaranteeing better performance, robustness and safety of the UV during mission. The main contribution in this paper lies in solving the speed control problem for a BLDC on board an UV via artificial intelligent control techniques ensuring the success of the UV in performing the required mission. The simulation results prove the success of designed controller to achieve the desired speed and the enhancement of the performance compared with traditional controllers.

Keywords: brushless DC motor; ANFIS; adaptive neuro fuzzy inference systems; SA-PID; self-adaptive proportional - integral - derivative; AFSMC; adaptive fuzzy sliding mode control.

DOI: 10.1504/IJHVS.2022.127830

International Journal of Heavy Vehicle Systems, 2022 Vol.29 No.4, pp.407 - 423

Received: 09 Mar 2022
Accepted: 09 Mar 2022
Published online: 19 Dec 2022 *

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