Disturbance rejection of three-axis gimbal mechanism using PSO-optimized Fuzzy-PID controller

Document Type : Research Article


1 Assistant Professor, Department of Computer and Electrical Engineering, Arak University of Technology, Arak, Iran

2 Assistant Professor, Department of Mechanical Engineering, Arak University of Technology, Arak, Iran


This paper covers the application of the Fuzzy-PID controller to stabilize the three-axis gimbal payload orientation with respect to the inertial frame in the presence of platform motion. In this way, the effect of external disturbances induced by the operating environment is greatly reduced, thereby increasing the accuracy of ultimate operation. Three independent controllers are employed to maintain the triple angles of the three-axis gimbal payload at a desired orientation. The Fuzzy-PID controller benefits the typical PID control structure in which the control gains are adaptively computed by a fuzzy inference system. The particle swarm optimization algorithm is also used to calculate the optimal values of input-output scale factors. A co-simulation platform is considered by coupling the PSO-optimized Fuzzy-PID controllers modeled in Matlab/Simulink to the mechanical gimbal model designed in Solidworks and exported to Simulink by using Simscape toolbox, aiming at the calculation of control torque needed for stabilization of gimbal payload. The effectiveness of the proposed controller is examined by simulation of the designed system for various commanded angles in the presence of different disturbances, including sinusoidal disturbances with diverse frequencies and random vibrations. According to the adopted collaborative simulations, it is shown that the utilized control system performs very well in the tracking of the desired angles and also the rejection of the applied perturbations.


  • Fuzzy-PID controller to stabilize the three-axis gimbal payload orientation is introduced.
  • Three controllers are employed to maintain the angles of the gimbal payload.
  • PID control parameters are adaptively computed by a fuzzy inference system.
  • A co-simulation platform is created by coupling Solidworks and Matlab/Simulink.
  • PSO algorithm is used to calculate the optimal values of input-output scaling factors.


Main Subjects

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