Hub angle control of double link flexible robotic arm manipulator using PID controller tuned by bacterial foraging optimization algorithm

Abstract

Robotic manipulator with a multi-link structure has a significant role in the majority of today's industries. Controlling the motion of a multi-link manipulator, on the other hand, has proven to be a difficult task, especially when a flexible structure is used. This is due to the complexity of their structures, which causes excessive vibration, resulting in system failure. The goal of this research is to eliminate excessive vibrations produced in order to maintain its efficiency and extend the life of the system. This can be accomplished by developing an intelligent controller for a double-link flexible robotics manipulator (DLFRM) using a proportional integral derivative (PID) controller approach and bacterial foraging optimization algorithm (BFOA) to tune the PID control parameters. BFOA is a new swarm intelligence optimization algorithm based on E. Coli's foraging behavior. The BFOA is utilised to tune the PID controller parameters via simulation to achieve the optimum angle for both links present in the DLFRM using MATLAB/Simulink software. Not only that, the BFOA performance is analyzed and compared with conventional method (Ziegler-Nichols) in optimizing the PID controller used to control the hub angle of the manipulator. It is noticed that the PID controller tuned by BFOA exhibited reduced settling time, overshoot, raising time, and steady state error for both hub angles of the manipulator at link 1 and link 2. Then, the system robustness was tested using different types of sinusoidal disturbance and its durability is demonstrated by the fact that it can effectively reduce vibration when the drawback is moved under different disturbances.