Hub angle control of flexible manipulator based on bacterial foraging optimization

Abstract

Flexible manipulator offers industry with less material requirement, lighter in weight thus transportable, consuming less power, require smaller actuators, less control complexity while being able to operate in higher payload to weight. But, due to high flexibility of the flexible manipulator, excessive vibration can be found if the system is implemented. This study aims to simulate an accurate model system using system identification (SI) technique via Bacterial Foraging Optimization (BFO) for control of the hub angle of the flexible manipulator system in simulation environment. It is vital to model the system that represents actual characteristics of the flexible manipulator before precisely control the hub angle of the flexible manipulator’s movement. The experimental data obtained from the flexible manipulator system’s hub are utilised to construct a model of the system using an auto-regressive with exogenous (ARX) structure. Bacterial Foraging Optimization (BFO) is used to develop the modelling by SI technique to obtain the mathematical models. The generated model’s performance is assessed using three methods: minimum mean square error (MSE), correlation tests, and stability test in pole-zero diagram. The model of hub angle constructed using BFO has a minimum mean square error of 1.9694,10-5, a high degree of stability, and strong correlation tests. The model of hub angle constructed using BFO has a minimum mean square error of 1.9694,10-5, a high degree of stability, and strong correlation results. Following that, a PID controller is designed and heuristically tuned to provide accurate hub angle positioning with a short settling time using the BFO model. It is also worth noting that BFO’s model successfully regulated the hub angle’s positioning with a 0.8% overshoot and a 0.5242 s settling time in the presence of single disturbances.