Hybrid fuzzy logic control with genetic optimisation for a single-link flexible manipulator

To reduce the end-point vibration of a single-link flexible manipulator without sacrificing its speed of response is a very challenging problem since the faster the motion, the larger the level of vibration. A conventional controller can hardly meet these two conflicting objectives simultaneously. This paper presents a genetic algorithm (GA)-based hybrid fuzzy logic control strategy to achieve that goal. A proportional-derivative (PD) type fuzzy logic controller utilising hub-angle error and hub-velocity feedback is designed for input tracking of the system. GA is used to extract and optimise the rule base of the fuzzy logic controller. The GA fitness function is formed by taking the weighted sum of multiple objectives to trade off between system overshoot and rise time. Moreover, scaling factors of the fuzzy controller are tuned with GA to improve its performance. A GA-based multi-modal command shaper is then designed and augmented with the fuzzy logic controller to reduce the end-point vibration of the system. The performance of the hybrid control scheme is assessed in terms of its input-tracking capability and vibration suppression at the end point. A significant amount of vibration reduction has been achieved at the end point, especially at the first three resonance modes of the rig structure, with satisfactory level of overshoot, rise time, settling time, and steady-state error.