Bacterial Foraging Optimized Hybrid Fuzzy Precompensated PD Control of Two Link Rigid-Flexible Manipulator

Abstract

Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents the social foraging behavior of Escherichia coli bacteria to optimize hybrid Fuzzy Precompensated Proportional — Derivative (PD) controller in trajectory control of two link rigid-flexible manipulator. Numerical simulation using the dynamic model of the two link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems and the use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm based optimization is presented to validate the controller design. The results presented emphasize that a satisfactory tracking precision could be achieved using hybrid Fuzzy Precompensated PD controller with bacterial foraging based optimization.