Designing a Decentralized LQ Controller for an Industrial Robot Manipulator Based on Optimization Techniques

In this paper, a method based on Broyden-Fletcher-Goldforb-Shanno (BFGS) optimization algorithm to design a decentralized controller for an industrial robot manipulator is presented. This method maintains all the necessary conditions for convergence such as stability, descending direction, and positive definiteness. It offers reasonable convergence rate which shows the effectiveness of the method, and the controller designed with this method shows high performance and decoupling property in time response. It is also compared with two other optimization algorithms, Davidson-Fletcher-Powel (DFP) and steepest descent, in the application to design a controller for an industrial robot manipulator. While the performance of the DFP algorithm is quite similar to the BFGS algorithm, the steepest descent method converges slowly and does not converge to the desired decentralized structure. Simulation results confirm the validity of the analytical work