Lagrangian Modeling and Optimal MIMO PID Control of a Manipulator Using Tabu Search Algorithm

Abstract

Robot manipulators, given their promising features and capabilities, have found a variety of applications in many fields including construction, nuclear, car, manufacturing and surgical industries, among others, which has turned them to a large and diffuse industry. In construction, use of robots has automated many tasks and risky jobs, including multitask road construction and maintenance processes based on ergonomic and economic analyses, surface finishing, concreting, excavating and backfilling, to name but a few. Hence, manipulators have progressively replaced human labor to meet strict health regulations, productivity gains, and control goals. Movement of an effector tool into a proper location and orientation required for a work object is the main role of a manipulator. In this research dynamic modeling and control of a 2-DOF planar robotic manipulator is presented using a PID controller to obtain optimal position of final operator of the manipulator. Considering nonlinearity of the system under consideration, to optimize final position of the manipulator, parameters of PID controller were tuned using Tabu Search (TS) algorithm as one of meta-heuristic optimization techniques. Numerical results obtained from simulations in this study demonstrated robustness and efficiency of the selected approach for optimizing the final position of the manipulator, minimizing oscillations and fast convergence of the error function to zero, compared to that of uncontrolled state as well as controlled system by PID controller with empirically adjusted factors. Efficiency of the proposed method was verified for different angular positions of joints in the manipulator. Keywords:Lagrangian Modeling; Manipulator; MIMO PID Controller; Evolutionary Algorithms