Design Stable Controller for PUMA 560 Robot with PID and Sliding Mode Controller Based on PSO Algorithm

Abstract

The most significant challenge facing the researcher in the field of robotics is to control the robot manipulator with appropriate overall performance. This paper focuses mainly on the novel Intelligent Particle Swarm Optimization (PSO) algorithm that was used for optimizing and tuning the gain of conventional Proportional Integral Derivative (PID), and improve the parameters of dynamic design in Sliding Mode Control (SMC), which is considered a strong nonlinear controller for controlling highly nonlinear systems, particularly for multi-degree serial link robot manipulator. Additional modified Integral Sliding Mode Controller (ISMC) was implemented to the design of dynamic system with high control theory of sliding mode controller. Intelligent Particle Swarm Optimization (PSO) algorithm was introduced for developing the nonlinear controller. The algorithm demonstrates superior performance in determining the appropriate gains and parameters value in harmony with robot scheme dynamic layout in order to achieve suitable and stable nonlinear controller, besides reduce the chattering phenomenon. PUMA robot manipulator that was used as study case in this work, shows perfect result in step response, with acceptable steady state, and overshoot, besides, eliminating the disadvantage of chattering in conventional SMC. Matlab / Simulink presents to increase the speed of matrix calculation in forward, inverse kinematics and dynamic model of manipulator. Comparison was made between the proposed method with existing methods. Result shows that integral sliding mode with PSO (ISMC/PSO) gave best result for stable step response, minimum mean square error with best objective function, and stable torque.

Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

“…SMC is applied to impose the system's state path to pass through the sliding surface, then imposes the state's system path to ''slide" along the switching surface till it stays on the origin [4]. In order to define the equation that control the total design of SMC, the nonlinear input single for dynamic system define is being as: where (υ) is consider as the vector of the control input , is the ℎ derivative of the state vector .…”

“…Therefore, best strategies to achieve this is to find the input control υ outside the sliding surface and remains on it. To keep the ( ,̇ ) close to zero, the law control is design to achieve the sliding condition of Lyapunov function [4], [6], is being as:…”

“…But it is caused to system instability and the occurrence of chatter. The second part is equivalent controller ( ) which is the effect of nonlinear terms that induced reliability and used to fine-tune the sliding surface slopes [4]. In addition, SMC has two major disadvantages, namely are chattering phenomenon in control response, and nonlinear equivalent analogous functional formulation in indeterminate and uncertain dynamic parameters [5].…”

“…Akkar and Haddad [4] introduced a strategy for tuning three types of dynamic control techniques that were developed for the PUMA 560 robot manipulator, which are proportional integral derived (PID), sliding mode control (SMC), and the modified type of integral sliding mode control (ISMC). Intelligent particle swarm optimization (PSO) has been suggested to achieve the best parameters in order to maximize the parameters in the proposed strategies.…”

“…In order to enhance the performance designed of the proposed controller scheme which is based on SMC, besides improve stability and minimize total error, integral sliding mode controller (ISMC) was designed, our goal is to keep the sliding surface close to zero all the time [4], [6], [10]. The formula that defines ISMC surface is being as:…”