In this paper, we have investigated the intelligent control of a hydraulically driven parallel robot based on the dynamic model and two control schemes have been developed: 1) Fuzzy-PID self tuning controller composed of the conventional PID control and with Fuzzy logic; 2) Adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller. | Journal of Automation and Control Engineering, Vol. 1, No. 2, June 2013 ANFIS and Fuzzy Tuning of PID Controller for Trajectory Tracking of a Flexible Hydraulically Driven Parallel Robot Machine Mazin I. AL-Saedi, Huapeng Wu, and Heikki Handroos Lab. of Intelligent Machines, Lappeenranta U. of T., Finland {, , }@ Abstract—Parallel robots exhibit good performance in terms of rigidity, accuracy, and dynamic characteristics. However, parallel robots have complex configurations and their dynamic model is highly nonlinear, and conventional PID controllers are not sufficiently robust for their motion control. In this paper, we have investigated the intelligent control of a hydraulically driven parallel robot based on the dynamic model and two control schemes have been developed: 1) Fuzzy-PID self tuning controller composed of the conventional PID control and with Fuzzy logic; 2) Adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller. The two controllers are used to track a straight line. The obtained results confirm the theoretical findings, ., the Fuzzy–PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Amongst these methods, ANFIS has provided the best results for controlling robotic manipulators as compared to the conventional control strategies. Finally, simulated results that demonstrate the robot behaviors are presented. this parallel robot is composed of six closed loop chains driving the end effector collectively in a parallel structure. The 10-DOF prototype is equipped with water hydraulic drives since large quantities of oil are not allowed in ITER. Figure 1. ITER reactor and hybrid robot. Flexible robot manipulators exhibit many advantages over rigid robots: they require lighter material, consume less power. Despite these advantages, modeling and control of flexible manipulators is more difficult .
