Fuzzy logic control of a two degree of freedom parallel robot

Parallel robots differ greatly from their serial counterparts in terms of performance and mechanical ability. Serial robots are open chained mechanisms since each link is connected to an adjacent one and each joint is actuated, while parallel robots implement a closed chained structure. This type of structure consists of having the endpoint of each kinematic chain connected to one another, hence called the common point. There can be a multitude of kinematic chains, but each chain utilizes only one actuator located near the base of the system to perform the desired operation. This brings up the dilemma between parallel and serial robots. Serial robots allow for a greater control precision and a simpler dynamic model, yet they are generally more expensive and their load capacity is limited due to their large mass. Parallel robots have a higher load capacity due to their smaller mass, much faster accelerations at the end effector and boast a high mechanical stiffness to weight ratio. Their drawbacks entail a complex dynamic model and they generally have many singular regions that must be avoided in order to achieve stability. There has been substantial research aimed at improving the performance of parallel robots by implementing PID and adaptive controllers’ and so on, but due to the variations in the dynamic models of each system, it is nearly impossible to conclusively determine the most appropriate controller to design. Therefore, this thesis compares the simulation and experimental results of four non-fuzzy logic controllers, namely the non-adaptive and adaptive PD and backstepping controllers ii along with four fuzzy logic controllers, namely the fuzzy PD, indirect adaptive fuzzy, direct adaptive fuzzy and fuzzy adaptive backstepping controllers on a planar two degrees of freedom parallel robot in order to determine which controller would yield the best control performance. By comparing the simulation results for the joint angles error and the end effector trajectory error plots for the non-fuzzy and fuzzy logic controllers, the adaptive backstepping and the fuzzy adaptive backstepping controllers held the potential to be the most likely candidate controllers to implement on the physical structure of the two degrees of freedom parallel robot. After the eight controllers elaborated in this thesis were utilized on the parallel robot structure, the controller that outputted the most impressive experimental results were found in the fuzzy adaptive backstepping controller. The joint angles error and end effector trajectory deviation yielded particularly low results, but it is the tracking performance which differentiates this controller from the rest. It has the smoothest tracking performance when compared between the non-fuzzy and fuzzy logic controllers discussed in this thesis without conceding a large displacement error and it tracks an acutely symmetrical circle. Another significant advantage of the fuzzy adaptive backstepping controller over any other control techniques employed in this thesis is the low computation time required to generate the control signals. This is very important since a lower computation time allows the control performance to increase dramatically. Therefore, the recommended control technique to be employed on the planar two degrees of freedom parallel robot is the fuzzy adaptive backstepping controller.