I.J. Intelligent Systems and Applications, 2014, 08, 87-96 Published Online July 2014 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijisa.2014.08.10 Copyright © 2014 MECS I.J. Intelligent Systems and Applications, 2014, 08, 87-96 Design Intelligent System Compensator to Computed Torque Control of Spherical Motor Maryam Rahmani, Farzin Piltan, Farzin Matin, Hamid Cheraghi, Nasim Sobhani Institute of Advance Science and Technology, Intelligent control and Robotics Lab. IRAN SSP, Shiraz/Iran, http://WWW.IRANSSP.COM, Email: Piltan_f@iranssp.com Abstract — Spherical three Degree-of- Freedom (DOF) is controlled by model-base fuzzy computed torque controller. The spherical motor has three revolute joints allowing the corresponding parts to move horizontally and vertically. When developing a controller using conventional control methodology (e.g., feedback linearization methodology), a design scheme has to be produced, usually based on a system‟s dynamic model. The work outline in this research utilizes soft computing applied to new conventional controller to address these methodology issues. Computed torque controller (CTC) is influential nonlinear controllers to certain systems which this method is based on compute the required arm torque using nonlinear feedback control law. When all dynamic and physical parameters are known, CTC works superbly; practically a large amount of systems have uncertainties and fuzzy feedback Inference Engine (FIS) is used to reduce this kind of limitation. Fuzzy logic provides functional capability without the use of a system dynamic model and has the characteristics suitable for capturing the approximate, varying values found in a MATLAB based area. Based on this research model- base fuzzy computed torque controller applied to spherical motor is presented to have a stable and robust nonlinear controller and have a good result compared with conventional and pure fuzzy logic controllers. Index Terms— Fuzzy Inference System, Fuzzy Logic Controller, Computed Torque Controller, Spherical Motor, Fuzzy Model-Base Computed Torque Controller I. INTRODUCTION Multi-degree-of-freedom (DOF) actuators are finding wide use in a number of Industries. Currently, a significant number of the existing robotic actuators that can realize multi-DOF motion are constructed using gear and linkages to connect several single-DOF motors in series and/or parallel. Not only do such actuators tend to be large in size and mass, but they also have a decreased positioning accuracy due to mechanical deformation, friction and backlash of the gears and linkages. A number of these systems also exhibit singularities in their workspaces, which makes it virtually impossible to obtain uniform, high-speed, and high-precision motion. For high precession trajectory planning and control, it is necessary to replace the actuator system made up of several single- DOF motors connected in series and/or parallel with a single multi-DOF actuator. The need for such systems has motivated years of research in the development of unusual, yet high performance actuators that have the potential to realize multi-DOF motion in a single joint. One such actuator is the spherical motor. Compared to conventional robotic manipulators that offer the same motion capabilities, the spherical motor possesses several advantages. Not only can the motor combine 3-DOF motion in a single joint, it has a large range of motion with no singularities in its workspace. The spherical motor is much simpler and more compact in design than most multiple single-axis robotic manipulators. The motor is also relatively easy to manufacture. The spherical motor have potential contributions to a wide range of applications such as coordinate measuring, object tracking, material handling, automated assembling, welding, and laser cutting. All these applications require high precision motion and fast dynamic response, which the spherical motor is capable of delivering. Previous research efforts on the spherical motor have demonstrated most of these features. These, however, come with a number of challenges. The spherical motor exhibits coupled, nonlinear and very complex dynamics. The design and implementation of feedback controllers for the motor are complicated by these dynamics. The controller design is further complicated by the orientation-varying torque generated by the spherical motor. Some of these challenges have been the focus of previous and ongoing research [1-11]. In modern usage, the word of control has many meanings, this word is usually taken to mean regulate, direct or command. The word feedback plays a vital role in the advance engineering and science. The conceptual frame work in Feed-back theory has developed only since world war ІІ. In the twentieth century, there was a rapid growth in the application of feedback controllers in process industries. According to Ogata, to do the first significant work in three-term or PID controllers which Nicholas Minorsky worked on it by automatic controllers in 1922. In 1934, Stefen Black was invention of the feedback amplifiers to develop the negative feedback amplifier[12-28]. Negative feedback invited communications engineer Harold Black in 1928 and it occurs when the output is subtracted from the input. Automatic control has played an important role in advance science and engineering and its extreme importance in many industrial applications, i.e., aerospace, mechanical engineering and joint control. The first significant work in automatic control was James Watt‟s centrifugal governor for the speed control in motor engine in eighteenth century[29-40]. There are several methods for controlling a spherical motor, which all of them follow two common goals, namely, hardware/software implementation and acceptable