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The very precise control of robot manipulator to track the desired trajectory is a very tedious job and almost unachievable to certain limit with the help of adaptive controllers. This task is achievable to certain limit with the help of adaptive controllers but these controllers also have their own limitation of assuming that the system parameters being controlled change relatively very slow. With reference to the tasks assigned to an industrial robot, one important issue is to determine the motion of the joints and the end effectors of the robot. Therefore, the purpose of the robot arm control, as Fu et al (1987) wrote in one classical works on robotics, is to maintain the dynamic response of the manipulator in accordance with some prespecified performance criterion. Among the early robots of the first generation, non-servo control techniques, such as bang-bang control and sequence control were used. These robots move from one position to another under the control or limit switches, relays, or mechanical stops. During the 1970s, a great deal of work was focused on including such internal state sensors as encoders, potentiometers, tachogenerators, etc., into the robot controller to facilitate manipulative operation ((Inoue, H.,(1974) and Wills, et al (1975)) . Since then, feedback control techniques have been applied for servoing robot manipulators. Up till now, the majority of practical approaches to the industrial robot arm controller design use traditional techniques, such as Proportional and Derivative (PD) or Proportional-Integral-Derivative (PID) controllers, by treating each joint of the manipulator as a simple linear servomechanism. In designing these kinds of controllers, the non-linear, coupled and time-varying dynamics of the mechanical part of the robot manipulator system are completely ignored, or dealt with as disturbances. These methods generally give satisfactory performance when the robot operates at a low speed. However, when the links are moving simultaneously and at a high speed, the non-linear coupling effects and the interaction forces between the manipulator links may degrade the performance of the overall system and increase the tracking errors. The disturbances and uncertainties in a task cycle may also reduce the tracking quality of robot manipulators. Thus, these methods are only suitable for relatively slow manipulator motion and for 18

Advanced Dynamic Path Control of the Three Links SCARA Using Adaptive Neuro Fuzzy Inference System