Abstract
This paper presents a novel trajectory tracking method for robot arms with uncertainties in parameters. The new controller applies the robust output feedback linearization method and is designed so that it is robust to the variation of parameters. Robustness of the algorithm is evaluated when the parameters of the system are floating over 10 percent up and down. An Unscented Kalman Filter (UKF) is applied for state and parameter estimation purposes. As the considered system has 8 unknown parameters while only 5 of them are independent parameters, UKF is applied only to the augmented system with independent parameters. Three types of simulations are applied depending on sensor groups – first with both position and joint sensors, second with only position sensors and third with only joint sensors. The observation of parameters in these groups is discussed. Simulation results show that when both position sensors and joint sensors are used, all the parameters and states are observable and good tracking performances are obtained. When only position sensors are used, the accuracy of the estimated parameters is reduced, and low tracking performances are revealed. Finally, when only joint sensors are applied, the lengths of robot arms are unobservable, but other parameters related to the dynamic system are observable, and poor tracking performances are given.
Highlights
The robot arm is a type of mechanical device which is usually programmable, and it usually has similar functions to a human arm
Huang et al [6] proposed a nonlinear PD controller with gravity compensation that is globally asymptotically stable in position control and a comparison was made between their proposed controller and the conventional PD controller, which showed that a faster response velocity and higher position accuracy were obtained by the former
The nonlinearity of the kinematics and the dynamics of robot arms is inherited in the robot itself, which means that even if a well precisely calibrated modelbased controller may give good tracking performance for a given robot model [8], the difficulty of having an exact model of a robot arm makes the calibrated controllers unable to adapt to any changes and uncertainties in its model and environment
Summary
The robot arm ( called Robot manipulator) is a type of mechanical device which is usually programmable, and it usually has similar functions to a human arm. The nonlinearity of the kinematics and the dynamics of robot arms is inherited in the robot itself, which means that even if a well precisely calibrated modelbased controller may give good tracking performance for a given robot model [8], the difficulty of having an exact model of a robot arm makes the calibrated controllers unable to adapt to any changes and uncertainties in its model and environment Under these circumstances, every time the robot arm picks up some tools of different dimensions, unknown orientations or gripping points, the overall kinematics and dynamics of the robot arm will change, which requires the derivation of a new robot arm model, as well as the designing of a controller.
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