Design of Adaptive Sliding Mode Fuzzy Control for Robot Manipulator Based on Extended Kalman Filter

In this work, a new adaptive motion control scheme for robust performance control of robot manipulators is presented. The proposed scheme is designed by combining the fuzzy logic control with the sliding mode control based on extended Kalman filter. Fuzzy logic controllers have been used successfully in many applications and were shown to be superior to the classical controllers for some nonlinear systems. Sliding mode control is a powerful approach for controlling nonlinear and uncertain systems. It is a robust control method and can be applied in the presence of model uncertainties and parameter disturbances, provided that the bounds of these uncertainties and disturbances are known. We have designed a new adaptive Sliding Mode Fuzzy Control (SMFC) method that requires only position measurements. These measurements and the input torques are used in an extended Kalman filter (EKF) to estimate the inertial parameters of the full nonlinear robot model as well as the joint positions and velocities. These estimates are used by the SMFC to generate the input torques. The combination of the EKF and the SMFC is shown to result in a stable adaptive control scheme called trajectory-tracking adaptive robot with extended Kalman (TAREK) method. The theory behind TAREK method provides clear guidelines on the selection of the design parameters for the controller. The proposed controller is applied to a two-link robot manipulator. Computer simulations show the robust performance of the proposed scheme

Control strategies for robotic manipulators

This survey is aimed at presenting the major robust control strategies for rigid robot manipulators. The techniques discussed are feedback linearization/Computed torque control, Variable structure compensator, Passivity based approach and Disturbance observer based control. The first one is based on complete dynamic model of a robot. It results in simple linear control which offers guaranteed stability. Variable structure compensator uses a switching/relay action to overcome dynamic uncertainties and disturbances. Passivity based controller make use of passive structure of a robot. If passivity of a feedback system is proved, nonlinearities and uncertainties will not affect the stability. Disturbance observer based controllers estimate disturbances, which can be cancelled out to achieve a nominal model, for which a simple controller can then be designed. This paper, after explaining each control strategy in detail, finally compares these strategies for their pros and cons. Possible solutions to cope with the drawbacks have also been presented in tabular form. © 2012 IEEE

Sliding mode control of robotics systems actuated by pneumatic muscles.

This dissertation is concerned with investigating robust approaches for the control of pneumatic muscle systems. Pneumatic muscle is a novel type of actuator. Besides having a high ratio of power to weight and flexible control of movement, it also exhibits many analogical behaviors to natural skeletal muscle, which makes them the ideal candidate for applications of anthropomorphic robotic systems. In this dissertation, a new phenomenological model of pneumatic muscle developed in the Human Sensory Feedback Laboratory at Wright Patterson Air Force Base is investigated. The closed loop stability of a one-link planar arm actuated by two pneumatic muscles using linear state feedback is proved. Robotic systems actuated by pneumatic muscles are time-varying and nonlinear due to load variations and uncertainties of system parameters caused by the effects of heat. Sliding mode control has the advantage that it can provide robust control performance in the presence of model uncertainties. Therefore, it is mainly utilized and further complemented with other control methods in this dissertation to design the appropriate controller to perform the tasks commanded by system operation. First, a sliding mode controller is successfully proposed to track the elbow angle with bounded error in a one-Joint limb system with pneumatic muscles in bicep/tricep configuration. Secondly, fuzzy control, which aims to dynamically adjust the sliding surface, is used along with sliding mode control. The so-called fuzzy sliding mode control method is applied to control the motion of the end-effector in a two-Joint planar arm actuated by four groups of pneumatic muscles. Through computer simulation, the fuzzy sliding mode control shows very good tracking accuracy superior to nonfuzzy sliding mode control. Finally, a two-joint planar arm actuated by four groups of pneumatic muscles operated in an assumed industrial environment is presented. Based on the model, an integral sliding mode control scheme is proposed as an ultimate solution to the control of systems actuated by pneumatic muscles. As the theoretical proof and computer simulations show, the integral sliding mode controller, with strong robustness to model uncertainties and external perturbations, is superior for performing the commanded control assignment. Based on the investigation in this dissertation, integral sliding mode control proposed here is a very promising robust control approach to handle systems actuated by pneumatic muscles

Design of Adaptive Switching Controller for Robotic Manipulators with Disturbance

Two adaptive switching control strategies are proposed for the trajectory tracking problem of robotic manipulator in this paper. The first scheme is designed for the supremum of the bounded disturbance for robot manipulator being known; while the supremum is not known, the second scheme is proposed. Each proposed scheme consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theorem, it is shown that two new schemes can guarantee tracking performance of the robotic manipulator and be adapted to the alternating unknown loads. Simulations for two-link robotic manipulator are carried out and show that the two schemes can avoid the overlarge input torque, and the feasibility and validity of the proposed control schemes are proved

Robust Backstepping Tracking Control of Mobile Robot Based on Nonlinear Disturbance Observer

This paper presents a robust backstepping control (BC) method based on nonlinear disturbance observer (NDOB) for trajectory tracking of the nonholonomic wheeled mobile robot (WMR) in the presence of external disturbances and parameters uncertainties. At first, a bounded Fuzzy logic based backstepping controller (BFLBC) is designed to control the WMR without considering the effects of the external disturbances and the parameters uncertainties. Typically, the conventional BC controller depends upon the state tracking errors analysis, where unbounded velocity signal is produced for the applications that have huge tracking errors. Therefore, a fuzzy logic controller (FLC) is introduced in this research in order to normalize the state tracking errors, so that the input errors to the BC are bounded to a finite interval. Finally, the designed BFLBC is integrated with the nonlinear disturbance observer in order to attenuate the external disturbances and model uncertainties. The simulation results show the effectiveness of the proposed controller to generate a bounded velocity signal as well as to stabilize the tracking errors to zero. In addition, the results prove that the proposed controller provide an excellent disturbance attenuation as well as robustness against the parameters uncertainties