Stable adaptive systems
Telerobotics, automation, and human supervisory control
Telerobotics, automation, and human supervisory control
Neural network robust-adaptive telemanipulator control-comparison with sliding-mode control
Systems Analysis Modelling Simulation
Progress in System and Robot Analysis and Control Design
Progress in System and Robot Analysis and Control Design
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A novel Neuropredictive Teleoperation (NPT) Scheme is presented. The design results from two key ideas: the exploitation of the measured or estimated neural input to the human arm or its electromyograph (EMG) as the system input and the employment of a predictor of the arm movement, based on this neural signal and an arm model, to compensate for time delays in the system. Although a multitude of such models, as well as measuring devices for the neural signals and the EMG, have been proposed, current telemanipulator research has only been considering highly simplified arm models. In the present design, the bilateral constraint that the master and slave are simultaneously compliant to each other‘s state (equal positions and forces) is abandoned, thus obtaining a “simple to analyze” succession of only locally controlled modules, and a robustness to time delays of up to 500 ms. The proposed designs were inspired by well established physiological evidence that the brain, rather than controlling the movement on-line, “programs” the arm with an action plan of a complete movement, which is then executed largely in open loop, regulated only by local reflex loops. As a model of the human arm the well-established Stark model is employed, whose mathematical representation is modified to make it suitable for an engineering application. The proposed scheme is however valid for any arm model. BIBO-stability and passivity results for a variety of local control laws are reported. Simulation results and comparisons with “traditional” designs also highlight the advantages of the proposed design.