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By Dan Zhang, Bin Wei

The robot mechanism and its controller make an entire process. because the robot mechanism is reconfigured, the regulate method needs to be tailored hence. the necessity for the reconfiguration frequently arises from the altering useful requisites. This e-book will concentrate on the adaptive keep an eye on of robot manipulators to handle the replaced stipulations. the purpose of the publication is to summarise and introduce the cutting-edge applied sciences within the box of adaptive keep an eye on of robot manipulators in an effort to enhance the methodologies at the adaptive keep an eye on of robot manipulators. Advances made some time past many years are defined within the publication, together with adaptive regulate theories and layout, and alertness of adaptive keep watch over to robot manipulators.

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Adaptive control. 32 Adaptive Control for Robotic Manipulators The adaptive control can be categorized into the following, model reference adaptive control, self-tuning adaptive control and gain-scheduled control, as shown in Fig. 3. Here we will mainly consider the model-reference approach. For the model-reference adaptive control, the set value is used as an input to both the actual and the model systems, and difference between the actual output and the output from the model is compared. The difference in these signals is then used to adjust the parameters of the controller to minimize the difference.

A steepest-descent method was Discussion on Model Reference Adaptive Control of Robotic Manipulators 35 used for updating the feedback gains. Firstly the reference model dynamics was written, subsequently the nonlinear manipulator (plant) dynamic equation was written, but how this equation is related to the Lagrange equation is not clear, thirdly an error function was written and it follows the method of steepest descent and a set of equations was derived for the parameter adjustment mechanism, which will minimize the difference between the actual closed-loop system response and the reference model response.

International Journal of Machine Tools and Manufacture, 40(14): 2083–2097. Uchiyama, M. 1978. Formation of High-Speed Motion Pattern of a Mechanical Arm by Trial (Japanese Title: 試行による人工の手の高速運動パターンの形成). Transactions of the Society of Instrument and Control Engineers, 14: 706–712. , B. Demeulenaere, J. Swevers, J. De Schutter and M. Diehl. 2009. Time-optimal path tracking for robots: A convex optimization approach. Automatic Control, IEEE Transactions on, 54(10): 2318–2327. Xia, Y. and J. Wang. 2004.

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