Identification and Control of Robot Manipulator Using Fuzzy Wavenet
Models, Methods, and Applications
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Reliable hands-on Techniques for identification and control of robot manipulator, were presented in this book, using innovative soft-computing tools. In recent years, controller design for systems having complex nonlinear dynamics becomes an important and challenging topic. Many remarkable results in this area have been obtained owing to the advances in geometric nonlinear control theory, and in particular, feedback linearization techniques. Both state feedback and output feedback linearization methods were studied in the literature. Under certain assumptions, these output feedback controllers...
Reliable hands-on Techniques for identification and control of robot manipulator, were presented in this book, using innovative soft-computing tools. In recent years, controller design for systems having complex nonlinear dynamics becomes an important and challenging topic. Many remarkable results in this area have been obtained owing to the advances in geometric nonlinear control theory, and in particular, feedback linearization techniques. Both state feedback and output feedback linearization methods were studied in the literature. Under certain assumptions, these output feedback controllers can guarantee the global stability of the closed-loop systems based on state observers. Applications of these approaches are quite limited because they rely on the exact knowledge of the plant nonlinearities. In order to relax some of the exact model matching restrictions, several adaptive schemes have recently been introduced to solve the problem of parametric uncertainties. At the presentstage they are only applicable to a kind of affine systems which can be linearly parameterized.
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