| Summary: | 碩士 === 崑山科技大學 === 電機工程研究所 === 91 === This paper addresses the problem of designing robust tracking controls of robot systems actuated by brushed direct current motors which involve parametric uncertainties and external disturbances. A unified and systematic procedure is employed to derive the controllers with respect to various different properties of uncertain nonlinear dynamics of electromechanical systems. First, if the uncertain dynamics satisfies the property of linear parametrization (i.e., the structure of system dynamics is known), then we shall construct the classical adaptive/robust state feedback tracking controller. Next, if the uncertain dynamics cannot be linearly parametrized (i.e., the structure of system dynamics is completely unknown), then we shall construct the neural-network-based adaptive/robust state feedback tracking controller. By employing the integrator backstepping approach and suitably choosing the Lyapunov function, we can show that all the states and signals of the resulting closed-loop system are bounded and the tracking error is uniformly ultimately bounded (UUB). The implementation of the developed controllers requires the measurements of link positions, link velocities and armature currents only. On the other hand, with respect to different properties of the inductance matrix (e.g., unknown constant matrix、a known invertible matrix plus a small perturbation, etc.), we shall design different adaptive/robust tracking controllers, respectively, in which the VSC technique will be incorporated. Finally, computer simulations are made to demonstrate the effectiveness and the tracking performance of the developed controllers. Consequently, compared with the previous classical adaptive control schemes and intelligent adaptive control schemes, the hybrid adaptive/robust control schemes developed here can be applied to a broader class of electromechanical systems involving a significant degree of uncertainty.
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