In this thesis a model reference adaptive sliding mode control scheme is proposed for a class of linear time-invariant MIMO systems with unstructured and input, output uncertainties to solve the robust tracking problems. The designing of the proposed control scheme is divided into three steps. The first step is to design the sliding functions, the second step is to construct the estimators of the lumped perturbation. These estimators are able to estimate the derivatives of the tracking errors. The third step is to design the adaptive sliding mode controller. The proposed control scheme is designed without requiring the information of the upper bound of perturbations, and guarantee the stability of the controlled system. In fact the asymptotical stability can be achieved for some special cases. Finally, three numerical examples are presented to demonstrate the feasibility of the proposed control scheme.

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New control methods are developed for the unconstrained motion and constrained force and motion control of flexible robots. The dynamic equations of the flexible robots are partitioned as pseudostatic equilibrium equations and deviations from them. The pseudostatic equilibrium considered here is defined as a hypothetical state where the tip point variables have their desired values while the modal variables are instantaneously constant. Then, the control torques for the pseudostatic equilibrium and for the stabilization of the deviation equations are formed in terms of tip point coordinates, modal variables and contact force components. The performances of the proposed methods are illustrated on a planar two-link robot and on a spatial three-link robot. Unmodeled dynamics and measurement noises are also taken into consideration. Performance of the proposed motion control method is compared with the computed torque method.