الفهرس 
Adaptive Control SystemsOnly 14 pages are availabe for public view
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Abstract
The objective of this dissertation is to design novel and versatile control designs that are applied to complex, uncertain nonlinear systems. The proposed designs are adaptive; i.e. they adapt to changes imposed by either the external working environment, or the internal parameters of the systems. The key issue in this dissertation is how to tackle the problem of designing modelbased controllers for complex nonlinear systems, for which the model can be illdefined, and where partial or no information is available about some or all of the parameters. It is intended to robustify adaptive control designs, by overcoming the limitations of traditional adaptive control systems that rely on the certainty equivalence principle for their designs, and for which direct manipulation of the covariance between the parameters and their estimation errors is required. The challenge is how to deal with uncertain nonlinear systems, without having to cancel useful nonlinearities. In fact, the control structures, to be designed, add more nonlinear terms to the original system to develop an overparameterized controller that can guarantee both stable and satisfactory performance. The use of Lyapunov functions is extended to include stabilization, the design of the parameter update mechanisms, and to implement the controller in a recursive way using some of the states as virtual controls. Three different control structures are presented, and compared against existing controllers to exemplify their superiority. Novelty and versatility of the control designs are demonstrated using numerous simulations and applications of different interests.