On-line Learning and Control of Partially-Known and Unknown Nonlinear Systems

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ECS-9877193IoannouWhile the control of linear time invariant (LTI) systems has reached a high level of maturity the control of nonlinear systems is still very much unexplored. Recent advances in nonlinear design and analysis techniques together with the widespread use of fast low cost computers and sophisticated software tools offer a strong potential for the development of successful control designs for nonlinear systems.In this proposal, a preliminary control design developed by the Principal Investigators for a class of nonlinear systems is used to motivate a series of research tasks that will lead to the development of a general methodology for controlling unknown nonlinear systems. The proposed control design employs ideas from robust adaptive and nonlinear control as well as function approximation results from neural and fuzzy systems to meet control objectives for a nonlinear plant that cannot be met by the current control methods. Robust adaptive control modifications. backstepping, tuning functions, nonlinear damping and control Lyapunov functions are some of the design techniques to be considered in the proposed work. Analytical tools such as Lyapunov theory, functional analysis and function approximations will be used together with computer simulations to establish and demonstrate the properties of the developed control methodologies.The expected outcome of the proposed research is the development of a methodology for controlling a wide class of unknown or partially known nonlinear plants that cannot be controlled using the current control methods.