closedloop - Robust Nonlinear Control Design via Convex...

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Robust Nonlinear Control Design via Convex Optimization and Its Application to Fault Tolerant Longitudinal Control of Vehicles by Bongsob Song B.S. (Hanyang University, Seoul, Korea) 1996 M.S. (University of California, Berkeley) 1999 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering - Mechanical Engineering in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor J. Karl Hedrick, Chair Professor Masayoshi Tomizuka Professor Laurent El Ghaoui Spring 2002
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The dissertation of Bongsob Song is approved: Chair Date Date Date University of California, Berkeley Spring 2002
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Robust Nonlinear Control Design via Convex Optimization and Its Application to Fault Tolerant Longitudinal Control of Vehicles Copyright Spring 2002 by Bongsob Song
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1 Abstract Robust Nonlinear Control Design via Convex Optimization and Its Application to Fault Tolerant Longitudinal Control of Vehicles by Bongsob Song Doctor of Philosophy in Engineering - Mechanical Engineering University of California, Berkeley Professor J. Karl Hedrick, Chair This dissertation presents a new analysis and design method for robust nonlinear control in the framework of Dynamic Surface Control (DSC), and its extension to fault tolerant control (FTC). The results are shown to apply to a class of nonlinear systems and in particular to automated longitudinal vehicle control. FTC has recently received significant attention in the design of large- scale systems such as automated highway systems due to a growing demand for reliability and an increase in complexity. A systematic procedure is needed to realize the ultimate benefits of a fault tolerant control system, thus leading to several interesting questions in the area of nonlinear control. Before developing a full FTC design method, it is necessary to develop an analysis and design procedure for nonlinear systems under a no-fault assumption. The method developed in this thesis is the DSC method, which is a “synthetic input” method, similar to the integrator backstep- ping method. The investigation of augmented closed loop error dynamics leads us to derive convex
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2 optimization problems for testing the stability and performance of nonlinear systems via DSC. It results in the development of a systematic method to choose appropriate gains and filter time con- stants for DSC and to analyze both the stability and tracking performance. We extend this rigorous analytical framework to derive a separation principle for nonlinear compensators which combine a nonlinear observer with DSC. The principle enables us to design the observer and DSC indepen- dently if full state information is not available or faults occur in the sensor measurements. Moreover, an initial condition set which guarantees quadratic stability for the regulation problem with input constraints, as well as a region of attraction, are estimated numerically within the framework of convex optimization.
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closedloop - Robust Nonlinear Control Design via Convex...

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