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Two well known approaches to nonlinear control involve the use of control Lyapunov functions (CLFs) and receding horizon control (RHC), also known as model predictive control (MPC). The on-line Euler-Lagrange computation of receding horizon control is naturally viewed in terms of optimal control, whereas researchers in CLF methods have emphasized such(More)
Issues of feasibility and stability are considered for a nite horizon formulation of receding horizon control for linear systems under mixed linear state and control constraints. We prove that given any compact set of initial conditions that is feasible for the innnite horizon problem, there exists a nite horizon length above which a receding horizon policy(More)
Many control techniques employ on-line optimization in the determination of a control policy. We develop a framework which provides suucient convex conditions, in the form of Linear Matrix Inequalities (LMIs), for the analysis of constrained quadratic based optimization schemes. These results encompass standard robustness analysis problems for a wide(More)
ii c 1999 James A. Primbs All Rights Reserved iii Acknowledgements I have been particularly fortunate during my graduate studies to have had the opportunity to collaborate with a broad range of faculty, students, and visitors. First and foremost, I am obliged to my advisor, John Doyle, who provides an atmosphere that truly allows graduate students to(More)
Control Lyapunov functions (CLFs) are used in conjunction with receding horizon control (RHC) to develop a new class of control schemes. In the process, strong connections between the seemingly disparate approaches are revealed, leading to a uniied picture that ties together the notions of pointwise min-norm, receding horizon, and optimal control. This(More)
Control Lyapunov functions (CLFs) are used in conjunction with receding horizon control (RHC) to develop a new class of receding horizon control schemes. In the process, strong connections between the seemingly disparate approaches are revealed, leading to a uniied picture that ties together the notions of pointwise min-norm, receding horizon, and optimal(More)