NCS: Receding Horizon Control
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In this lecture the receding horizon control (RHC) principle is described and the main ingredients required for its stability are discussed. After a brief review of Lyapunov stability, the use of terminal cost, constraint and controller is shown in a discrete-time constrained nonlinear system formulation. Treatment of stability is also illustrated in a continuous-time unconstrained nonlinear system setting, using a control Lyapunov function (CLF)-based terminal cost.
Constrained model predictive control: Stability and optimality, D. Q. Mayne, J. B. Rawlings, C. V. Rao and P. O. M. Scokaert. Automatica, 2000, Vol. 36, No. 6, pp. 789-814. This is one of the most referenced comprehensive survey papers on MPC. Gives a nice overview about its history and explains the most important issues and various approaches.
Online Control Customization via Optimization-Based Control, R. M. Murray et al. In Software-Enabled Control: Information Technology for Dynamical Systems, T. Samad and G. Balas (eds.), IEEE Press, 2001. This paper talks about the CLF-based nonlinear RHC approach and its application on the Caltech ducted fan using NTG.
Constrained Control and Estimation - An Optimisation Approach, G. C. Goodwin, M. M. Seron, J. A. De Dona. Springer Verlag, 2005. This is a recent book treating constrained control and estimation in a unified framework (including finite horizon optimal control and RHC) using discrete-time formulation. The website has a lot of additional useful and interesting material.
Unconstrained Receding-Horizon Control of Nonlinear Systems, A. Jadbabaie, J. Yu and J. Hauser. IEEE Transactions on Automatic Control, May 2001, Vol. 46, No. 5, pp. 776-783. This paper might be a little dense for the first read, but contains an essence of A. Jadbabaie's PhD thesis on CLF-based nonlinear RHC.
Nonlinear Receding Horizon Control: A Control Lyapunov Function Approach, A. Jadbabaie. PhD Thesis, 2000.