# Difference between revisions of "NCS: Receding Horizon Control"

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<!-- Enter a 1 paragraph description of the contents of the lecture. Make sure to include any key concepts, so that the wiki search feature will pick them up --> | <!-- Enter a 1 paragraph description of the contents of the lecture. Make sure to include any key concepts, so that the wiki search feature will pick them up --> | ||

− | + | 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. | |

== Lecture Materials == | == Lecture Materials == | ||

<!-- Include links to materials that you used in your lecture. At a minimum, this should include a link to your lecture presentation. You might also include links to MATLAB scripts or other source code that students would find useful --> | <!-- Include links to materials that you used in your lecture. At a minimum, this should include a link to your lecture presentation. You might also include links to MATLAB scripts or other source code that students would find useful --> | ||

<!-- Sample lecture link: * [[Media:L1-1_Intro.pdf|Lecture: Networked Control Systems: Course Overview]] --> | <!-- Sample lecture link: * [[Media:L1-1_Intro.pdf|Lecture: Networked Control Systems: Course Overview]] --> | ||

+ | [[Media:L3-2_rhc.pdf|Lecture: Receding Horizon Control]] | ||

== Reading == | == Reading == | ||

− | < | + | * <p>[http://dx.doi.org/10.1016/S0005-1098(99)00214-9 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.</p> |

+ | * <p>[http://www.cds.caltech.edu/~murray/papers/2001n_mur+03-sec.html 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.</p> | ||

== Additional Resources == | == Additional Resources == |

## Latest revision as of 22:36, 10 April 2006

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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.

## Lecture Materials

Lecture: Receding Horizon Control

## Reading

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.

## Additional Resources

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.