Solution for the Continuous-Time Infinite-Horizon Linear Quadratic Regulator Subject to Scalar State Constraints
This letter provides a solution for the continuous-time linear quadratic regulator (LQR) subject to a scalar state constraint. Using a dichotomy transformation, novel properties for the finite-horizon LQR are derived; the unknown boundary conditions are explicitly expressed as a function of the hori...
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Published in | IEEE control systems letters Vol. 4; no. 1; pp. 133 - 138 |
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Format | Journal Article |
Language | English |
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01.01.2020
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Abstract | This letter provides a solution for the continuous-time linear quadratic regulator (LQR) subject to a scalar state constraint. Using a dichotomy transformation, novel properties for the finite-horizon LQR are derived; the unknown boundary conditions are explicitly expressed as a function of the horizon length, the initial state, and the final state or cost of the final state. Practical relevance of these novel properties are demonstrated with an algorithm to compute the continuous-time LQR subject to a scalar state constraint. The proposed algorithm uses the analytical conditions for optimality, without a priori discretization, to find only those sampling time instances that mark the start and end of a constrained interval. Each subinterval consists of a finite-horizon LQR, hence, a solution can be efficiently computed and the computational complexity does not grow with the horizon length. In fact, an infinite horizon can be handled. The algorithm is demonstrated with a simulation example. |
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AbstractList | This letter provides a solution for the continuous-time linear quadratic regulator (LQR) subject to a scalar state constraint. Using a dichotomy transformation, novel properties for the finite-horizon LQR are derived; the unknown boundary conditions are explicitly expressed as a function of the horizon length, the initial state, and the final state or cost of the final state. Practical relevance of these novel properties are demonstrated with an algorithm to compute the continuous-time LQR subject to a scalar state constraint. The proposed algorithm uses the analytical conditions for optimality, without a priori discretization, to find only those sampling time instances that mark the start and end of a constrained interval. Each subinterval consists of a finite-horizon LQR, hence, a solution can be efficiently computed and the computational complexity does not grow with the horizon length. In fact, an infinite horizon can be handled. The algorithm is demonstrated with a simulation example. |
Author | van Keulen, Thijs |
Author_xml | – sequence: 1 givenname: Thijs surname: van Keulen fullname: van Keulen, Thijs email: t.a.c.v.keulen@tue.nl organization: Dept. of Mech. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands |
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References | ref13 ref15 seierstad (ref17) 1987 ref11 vinter (ref18) 2000 ref2 ref16 ref19 anderson (ref1) 1990 kwakernaak (ref10) 1972 ref8 ref7 ref9 ref4 ref3 ref6 ref5 liberzon (ref12) 2012 maciejowski (ref14) 2002 |
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Snippet | This letter provides a solution for the continuous-time linear quadratic regulator (LQR) subject to a scalar state constraint. Using a dichotomy... |
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StartPage | 133 |
SubjectTerms | Boundary conditions Eigenvalues and eigenfunctions Optimal control predictive control for linear systems Regulators Trajectory |
Title | Solution for the Continuous-Time Infinite-Horizon Linear Quadratic Regulator Subject to Scalar State Constraints |
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