Global optimization of linear hybrid systems with explicit transitions
The global optimization of hybrid systems described by linear time-varying ordinary differential equations is examined. A method to construct convex relaxations of general, nonlinear Bolza-type objective functions or constraints subject to an embedded hybrid system with explicit transitions is prese...
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| Published in | Systems & control letters Vol. 51; no. 5; pp. 363 - 375 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.04.2004
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0167-6911 1872-7956 |
| DOI | 10.1016/j.sysconle.2003.09.005 |
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| Abstract | The global optimization of hybrid systems described by linear time-varying ordinary differential equations is examined. A method to construct convex relaxations of general, nonlinear Bolza-type objective functions or constraints subject to an embedded hybrid system with explicit transitions is presented. The optimization problem can be solved using gradient-based algorithms in a branch and bound framework that is shown to be infinitely convergent when the implied state bounds are employed. |
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| AbstractList | The global optimization of hybrid systems described by linear time-varying ordinary differential equations is examined. A method to construct convex relaxations of general, nonlinear Bolza-type objective functions or constraints subject to an embedded hybrid system with explicit transitions is presented. The optimization problem can be solved using gradient-based algorithms in a branch and bound framework that is shown to be infinitely convergent when the implied state bounds are employed. |
| Author | Barton, Paul I Singer, Adam B Lee, Cha Kun |
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| Cites_doi | 10.1016/S0168-9274(98)00125-1 10.1007/BF00138689 10.1287/mnsc.15.9.550 10.1021/ie00033a014 10.1145/643120.643122 10.1016/S0168-9274(97)00050-0 10.1016/S0098-1354(98)00027-1 10.1007/BF01580665 10.1002/aic.690400608 10.1109/9.654885 10.1023/B:JOTA.0000037606.79050.a7 |
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| Keywords | Convex underestimators Control parametrization Linear hybrid systems Fixed time events Multistage dynamic optimization Dynamic optimization Gradient Multistage Differential equation Branch and bound method Global optimum Linear time Discrete system Parameterization Optimization Hybrid system Boarded computer Time varying system Transition system Relaxation method Objective function Dynamic programming |
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| SubjectTerms | Applied sciences Computer science; control theory; systems Control parametrization Control theory. Systems Convex underestimators Dynamic optimization Exact sciences and technology Fixed time events Linear hybrid systems Multistage dynamic optimization |
| Title | Global optimization of linear hybrid systems with explicit transitions |
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