Optimization: algorithms and consistent approximations
Optimization: algorithms and consistent approximations
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Results and perspectives on computational methods for optimal control of switched systems
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Dynamic programming for constrained optimal control of discrete-time linear hybrid systems
Automatica (Journal of IFAC)
Scheduling of a limited communication channel for optimal control
Automatica (Journal of IFAC)
Variational formulation and optimal control of hybrid lagrangian systems
Proceedings of the 14th international conference on Hybrid systems: computation and control
Synthesis of optimal switching logic for hybrid systems
EMSOFT '11 Proceedings of the ninth ACM international conference on Embedded software
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One of the oldest problems in the study of dynamical systems is the calculation of an optimal control. Though the determination of a numerical solution for the general non-convex optimal control problem for hybrid systems has been pursued relentlessly to date, it has proven difficult, since it demands nominal mode scheduling. In this paper, we calculate a numerical solution to the optimal control problem for a constrained switched nonlinear dynamical system with a running and final cost. The control parameter has a discrete component, the sequence of modes, and two continuous components, the duration of each mode and the continuous input while in each mode. To overcome the complexity posed by the discrete optimization problem, we propose a bi-level hierarchical optimization algorithm: at the higher level, the algorithm updates the mode sequence by using a single-mode variation technique, and at the lower level, the algorithm considers a fixed mode sequence and minimizes the cost functional over the continuous components. Numerical examples detail the potential of our proposed methodology.