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On the embedding transformation for optimal control of multi-mode switched systems

Masoud S. Sakha, Rushikesh Kamalapurkar

TL;DR

A modified EOCP (MEOCP) is introduced by adding a concave auxiliary cost function of appropriate dimensionality to the main cost function, which ensures that the optimal solution of the EOCP is bang-bang, and as a result, feasible for the original SOCP.

Abstract

This paper develops an embedding-based approach to solve switched optimal control problems (SOCPs) with an arbitrary number of subsystems. Initially, the discrete switching signal is represented by a set of binary variables, encoding each mode in binary format. An embedded optimal control problem (EOCP) is then formulated by replacing these binary variables with continuous embedded variables that can take intermediate values between zero and one. Although embedding allows SOCPs to be addressed using conventional techniques, the optimal solutions of EOCPs often yield intermediate values for binary variables, which may not be feasible for the original SOCP. To address this challenge, a modified EOCP (MEOCP) is introduced by adding a concave auxiliary cost function of appropriate dimensionality to the main cost function. This addition ensures that the optimal solution of the EOCP is bang-bang, and as a result, feasible for the original SOCP.

On the embedding transformation for optimal control of multi-mode switched systems

TL;DR

A modified EOCP (MEOCP) is introduced by adding a concave auxiliary cost function of appropriate dimensionality to the main cost function, which ensures that the optimal solution of the EOCP is bang-bang, and as a result, feasible for the original SOCP.

Abstract

This paper develops an embedding-based approach to solve switched optimal control problems (SOCPs) with an arbitrary number of subsystems. Initially, the discrete switching signal is represented by a set of binary variables, encoding each mode in binary format. An embedded optimal control problem (EOCP) is then formulated by replacing these binary variables with continuous embedded variables that can take intermediate values between zero and one. Although embedding allows SOCPs to be addressed using conventional techniques, the optimal solutions of EOCPs often yield intermediate values for binary variables, which may not be feasible for the original SOCP. To address this challenge, a modified EOCP (MEOCP) is introduced by adding a concave auxiliary cost function of appropriate dimensionality to the main cost function. This addition ensures that the optimal solution of the EOCP is bang-bang, and as a result, feasible for the original SOCP.

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