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Feedback Solution to Optimal Switching Problems With Switching Cost.

Ali Heydari

    IEEE Transactions on Neural Networks and Learning Systems
    |January 27, 2015
    PubMed
    Summary

    This study introduces a method for optimal switching between nonlinear systems, penalizing switches to improve control. The approach uses approximate dynamic programming for feedback control strategies.

    Area of Science:

    • Control Theory
    • Nonlinear Systems
    • Optimization

    Background:

    • Investigates optimal switching between nonlinear autonomous subsystems.
    • Addresses challenges in state convergence and mode utilization preferences.

    Purpose of the Study:

    • To develop a method for optimal switching control that penalizes switching occurrences.
    • To provide a feedback control solution for nonlinear systems with unspecified mode sequences.

    Main Methods:

    • Incorporates a switching cost term into the cost function.
    • Develops an approximate dynamic programming-based method for solution approximation.

    Main Results:

    • Optimal cost-to-go function becomes dependent on the previously active subsystem.

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  • The method provides an approximate optimal solution in feedback form.

    • Conclusions:

    • The developed approximate dynamic programming method effectively handles optimal switching in nonlinear systems.
    • The approach is validated through numerical examples for various initial conditions.