A Separation Principle for Conditional Mean-Field Type Linear Quadratic Optimal Control Problem

TL;DR

This paper extends the classical separation principle to a conditional mean-field LQ control problem with partial observations and regime switching, providing explicit feedback control formulas and demonstrating their effectiveness through numerical examples.

Contribution

It introduces a separation principle for conditional mean-field systems with regime switching, deriving explicit feedback controls via Riccati equations.

Findings

Established a separation principle for the problem setting.

Derived explicit feedback control formulas.

Validated results through numerical simulations.

Abstract

This paper investigates a conditional mean-field type linear quadratic (LQ) optimal control problem with partial observation and regime switching, where the conditional expectations of the state and control given the history of Markov chain enter into the dynamics and cost. The exact regime of Markov chain is accessible, whereas the system state can only be partially observed. A separation principle is established, showing that the estimate and control procedures can be separated and implemented independently. It extends the classical separation principle to conditional mean-field system. Utilizing two sets of Riccati equations and a set of first-order ordinary differential equations, we derive the feedback representation of the optimal control. To illustrate the effectiveness of the theoretical results, two applications with numerical simulations are provided, including a one-dimensional LQ example and a coupled electrical machines control problem.