Optimal Modified Feedback Strategies in LQ Games under Control Imperfections
This work addresses practical control challenges in game-theoretic applications, but it is incremental as it builds on existing LQ game frameworks.
The paper tackles the problem of implementation imperfections like disturbances and actuator limitations in two-player linear quadratic games, showing that a compensation law for the influenced player locally outperforms uncompensated equilibrium strategies for small deviations.
Game-theoretic approaches and Nash equilibrium have been widely applied across various engineering domains. However, practical challenges such as disturbances, delays, and actuator limitations can hinder the precise execution of Nash equilibrium strategies. This work investigates the impact of such implementation imperfections on game trajectories and players' costs in the context of a two-player finite-horizon linear quadratic (LQ) nonzero-sum game. Specifically, we analyze how small deviations by one player, measured or estimated at each stage affect the state trajectory and the other player's cost. To mitigate these effects, we construct a compensation law for the influenced player by augmenting the nominal game with the measurable deviation dynamics. The resulting policy is shown to be optimal within a causal affine policy class, and, for sufficiently small deviations, it locally outperforms the uncompensated equilibrium-derived feedback. Rigorous analysis and proofs are provided, and the effectiveness of the proposed approach is demonstrated through a representative numerical example.