A Quasilinear Quadratic Tracking Algorithm for Systems with Saturating Actuators

The primary aim of this paper is to extend the classical linear quadratic tracker (LQT) to scenarios with saturating actuators. By employing stochastic linearization theory, the saturation function is replaced with equivalent gains and bias to incorporate the influence of saturated actuators in the controller design process. Additionally, two time scales are introduced to achieve high tracking accuracy. Finally, the proposed algorithm is compared with other modified LQT-based methods, demonstrating superior tracking precision. The impact of time scale selection on tracking results is also examined in the simulation section.