Signal Compensation Control With DDPG-Based Tuning Strategy for Electronic Throttle System

Abstract

The electronic throttle system (ETS) is one of the important components of an automobile engine that adjust the engine air intake to directly affect the combustion power of the engine. In practical scenarios, Proportional-Integral-Derivative (PID) is a common and effective method. However, the traditional PID is difficult to satisfy the ETS performance requirements, e.g., the system response overshoot is not allowed to exist. Moreover, the controller gains are also difficult to tune manually. To tackle the above-mentioned issues, we propose a signal compensation control framework with an adaptive gain tuning strategy for the electronic throttle system, which consists of an upper-level to tune controller gains and a lower-level signal compensation controller to eliminate the nonlinear terms. The main feature of the signal compensation controller relies on two nonlinear compensators to remove the strong nonlinearity and uncertainty in the actual throttle system. Furthermore, we develop an adaptive gain tunning strategy based on Deep Deterministic Policy Gradient (DDPG) algorithm, and we analyze the corresponding stability and convergence properties of the proposed method. Finally, we illustrate the proposed algorithm on benchmarks and the tracking control problem using the real-world experiment platform of the ETS to show the effectiveness of the proposed algorithm.