Improving a Proportional Integral Controller with Reinforcement Learning on a Throttle Valve Benchmark

arXiv:2402.13654v1 Announce Type: cross
Abstract: This paper presents a learning-based control strategy for non-linear throttle valves with an asymmetric hysteresis, leading to a near-optimal controller without requiring any prior knowledge about the environment. We start with a carefully tuned Proportional Integrator (PI) controller and exploit the recent advances in Reinforcement Learning (RL) with Guides to improve the closed-loop behavior by learning from the additional interactions with the valve. We test the proposed control method in various scenarios on three different …

abstract arxiv benchmark control cs.lg cs.sy eess.sy environment exploit integral knowledge linear near non-linear paper prior reinforcement reinforcement learning strategy the environment type valve