Damping Control by Fusion of Reinforcement Learning and Control Lyapunov Functions

The main idea behind the concept, proposed in the paper, is the opportunity to make control systems with increased capabilities by synergetic fusion of the domain-specific knowledge and the methodologies from control theory and artificial intelligence. The particular approach considered combines Control Lyapunov Functions (CLF), a constructive control technique, and Reinforcement Learning (RL) in attempt to optimize a mix of system stability and performance. Two control schemes are proposed and the capabilities of the resulting controllers are illustrated on a control problem involving a thyristor controlled series capacitor (TCSC) for damping oscillations in a four-machine power system.