Dynamic Decentralized Event-Triggered Tracking Control of Continuous Stirred Tank Reactor Systems

We develop a dynamic decentralized event-triggered tracking control strategy for cascade interconnected continuous stirred tank reactor (CSTR) systems subject to asymmetric input limits. Initially, we construct auxiliary augmented subsystems related to the cascade interconnected CSTR systems. Then, by introducing modified nonquadratic cost functions for the auxiliary augmented subsystems, we convert the decentralized constrained tracking control problem into an array of unconstrained optimal regulation problems. After that, with the construction of dynamic event-triggering mechanisms, we propose the event-triggered Hamilton-Jacobi-Bellman equations (ET-HJBEs) associated with the transformed optimal regulation problems. To approximately solve the ET-HJBEs, we design critic neural networks (CNNs) in the adaptive dynamic programming framework with the CNNs’ weights being updated through the gradient descent method. Furthermore, we use Lyapunov method to prove that the CNNs’ weight estimation errors and the tracking error are stable in the sense of uniform ultimate boundedness. Finally, simulation results of the three-reactor cascade interconnected CSTR systems are provided to validate the present dynamic decentralized event-triggered tracking control scheme.