Continuous stirred tank reactor (CSTR), a kind of special chemical reactor, is extensively applied to chemical processing industries. However, it has long been a challenging issue to control the reactant concentration and reactant temperature of CSTR system to expected state due to the high complexity and strong nonlinearity of the chemical process. This paper presented a novel event-triggered adaptive dynamic programming (ADP) optimal control algorithm for CSTR system, where the controller is updated unless the event-triggering condition is not satisfied. The technology proposed in this paper has cut down the update frequency of the controller to 66%. Thus, computational load and communication burden can be remarkably decreased, which is very important for the real CSTR system.

Continuous stirred tank reactor (CSTR)is essential equipment found in chemical processing industries. Control of the CSTR process has long been a challenging issue due to the high complexity and strong nonlinearity of the chemical process. In this article, a novel event-triggered (ET) adaptive dynamic programming (ADP) optimal control algorithm is developed for the CSTR system. To reduce the computational load and the communication data between the controller and the actuator, a novel event-triggering condition based on the Taylor series expansion is designed for the ET controller. With the novel event-triggering condition, the control policy does not update unless the event-triggering condition is not satisfied. Compared with the time-triggering mechanism, the update frequency of the controller can be obviously reduced. Then, an identifer–actor–critic structure is developed to implement the ET ADP controller. In particular, to overcome the challenge of establishing an exact dynamic fo...