Event-Triggered Optimal Output Tracking Control for Industrial Automation with Stochastic Dynamics

With the recent technological development, performance of networked control systems (NCS) can suffer when stochastic dynamics are included. In literature several methods have been identified by invaders to compromise the system performance. The denial-of-service (DoS), packet loss, and time delay are well-known annoying stochastic dynamics for degrading the system performance in automated networked control system. This research deals with the design of optimal controller for industrial automation subject to stochastic uncertain dynamics. These stochastic uncertain dynamics use the Bernoulii distribution to show network uncertainty and attacks on the process. In this design first conventional proportional-integral (PI) control is addressed to evaluate performance factors. Here PI control maintains response at the desired level but as soon as packet loss and attacks are introduced by an attacker into the system, it tends to be unstable. Second, to counteract stochastic nature of dynamics event-triggered optimal control mechanism is employed. With the proposed work, the transient along with steady state performance is maintained at the reference level and guarantees the well tracking of output through simulating.