Observer-Based Decentralized Adaptive Control of Interconnected Nonlinear Systems With Output/Input Triggering

In this article, a double-channel event-triggered control method is developed for nonlinear uncertain interconnected systems using backstepping techniques, which introduces event-triggering mechanisms at both the sensor and controller sides. Using event-triggering mechanism at the sensor side presents a challenge to the backstepping control design as the discontinuous state/output signals received at the controller side result in nondifferentiable virtual control signals. This challenge becomes more pronounced when considering more general types of event-triggering mechanisms. Compared with existing methods, this article proposes a different idea with three innovative features: 1) the proposed event-triggering mechanism does not require the calculation of virtual control signals at the sensor side before transmitting them to the controller side; 2) the output triggering is considered directly, and there is no need to design separate controllers for the two communication scenarios without and with event-triggering, thereby avoiding the effect of errors caused by processing substitutions; and 3) it necessitates the online update of only one parameter estimator, avoiding the issue of over-parameterization. Finally, we validate the effectiveness and advantages of the proposed decentralized event-triggered control approach through a numerical case study.

I. Introduction

In engineering applications, the successful execution of tasks frequently requires the coordinated efforts of multiple interconnected and interactive subsystems, collectively forming a complex interconnected system. Given the interconnected nature of these subsystems, it is difficult to design effective controllers for interconnected systems using centralized control schemes. To handle this issue, the decentralized control framework is developed, motivated by designing local controllers to reduce the computational burden on the controllers and the information communication between subsystems [1], [2], [3], [4], [5], [6]. However, as more subsystems and interconnected operations are introduced, the transmission and computation burdens will increase accordingly. The use of traditional time-triggered control methods will consume a significant amount of communication resources and computation costs in such scenarios.