This paper studies the event-triggered (ET) H ∞ control of linear networked systems based on static output-feedback. An emulation-based stabilization of the networked system is investigated under the constraints such as (i) quantizations, (ii) network-induced delays, (iii) external disturbances, and (iv) packet losses. In particular, output measurement and control input quantizations, lower and upper bounds of the network-induced delays, bounded external disturbances, and packet losses are carefully taken into account. The process of stability analysis has three steps. In the first step, a quantized ET control is defined, and then three sector-bound methods for logarithmic quantization are formulated. In the second step, the ET-mechanism is described with an input delay model. Based on the model, for two approaches, namely, switching-ET and periodic-ET, the criteria for the exponential stability and L 2 -gain analysis of perturbed networked system are established, respectively. In the third step, a constraint for packet loss effect is provided. In summary, the stability analysis is based on linear matrix inequalities (LMIs) through a Lyapunov-Krasovskii functional method. Finally, the simulation results are given to evaluate the validation of the analysis using two benchmark examples. KEYWORDS event-triggered H ∞ control, network-induced delay, packet loss (dropout), periodic and switching approach, quantization A networked control system (NCS) is a setup including nodes that interact over a signal transaction network for its coordinated operation. With the fast development of Internet, types of wireless communication equipment, and new control schemes, NCSs have been recently paid much attention by researchers. 1,2 Such systems have found many applications in various areas of engineering, including (i) remote control of distributed or non-co-located modern industrial systems such as tele-surgery, tele-operated haptic systems, and tele-robotics, 3 especially remote controlled robots in harmful areas, for instance, nuclear locations, or space, (ii) power systems and smart grids, 4 (iii) multiagent systems, 5 and (iv) vehicle industry and modern automobile. 6 Despite the merits of networks such as flexibility, reduced wireline, easy installation, and low maintenance costs, the possible constraints include limited channel bandwidth, time delay, variable sampling and release intervals, quantization, and packet loss. These constraints lead to performance degradation or even destabilizing NCS. For reducing the network workload, the ET mechanism has been proposed. 1,[7][8][9] In the conventional/continuous ET control, the sampling time is executed after an event, which is generated by some state or/and input dependent condition, whereas, in periodic Optim Control Appl Meth. 2020;41:327-348.wileyonlinelibrary.com/journal/oca
