This paper investigates the problem of output feedback control for networked discrete-time systems with two quantized signals in measurement output and control input. Since the measurement output and control input are quantized by general quantizers before they are passed to the controller and the system, the closed-loop system will include the quantization error terms, which might lead to that the performance of the closed-loop system is not guaranteed. For this purpose, this paper proposes a novel quantized output control strategy such that the closed-loop system is asymptotically stable or satisfies the prescribed $\mathcal{H}_\infty$ performance. The corresponding design conditions for the output feedback controllers and the quantizers' dynamic parameters are presented in terms of solutions to a set of linear matrix inequalities (LMIs). Finally, two simulation examples are given to prove the effectiveness of the proposed design method.

This paper investigates the output feedback H∞ control problem for a class of continuous-time nonlinear systems with both output and input quantization. The nonlinear plant is represented by a Takagi-Sugeno fuzzy model. The measurement output and the control input signals will be quantized by dynamic quantizers. The attention of this paper is focused on the design of the output feedback controller and quantizers such that the fuzzy closed-loop system is asymptotically stable and also achieves a prescribed H∞ noise attenuation level with respect to the effect of quantization. In the presence of quantization, two novel H∞ performance analysis criteria are presented for the considered fuzzy systems based on the descriptor representation approach. Then, sufficient conditions for the existence of the feedback H∞ controller gain and the quantizers' dynamic parameters are expressed in terms of linear matrix inequalities. An adjusting scheme on quantizers' parameters is proposed for the fuzzy system. Simulation examples are provided to show the effectiveness of the proposed design method.

In this paper, the peak-to-peak filtering problem is studied for a class of networked nonlinear systems. The nonlinear physical plant is represented by Takagi-Sugeno (T-S) fuzzy system. Assume that the data packet dropout phenomenon may occur when the measurement output signal and the performance output signal of the nonlinear systems are transmitted by the digital communication channel. Two stochastic variables satisfying the Bernoulli random binary distribution are used to model this phenomenon. The motive of this paper is to design a peakto- peak filter such that the filtering error system is stochastically stable and the prescribed peak-to-peak performance index is guaranteed. The developed theoretical results for designing a peak-to-peak filter are expressed in the form of linear matrix inequalities (LMIs). Finally, a simulation example is presented to illustrate the validity of theoretical analysis.

Summary: This study addresses the quantized nonfragile feedback control problem for active suspension systems with and without actuator faults. By considering the input quantization, a class of dynamic quantizers is adopted. The multiplicative controller gain variation is used to describe the actuator parameter perturbation or uncertainty. Apart from the ride comfort, the road holding ability and the hard constraints on suspension deflection and actuator force are also taken into account, which can be treated as a multi‐objective control problem. The redundancy of input quantization error is used to formulate the quantized closed‐loop system via the descriptor representation approach, then a novel quantized control strategy based on state feedback by separately designing dynamic quantizer and controller is proposed for the closed‐loop system with and without actuator faults. The design strategy is a unified and simple one, then can be easily extended to the case of static output feedback, as only part of the variables measured by sensors are available, which avoids some equality constraints in existing works. Finally, some simulation results are presented to validate the feasibility and effectiveness of the developed control strategies.

This paper investigates the problem of event-based output feedback tracking control for discrete-time nonlinear networked systems with dynamic quantization. The Takagi-Sugeno (T-S) fuzzy systems theory is utilized to approximate the investigated nonlinear systems. Three general dynamic quantizers and an improved asynchronous event-triggering communication scheme are carried out to comprehensively decrease the amount of data in the communication of network and realize the rational utilization of limited communication resources. The objective is to design an event-based static output feedback tracking controller such that, in the presence of dynamic quantization, the closed-loop system can be asymptotically stabilized, and the tracking error achieves the predefined tracking performance. Moreover, the parameters for the desired dynamic quantizers and tracking controller can be obtained simultaneously by solving a set of linear matrix inequalities. Finally, the simulation responses are provided to demonstrate the validity of the proposed tracking control strategy.

This paper studies the estimation problem for a class of nonlinear tunnel diode circuits with parameter perturbation. The dynamics of the nonlinear circuit is approximated by the Takagi-Sugeno fuzzy model with linear fractional parametric uncertainties. Considering the fuzzy filter with gain uncertainties, a filtering error system can be gotten naturally. The concentration of this paper lies in deriving the design conditions for the desired resilient filter such that the filtering error system preserves asymptotic stability as well as the L∞-norm of the transfer function from the external disturbance input to the filtering error output is below a specified bound. The filter design conditions for guaranteeing the prescribed peak-to-peak performance of the filtering error system are provided by a set of linear matrix inequalities. Finally, a simulation result is presented to illustrate the validity and effectiveness of the proposed filtering design for the parameter-controlled tunnel diode circuit.