Fuzzy Adaptive Saturation Control for Nonlinear Systems With Event-Triggered Sampling and Quantization

Based on event-triggering and quantization mechanisms, a fuzzy adaptive quantization saturation control problem has been investigated for a class of nonlinear systems. The unknown components of the controlled system are approximated using fuzzy logic systems. Sensors are able to measure the states of the system. The state signals and some associated variables are sequentially event-triggered, quantized, and transmitted to the controller via network communication. To overcome asymmetric input saturation, an auxiliary subsystem is constructed to compensate for the nonlinearity caused by the saturation. By introducing dynamic surface technology and using the backstepping control design method, a quantization saturation control scheme is proposed, and the problem of virtual controllers being non-differentiable in quantization control is solved. Theoretical proof shows that all error signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the Zeno behavior can be avoided. The control scheme is applied to a quarter-car active suspension system, and the simulation results verify the effectiveness of the proposed control method. Note to Practitioners—Data sampling and quantization are critical processes in both computer control systems and network control systems. Event-triggered sampling can reduce network congestion and energy consumption. However, most existing methods rarely consider both event-triggering and quantization of system states and parameters simultaneously. Additionally, both the unknown components of the model and the saturation constraints of the actuator are common in control systems. Taking into account the above issues, this paper proposes a fuzzy adaptive quantization saturation control scheme based on event-triggering and quantization mechanisms. This scheme considers multiple nonlinear links that are more practical in computer control. It has been successfully validated for its applicability in a quarter-car active suspension system.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2024-09-16
DOI
https://doi.org/10.1109/tase.2024.3457537
Citations
8
Primary Topic
Stability and Control of Uncertain Systems
Type
article
Field-Weighted Citation Impact
2.63

Funders

Controls
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article

Fuzzy Adaptive Saturation Control for Nonlinear Systems With Event-Triggered Sampling and Quantization

T Wang, Hongyang Zhang, Huayang Zhang
8 citations
IEEE Transactions on Automation Science and Engineering
Stability and Control of Uncertain Systems
2.63
article

Fuzzy Adaptive Saturation Control for Nonlinear Systems With Event-Triggered Sampling and Quantization

T Wang, Hongyang Zhang, Huayang Zhang
article en
8 citations

Abstract

Based on event-triggering and quantization mechanisms, a fuzzy adaptive quantization saturation control problem has been investigated for a class of nonlinear systems. The unknown components of the controlled system are approximated using fuzzy logic systems. Sensors are able to measure the states of the system. The state signals and some associated variables are sequentially event-triggered, quantized, and transmitted to the controller via network communication. To overcome asymmetric input saturation, an auxiliary subsystem is constructed to compensate for the nonlinearity caused by the saturation. By introducing dynamic surface technology and using the backstepping control design method, a quantization saturation control scheme is proposed, and the problem of virtual controllers being non-differentiable in quantization control is solved. Theoretical proof shows that all error signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the Zeno behavior can be avoided. The control scheme is applied to a quarter-car active suspension system, and the simulation results verify the effectiveness of the proposed control method. Note to Practitioners—Data sampling and quantization are critical processes in both computer control systems and network control systems. Event-triggered sampling can reduce network congestion and energy consumption. However, most existing methods rarely consider both event-triggering and quantization of system states and parameters simultaneously. Additionally, both the unknown components of the model and the saturation constraints of the actuator are common in control systems. Taking into account the above issues, this paper proposes a fuzzy adaptive quantization saturation control scheme based on event-triggering and quantization mechanisms. This scheme considers multiple nonlinear links that are more practical in computer control. It has been successfully validated for its applicability in a quarter-car active suspension system.

IEEE Transactions on Automation Science and EngineeringVol. 22
Liaoning University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Stability and Control of Uncertain Systems
2.63
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