Global sampled‐data output‐feedback stabilization for nonlinear systems with unknown measurement sensitivity

Wang, Pan; Chai, Lu; Chen, Chih Chiang; Fei, Shumin

doi:10.1002/rnc.4668

Cited by 11 publications

(12 citation statements)

References 33 publications

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“…Compared with the traditional time-triggered signal transmission strategy [ 39 , 40 ], the event-triggered mechanism can reduce the frequency of sending redundant control signals in the system, restrain unnecessary information transmission, and make full use of bandwidth resources. The collaborative design of the event trigger and the controller can effectively ensure the fault tolerance performance of the system.…”

Section: The Main Resultsmentioning

confidence: 99%

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

Zhu

Chen

et al. 2020

Entropy

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This paper considers an adaptive fault-tolerant control problem for a class of uncertain strict feedback nonlinear systems, in which the actuator has an unknown drift fault and the loss of effectiveness fault. Based on the event-triggered theory, the adaptive backstepping technique, and Lyapunov theory, a novel fault-tolerant control strategy is presented. It is shown that an appropriate comprise between the control performance and the sensor data real-time transmission consumption is made, and the fault-tolerant tracking control problem of the strict feedback nonlinear system with uncertain and unknown control direction is solved. The adaptive backstepping method is introduced to compensate the actuator faults. Moreover, a new adjustable event-triggered rule is designed to determine the sampling state instants. The overall control strategy guarantees that the output signal tracks the reference signal, and all the signals of the closed-loop systems are convergent. Finally, the fan speed control system is constructed to demonstrate the validity of the proposed strategy and the application of the general systems.

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Section: The Main Resultsmentioning

confidence: 99%

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

Zhu

Chen

et al. 2020

Entropy

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“…In [3,4], H ∞ control approaches were proposed for linear systems. For nonlinear systems, effective high-gain observer designs were suggested in [5,6] and output-feedback control methods were studied in [7][8][9][10][11][12][13][14][15][16][17]. In [7][8][9][10][11][12][13], the inaccurate measurements were modeled by an unknown output function.…”

Section: Introductionmentioning

confidence: 99%

“…However, these works [7][8][9][10][11][12][13] assume that the partial derivative of the unknown output function is upper and lower bounded by some known constants. In [14][15][16][17], unknown sensor sensitivities were defined as unknown timevarying parameters. The output-feedback stabilization problems were solved by using a dual-domination approach [14] and by utilizing a matrix inequality approach [15].…”

Section: Introductionmentioning

confidence: 99%

“…The output-feedback stabilization problems were solved by using a dual-domination approach [14] and by utilizing a matrix inequality approach [15]. Also, these problems were considered for sampled-data nonlinear systems [16] and for stochastic feedforward systems [17]. Despite these efforts, the control methods presented in [14][15][16][17] depend on the known upper and lower bounds of the unknown sensor sensitivity to guarantee the closed-loop stability.…”

Section: Introductionmentioning

confidence: 99%

“…Also, these problems were considered for sampled-data nonlinear systems [16] and for stochastic feedforward systems [17]. Despite these efforts, the control methods presented in [14][15][16][17] depend on the known upper and lower bounds of the unknown sensor sensitivity to guarantee the closed-loop stability. Thus, the existing results cannot provide a solution on the output-feedback control problem of nonlinear systems with completely unknown bounds of the uncertain sensor sensitivity.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Output-Feedback Control of a Class of Nonlinear Systems with Unknown Sensor Sensitivity and Its Experiment for Flexible-Joint Robots

Jeong

Choi

Yoo

2020

J. Electr. Eng. Technol.

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This paper investigates an adaptive output-feedback stabilization problem for a class of uncertain nonlinear systems with an unknown sensor sensitivity. A high-gain observer based on an inexact system output is designed to estimate unmeasurable state variables and an adaptive output-feedback dynamic surface control strategy is established to accomplish the robust stabilization in the presence of the unknown sensor sensitivity. Compared with the existing control results dealing with the unknown sensor sensitivity, the primary contribution of this paper is that the proposed adaptive control strategy does not require the information of the sensor sensitivity and its bound where the effect of the unknown sensor sensitivity is compensated by designing an adaptation structure. From the Lyapunov stability analysis, the ultimate uniform boundedness of all closed-loop signals and the convergence of the stabilization error to an adjustable neighborhood of the origin are ensured. A simulation for a numerical example and an experiment for a flexible-joint robot are provided to validate the effectiveness of the proposed theoretical approach.

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Seven‐degree‐of‐freedom‐based electric wheel sampled‐data active shimmy control method considering unknown sensor measurement error

Meng,

Liu,

Sun

et al. 2024

Asian Journal of Control

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The active shimmy control methods for electric vehicle driven by in‐wheel motors (EV‐DIM) have been proposed in the recent years. However, these methods assume that data obtained from sensors are accurate, despite the fact that sensor measurements are prone to error. This unknown measurement error can make shimmy control difficult. Additionally, current shimmy models are low degree‐of‐freedom, which simplifies control but decreases accuracy. In this paper, we address these issues using a sampled‐data output control method based on a higher seven‐degree‐of‐freedom (7DOF) shimmy model which includes the steering system, suspension, and electric wheel. We first construct a 7DOF electric wheel shimmy model and use Lagrange's theorem to derive the electric wheel shimmy dynamic equations. We then obtain system state equations that account for unknown sensor measurement error based on the 7DOF shimmy model. A sampled‐data observer and controller are designed to attenuate or eliminate the shimmy phenomenon via a domination gain. Finally, we conduct numerical simulations and experiments to verify the effectiveness of our proposed method.

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Global sampled‐data output‐feedback stabilization for nonlinear systems with unknown measurement sensitivity

Cited by 11 publications

References 33 publications

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

Adaptive Output-Feedback Control of a Class of Nonlinear Systems with Unknown Sensor Sensitivity and Its Experiment for Flexible-Joint Robots

Seven‐degree‐of‐freedom‐based electric wheel sampled‐data active shimmy control method considering unknown sensor measurement error

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