Nonlinear control design of piezoelectric actuators with micro positioning capability

Chen, Yung Yue; Huang, Min; Tsai, Yi Lin

doi:10.1007/s00542-019-04437-9

Cited by 6 publications

(7 citation statements)

References 16 publications

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“…For verifying the trajectory tracking performance of this proposed fuzzy-based control method, two scenarios: a trapezoidal trajectory and a staircase trajectory are adopted. Comparisons of this proposed fuzzy-based control method with respect to the feedback linearization (FL) control method and the robust control method [15] will be discussed in this section. The famous software: MATLAB is adopted to execute simulation results and optimally solve the LMI problem in Eq.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…1 Hysteresis loop of the piezoelectric actuator International Journal of Fuzzy Systems piezoelectric actuator with the hysteresis behavior in Fig. 1 can be expressed as the following form [14,15].…”

Section: Schematic and Mathematical Model Of The Controlled Piezoelectric Actuatormentioning

confidence: 99%

“…The nominal model parameters of the controlled piezoelectric actuator can be identified by using particle swarm optimization (PSO) method [15] and listed as Table 1.…”

Section: Parameters Of the Controlled Piezoelectric Actuatormentioning

confidence: 99%

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Micrometer Level Control Design of Piezoelectric Actuators: Fuzzy Approach

Chen

Gieng

Liao

et al. 2021

Int. J. Fuzzy Syst.

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In this investigation, a fuzzy-based micrometer level control design with a guaranteed trajectory tracking performance for piezoelectric actuators which naturally have hysteresis effects is proposed. Nominal dynamics of the controlled piezoelectric actuators are described by adopting Takagi and Sugeno fuzzy models initially. Via interpolating Takagi and Sugeno local fuzzy model, a robust fuzzy-based controller is developed to eliminate hysteresis, modeling uncertainties and external disturbances. Meanwhile, the tracking error is expected to be reduced as small as possible with respect to all bounded desired trajectories. This proposed fuzzy-based controller has an easy to implement control structure. The trajectory tracking design problem of piezoelectric actuators of this study is transferred to a linear matrix inequality problem, and based on the convex optimization technique, the solution of the trajectory tracking design problem of piezoelectric actuators can be solved efficiently. From the simulation results, it is obvious that this proposed fuzzy-based control design possesses robustness property and can converge tracking errors to zero in micrometer level.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Schematic and Mathematical Model Of The Controlled Piezoelectric Actuatormentioning

confidence: 99%

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Micrometer Level Control Design of Piezoelectric Actuators: Fuzzy Approach

Chen

Gieng

Liao

et al. 2021

Int. J. Fuzzy Syst.

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“…Hence, the Lyapunov stability proof establishes that a dynamical system is asymptotically stable if there exists a definite Lyapunov function V(S), such that V: [93][94][95]. Thus, the Lyapunov function chosen is Equation (31); the correspondent time derivative is defined in Equation (32).…”

Section: Stability Proofmentioning

confidence: 99%

“…The significant presence of nonlinearities in PEAs aims to implement controllers which can deal with these features. Feedback linearization with uncertainties control has been employed recently with the addition of a Bouc-Wen (BW) model for hysteresis where the researchers achieved good accuracy although the BW is limited for asymmetric hysteresis response [32,33]. An advance approach has equally been used with model predictive control based on an adaptive algorithm that was tested in a real system that provided an error of around 1%, which is an acceptable although tests were performed with low amplitude signals [34].…”

Section: Introductionmentioning

confidence: 99%

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

et al. 2021

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Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.

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Dynamic rate-dependent hysteresis modeling and trajectory prediction of voice coil motors based on TF-NARX neural network

Rui-chao

et al. 2023

Microsyst Technol

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Nonlinear control design of piezoelectric actuators with micro positioning capability

Cited by 6 publications

References 16 publications

Micrometer Level Control Design of Piezoelectric Actuators: Fuzzy Approach

Micrometer Level Control Design of Piezoelectric Actuators: Fuzzy Approach

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

Dynamic rate-dependent hysteresis modeling and trajectory prediction of voice coil motors based on TF-NARX neural network

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