Adaptive Tracking Control for the Piezoelectric Actuated Stage Using the Krasnosel’skii-Pokrovskii Operator

Xu, Rui; Tian, Dapeng; Wang, Zhongshi

doi:10.3390/mi11050537

Cited by 12 publications

(6 citation statements)

References 33 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because k b = 0 according to (7), the output of the control system is y(s) = G m (s)u(s). Then, (12) can be denoted as follows:…”

Section: Hac Design Based On Hysteresis Compensatormentioning

confidence: 99%

“…Piezo-actuated stage (P-AS) driven by piezoelectric ceramics are broadly applied to projection lithography lenses, scanning probe microscopy, astronomical telescopes, modern optics, other advanced optoelectronic devices, and ultraprecision systems [1][2][3] owing to high resolutions and response speeds and the impregnability of the magnetic fields [4,5]. However, the intrinsic rate-dependent (RD) hysteresis of piezoelectric ceramic materials significantly affects the control and positioning accuracies of P-AS [6][7][8]. The response of RD hysteresis characteristic exhibits a special multi-value mapping relationship, where the P-AS output depends on the current input and the previous output of P-AS [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid Adaptive Controller Design with Hysteresis Compensator for a Piezo-Actuated Stage

et al. 2022

View full text Add to dashboard Cite

Piezo-actuated stage (P-AS) has become the topic of considerable interest in the realm of micro/nanopositioning technology in the recent years owing to its advantages, such as high positioning accuracy, high response speed, and large output force. However, rate-dependent (RD) hysteresis, which is an inherent nonlinear property of piezoelectric materials, considerably restricts the application of P-AS. In this research paper, we develop a Hammerstein model to depict the RD hysteresis of P-AS. An improved differential evolution algorithm and a least-squares algorithm are used to identify the static hysteresis sub-model and the dynamic linear sub-model for the Hammerstein model, respectively. Then, a hysteresis compensator based on the inverse Bouc–Wen model is designed to compensate for the static hysteresis of the P-AS. However, the inevitable modeling error presents a hurdle to the hysteresis compensation. In addition, external factors, such as environmental noise and measurement errors, affect the control accuracy. To overcome these complications, a hybrid adaptive control approach based on the hysteresis compensator is adopted to increase the control accuracy. The closed-loop system stability is analyzed with the help of the Lyapunov stability theory. Finally, experimental results indicate that the raised control approach is effective for the accurate positioning of P-AS.

show abstract

“…Because k b = 0 according to (7), the output of the control system is y(s) = G m (s)u(s). Then, (12) can be denoted as follows:…”

Section: Hac Design Based On Hysteresis Compensatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Adaptive Controller Design with Hysteresis Compensator for a Piezo-Actuated Stage

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Several hysteresis models have been proposed in previous studies to predict the hysteresis nonlinearity of piezoelectric materials [20]. The first type of hysteresis model is obtained by multiplying large number of basic operators with their corresponding weight vectors and then superimposing them together, such as the classical Preisach model [21,22], the Krasnosel'skii-Pokrovskii model [23,24], and the Prandtl-Ishlinskii model [25][26][27], etc. The advantage of these kinds of models is that they can improve the prediction accuracy by increasing the number of basic operators.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and disturbance rejection compensation for hysteresis nonlinearity of high voltage piezoelectric stack actuators

Li¹,

Liu²,

Yang³

et al. 2022

Smart Mater. Struct.

View full text Add to dashboard Cite

High voltage piezoelectric stack actuators (HVPSA) are widely used in the field of active vibration control (AVC) of engineering structures due to their strong load capacity, fast response rate, and high mechanical output efficiency. However, their inherent hysteresis will have a direct impact on the stability and control efficiency of the piezoelectric active control system. To compensate the hysteresis nonlinearity of HVPSA, a high-precision dynamic hybrid method based on linear active disturbance rejection control (LADRC) is proposed. Starting from the hysteresis analysis of piezoelectric actuators, an exponential function butterfly-shape hysteresis operator is constructed and combined with the asymmetric Bouc-Wen model to present a novel hybrid static hysteresis model. In order to implement rate-dependent hysteresis modeling, the Hammerstein rate-dependent hysteresis model of HVPSA is further established, and its inverse model is built for feedforward compensation. Subsequently, the LADRC is used to adjust the driving voltage in real time to form the hysteresis closed-loop compensator of HVPSA. The experimental results show that the Hammerstein rate-dependent hysteresis model established has satisfactory modeling accuracy in the working voltage range and frequency band under consideration. Furthermore, compared with the traditional inverse model feedforward compensation strategy, the proposed hybrid compensation method based on LADRC improves the compensation efficiency by more than 11% and reduces the hysteresis nonlinearity of HVPSA to less than 3%, with strong anti-disturbance ability.

show abstract

“…The first-mentioned group is a description of the ferromagnetic effect that produces the non-linearity, although the material dependency and complex numerical solutions are the downsides of these theories [20,21]. In regards to the phenomenological, the sub-classification is related to the ones based on differential equations (Dunhem [22], Backslash [23] and Bouc-Wen [24]), operator models (Preisach [5], Prandtl-Ishlinskii [25] and Krasnoselskii-Pokrovskii [26]) and polynomial models [27]. Nevertheless, the disadvantages of these approaches are linked with complicated solutions to gather the inverse model, incapability to deal with asymmetric hysteresis, rate dependency and complex implementation [20].…”

Section: Introductionmentioning

confidence: 99%

Advanced Trajectory Control for Piezoelectric Actuators Based on Robust Control Combined with Artificial Neural Networks

et al. 2021

View full text Add to dashboard Cite

In applications where high precision in micro- and nanopositioning is required, piezoelectric actuators (PEA) are an optimal micromechatronic choice. However, the accuracy of these devices is affected by a natural phenomenon called “hysteresis” that even increases the instability of the system. This anomaly can be counteracted through a material re-shape or by the design of a control strategy. Through this research, a novel control design has been developed; the structure contemplates an artificial neural network (ANN) feedforward to contract the non-linearities and a robust close-loop compensator to reduce the unmodelled dynamics, uncertainties and perturbations. The proposed scheme was embedded in a dSpace control platform with a Thorlabs PEA; the parameters were tuned online through specific metrics. The outcomes were compared with a conventional proportional-integral-derivative (PID) controller in terms of control signal and tracking performance. The experimental gathered results showed that the advanced proposed strategy had a superior accuracy and chattering reduction.

show abstract

Adaptive Tracking Control for the Piezoelectric Actuated Stage Using the Krasnosel’skii-Pokrovskii Operator

Cited by 12 publications

References 33 publications

Hybrid Adaptive Controller Design with Hysteresis Compensator for a Piezo-Actuated Stage

Hybrid Adaptive Controller Design with Hysteresis Compensator for a Piezo-Actuated Stage

Dynamic modeling and disturbance rejection compensation for hysteresis nonlinearity of high voltage piezoelectric stack actuators

Advanced Trajectory Control for Piezoelectric Actuators Based on Robust Control Combined with Artificial Neural Networks

Contact Info

Product

Resources

About