Adaptive tracking control solely using displacement feedback for a piezo-positioning mechanism

Shieh, Hsin-Jang; Lin, Faa-Jeng; Huang, Po-Kai; Teng, Li-Tao

doi:10.1049/ip-cta:20040795

Cited by 39 publications

(22 citation statements)

References 16 publications

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“…Other advanced control techniques such as state feedback [123], optimal control [109,124], adaptive control [125][126][127][128], and neuron network methods [129][130][131] have also been applied to control PEAs.…”

Section: Feedbackmentioning

confidence: 99%

A Survey of Modeling and Control of Piezoelectric Actuators

Peng¹,

Xiongbiao²

2013

MME

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Piezoelectric actuators (PEAs) have been widely used in micro-and nanopositioning applications due to their fine resolution, fast responses, and large actuating forces. However, the existence of nonlinearities such as hysteresis makes modeling and control of PEAs challenging. This paper reviews the recent achievements in modeling and control of piezoelectric actuators. Specifically, various methods for modeling linear and nonlinear behaviors of PEAs, including vibration dynamics, hysteresis, and creep, are examined; and the issues involved are identified. In the control of PEAs as applied to positioning, a review of various control schemes of both model-based and non-model-based is presented along with their limitations. The challenges associated with the control problem are also discussed. This paper is concluded with the emerging issues identified in modeling and control of PEAs for future research.

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Section: Feedbackmentioning

confidence: 99%

A Survey of Modeling and Control of Piezoelectric Actuators

Peng¹,

Xiongbiao²

2013

MME

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“…Recent examples include an adaptive control using back-stepping approach [6], a combination of feedforward model with feedback control with an input shaper [7], PID-based control with iterative learning plus disturbance observer [8], and a sliding mode control augmented with inverse hysteresis model [9].…”

Section: Introductionmentioning

confidence: 99%

Robust Control Framework for Piezoelectric Actuation Systems in Micro/Nano Manipulation

Liaw

Oetomo

Shirinzadeh

et al. 2005

TENCON 2005 - 2005 IEEE Region 10 Conference

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Abstract-Micro/nano manipulation has been identified as one of the key enabling technologies for many emerging challenges. Within this scope, piezoelectric actuators have played major roles in achieving the required nano-resolution motion. This paper proposes a robust control framework for piezoelectric actuation systems to follow specified motion trajectories. The basic concept associated with this methodology lies in the specification of a target performance and the robust control scheme formulation for piezoelectric actuation systems to ensure the convergence of the position tracking error to zero. This control methodology is attractive as its implementation requires only the knowledge of the estimated system parameters and their corresponding bounds, including bound of hysteresis and external disturbances. Feasibility study of the framework for piezoelectric actuation systems in micro/nano manipulation is described. Simulation results validated the suitability of the proposed control approach.

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“…Some of these methods are PI and PID controller, fuzzy controller [11], adaptive RFNN [12], feed-forward model reference control method [13], adaptive hysteresis inverse cascade with the plant [14], reinforcement discrete neuro-adaptive controller [15], adaptive wavelet neural network controller [16], nonlinear observer-based sliding-mode controller [17] an adaptive backstepping controller [10,18], robust motion tracking controller based on sliding-mode theory [19] and continuous time controller based on SMC and disturbance observer [20]. In some of these works, a complex inverse hysteresis model has been adopted to overcome the nonlinear hysteresis effect.…”

mentioning

confidence: 99%