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This paper presents a new control scheme to compensate for the amplitude- and rate-dependent hysteresis behavior of a piezo-driven parallel stage developed for the application of biological cell manipulation. A variable phase-delay model with variable gain is established to describe the nonlinear hysteresis of the system. The proposed controller integrates an inverse model-based preview feedforward...
In this paper, the hysteresis modeling and compensation are carried out and verified for a piezo-driven XY parallel micropositioning stage aiming at a sub-micron precise motion tracking control. Specifically, inverse modified Prandtl-Ishlinskii (MPI) model-based feedforward in combination with a proportional-integral-derivative (PID) feedback control algorithm is implemented for the real-time control...
In this paper, a two-loop controller is proposed to suppress the hysteresis and to achieve a precise motion tracking control for a piezo-driven XY parallel micropositioning system. Specifically, an inner-loop disturbance observer (DOB) is employed to tolerate the unmodeled hysteresis which is treated as a disturbance to the nominal plant model of the system, and an outer-loop feedback controller is...
This paper proposes an improved sliding mode control with perturbation estimation (SMCPE) featuring a PID-type sliding surface and adaptive gains for the motion tracking control of a micromanipulator system with piezoelectric actuation. One advantage of the proposed controller lies in that its implementation only requires the online estimation of perturbation and control gains without acquiring the...
In this paper, a global sliding mode control (GSMC) scheme is implemented on a piezo-driven XY parallel micropositioning stage to compensate for the unmodeled hysteresis aiming at a sub-micron accuracy motion tracking control. The GSMC controller is designed with the consideration of all uncertainty bounds. In the controller implementation, a high-gain velocity observer is adopted to estimate the...
In this paper, an adaptive neural sliding mode control based on radial basis function (RBF) neural network (NN) is implemented on a piezo-driven XY parallel micro-positioning stage for a sub-micron accuracy motion tracking control. The controller is designed to map the relationship between the sliding surface variable and voltage applied to piezoelectric actuator (PZT). Hence, neither a hysteresis...
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