Active Model-Based Hysteresis Compensation and Tracking Control of Pneumatic Artificial Muscle

The hysteretic nonlinearity of pneumatic artificial muscle (PAM) is the main factor that degrades its tracking accuracy. This paper proposes an efficient hysteresis compensation method based on the active modeling control (AMC). Firstly, the Bouc–Wen model is adopted as the reference model to describe the hysteresis of the PAM. Secondly, the modeling errors are introduced into the reference model, and the unscented Kalman filter is used to estimate the state of the system and the modeling errors. Finally, a hysteresis compensation strategy is designed based on AMC. The compensation performances of the nominal controller with without AMC were experimentally tested on a PAM. The experimental results show that the proposed controller is more robust when tracking different types of trajectories. In the transient, both the overshoot and oscillation can be successfully attenuated, and fast convergence is achieved. In the steady-state, the proposed controller is more robust against external disturbances and measurement noise. The proposed controller is effective and robust in hysteresis compensation, thus improving the tracking performance of the PAM.

A modified direct inverse Prandtl–Ishlinskii model based on two sets of operators for the piezoelectric actuator hysteresis compensation

Piezoelectric actuator (PEA) is widely applied in the field of micro/nano high precision positioning. However PEA has the phenomenon of hysteresis non-linearity between input voltage and output displacement, due to the natural property of piezoelectric materials. The PEA hysteresis can be compensated by hysteresis models, which makes the input voltage and output displacement more linearity. The research work on compensation of PEA hysteresis by using various hysteresis models has been being a hot topic. This paper presents a modified direct inverse rate-independent Prandtl–Ishlinskii (PI) (MDIPI) model for compensating the hysteresis of PEA. The proposed MDIPI model has two different sets of operators compared with classical PI (CPI) model having one set of operators. For the two sets operators in MDIPI model one is rate operators and the other is modified classical operators. By combining the two sets operators, the MDIPI model has the properties of the adaption and accuracy in hysteresis compensation. The MDIPI model can be used as feedforward controller to compensate different reference trajectories. Parameters of MDIPI model are calculated by matlab optimization tool box. The experiments of compensating the complex displacement trajectory and sinusoidal trajectory are validated on a platform of commercial PEA. The MDIPI model has achieved more accurate results than the Krasnosel’skii–Pokrovkii (KP), Preisach and CPI models. It is effective in improving the accuracy of PEA hysteresis compensation.

Hysteresis Compensation for a Piezoelectric Actuator of Active Helicopter Rotor Using Compound Control

Active rotor with trailing-edge flaps is a promising method to alleviate vibrations and noise level of helicopters. Hysteresis of the piezoelectric actuators used to drive the flaps can degrade the performance of an active rotor. In this study, bench-top tests are conducted to measure the nonlinear hysteresis of a double-acting piezoelectric actuator. Based on the experimental data, a rate-dependent hysteresis model is established by combining a Bouc–Wen model and a transfer function of a second order system. Good agreement is exhibited between the model outputs and the measured results for different frequencies. A compound control regime composed of a feedforward compensator and PID (Proportional–Integral–Derivative) feedback control is developed to suppress the hysteresis of this actuator. Bench-top test results demonstrate that this compound control regime is capable to suppress hysteresis at different frequencies from 10 Hz to 60 Hz, and errors between the desired actuator outputs and the measured outputs are reduced dramatically at different frequencies, revealing that this compound control regime has the potential to be implemented in an active helicopter rotor to suppress actuator hysteresis.

Precision open-loop control of piezoelectric actuator

Due to space constraints, some micro-assemblies and micro-operating systems cannot install sensors, so it is challenging to achieve closed-loop control. For this reason, a precision open-loop control strategy for piezoelectric actuators is proposed. Firstly, based on the PI model and the proposed threshold partition method, the hysteresis model of the piezoelectric actuator with rate-dependent and few operators is established. Then the hysteresis error of the piezoelectric actuator is compensated by the inverse model obtained. Secondly, the creep model of the logarithmic piezoelectric actuator with simple expression and few parameters is established. Then, a creep controller without demand inverse is designed to compensate for the creep error of the piezoelectric actuator. Finally, a ZVD (Zero Vibration Derivative) input shaping method with good robustness is given to eliminate the oscillation generated by the piezoelectric actuator under the action of the step signal. The experimental results show that the displacement error of piezoelectric actuator is reduced from −9.07 to 9.46 μm to −1.22 to 1.78 μm when the maximum displacement is 120 μm after hysteresis compensation; after creeping compensation, within the action time of the 1200 s, the displacement creep of the piezoelectric actuator was reduced from 5.5 μm before compensation to 0.3 μm; after the oscillation control, the displacement overshoot of the piezoelectric actuator is reduced to 0.6% of that before control.

Inversion-based Hysteresis Compensation Using Adaptive Conditional Servocompensator for Nanopositioning Systems

Nanopositioning stages are widely used in high-precision positioning applications. However, they suffer from an intrinsic hysteretic behavior, which deteriorates their tracking performance. This study proposes an adaptive conditional servocompensator (ACS) to compensate the effect of the hysteresis when tracking periodic references. The nanopositioning system is modeled as a linear system cascaded with hysteresis at the input side. The hysteresis is modeled with a Modified Prandtl-Ishlinskii (MPI) operator. With an approximate inverse MPI operator placed before the system hysteresis operator, the resulting system takes a semi-affine form. The design of the adaptive conditional servocompensator consists of two stages: firstly, we design a continuously-implemented sliding mode control (SMC) law. The hysteresis inversion error is treated as a matched disturbance and an analytical bound on the inversion error is used to minimize the conservativeness of the SMC design. The second part of the controller is the adaptive conditional servocompensator. Under mild assumptions, we establish the well-posedness and periodic stability of the closed-loop system. In particular, the solution of the closed-loop error system will converge exponentially to a unique periodic solution in the neighborhood of zero. The efficacy of the proposed controller is verified experimentally on a commercial nanopositioning device under different types of periodic reference inputs, via comparison with multiple inversion-based and inversion-free approaches.