Disturbance Rejection Control For Nano Motion Stages With Measurement Delays

Nano motion systems are widely employed in ultra-precision technology fields such as microscopic scanning imaging,semiconductor preparation,and information storage because of their high accuracy and fast response performances,and are the core components of frontier equipment in these fields.However,increasingly complex manipulation tasks such as multi-axis precision coordination and high dynamic nano motion make such systems vulnerable to external perturbations and load variations.Furthermore,the measurement time delay problem to achieve sub-nanometer resolution sensing deteriorates the control performances as well.To address the above problems,this study explores the disturbance rejection control methods for piezoelectric nano-positioning stages with measurement delays on the basis of establishing a comprehensive dynamics model of the nano-servo stage by considering the complex characteristics such as the hysteresis nonlinearity of piezoelectric actuators and sensor delays to suppress the effects from multi-source perturbations of model uncertainties and external disturbances etc.(1)An active damping algorithm based on the Smith predictor compensation is proposed.Considering the complex characteristics of underdamped dynamics and sensor delays,he dynamic model of the nano-motion servo system is established firstly.The Smith predictor structure which can eliminate the influence of delay on the system control study is integrated with the damping control structure based on the positive velocity and position feedback,so as to achieve high-bandwidth loop shaping of the sensitivity function.(2)The disturbance observer control with a dual-observer structure is presented.Consider the sensor caused delays into design.The frequency information of the unknown periodic disturbance is extracted and estimated by designing an auxiliary observer and a key parameter observer,then compensating by a disturbance observer.After that,the system is stabilized by the feedback controller with a derived stability condition by the conducted Lyapunov-Krasovskii function.The performance of unknown disturbances attenuation is finally assured.(3)A data-driven intelligent disturbance observer algorithm is proposed.In order to compensate the effects of modeling inaccuracies on the control performances of disturbance observer,the disturbance observer control is combined with iterative feedback tuning theory.By designing the target performance function and the corresponding experimental procedure,the parameters of the controller are iteratively optimized using the obtained input-output data,realizing the model-free disturbances attenuation specifications.