With regard to precision/ultra-precision motion systems, it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances. In this paper, to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control (ILC), a novel real-time iterative compensation (RIC) control framework is proposed for precision motion systems without changing the inner closed-loop controller. Specifically, the RIC method can be divided into two parts, i.e., accurate model prediction and real-time iterative compensation. An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times. In light of predicted errors, a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation. Both the prediction and compen-sation processes are finished in a real-time motion control sampling period. The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions. Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability, which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

Chuxiong Hu;Ran Zhou;Ze Wang;Yu Zhu;Masayoshi Tomizuka

State Key Laboratory of Tribology,Department of Mechanical Engineering,Tsinghua University,Beijing 100084;Beijing Key Laboratory of Precision/Ultra-Precision Manufacture Equipments and Control,Tsinghua University,Beijing 100084,China;Department of Mechanical Engineering,University of California,Berkeley,CA 94720-1740 USA

自动化学报（英文版）

[1]Chuxiong Hu;Ran Zhou;Ze Wang;Yu Zhu;Masayoshi Tomizuka-.Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems)[J].自动化学报（英文版）,2022(07):1218-1232

Mechatronic

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