96 A Survey of Iterative Learning Control Al earning-based method for high-performance tracking control

http://www.mate.tue.nl/mate/pdfs/11373.pdf

MIMO feed-forward design in wafer scanners using a gradient approximation-based algorithm

Iterative controller tuning is a method to fine-tune controllers in a repetitive process using only data collected in experiment runs. The controller parameters are chosen so as to minimize a certain cost function. The values of the parameters are updated iteratively based on tracking error in a gradient search. Iterative controller tuning is an advantageous method of controller tuning because no prior plant model is necessary. In this paper, we iteratively tune the feedforward controller of a wafer stage of a photolithography machine. A fixed-structure feedforward controller consisting of the inverted plant model was tuned. In addition, an additive feedforward term for compensation of nonlinear force ripple disturbance was tuned. The feedforward controller is tuned with the objective of minimizing a cost function that is a quadratic function of tracking error. Simulation and experimental results are presented which show that the iterative tuning method effectively reduced tracking error.

Iterative tuning of feedforward controller with force ripple compensation for wafer stage

Model-based spatial feedforward for over-actuated motion systems

The feedforward controller plays an important role in the achievement of high servo performance of wafer scanning. In this paper, a novel data-driven feedforward tuning method is developed in the presence of noise. Three distinguished features make it different from the existing methods: first, high extrapolation capability to tasks; second, low requirement on the system model; and especially, third, high noise tolerant capability. These superiorities are achieved by a high-order iterative feedforward tuning algorithm based on instrumental variables. It utilizes error data from all past iterations via an integrator in the learning law, yet without the need of the plant model or the sensitivity function. Furthermore, $H_2$ optimization with specified convergence speed constraint is proposed to design the learning gain. Connections and differences between the proposed algorithm and the existing ones are discussed. Experimental results validate the proposed method and confirm its effectiveness and superiority.

Data-Driven Iterative Feedforward Tuning for a Wafer Stage: A High-Order Approach Based on Instrumental Variables

The design of an efficiency optimal controller for the variator in a vehicular continuously variable transmission is studied. A conventional controller aims at tracking a prescribed reference for the transmission ratio and at preventing damage, but does not address efficiency. Sufficiently accurate models for the efficiency as function of the clamping forces are not available, whereas measurement of the efficiency requires extra sensors. In this brief, a controller is proposed that improves the efficiency without needing extra sensors. The maps between the clamping forces (input) and the efficiency or the speed ratio (output) are studied with test rig experiments. These maps exhibit a maximum, but the location of this maximum is uncertain. So, an extremum seeking controller is developed. This controller can adapt the input to maximize the output, without needing a model. Experiments show that this approach is feasible and that a conventional controller is outperformed. A robustness analysis for disturbances indicates that these are effectively handled.

Improving Continuously Variable Transmission Efficiency With Extremum Seeking Control

In this paper, the feedforward controller design problem for high-precision electromechanical servo systems that execute finite time tasks is addressed. The presented procedure combines the selection of the fixed structure of the feedforward controller and the optimization of the controller parameters on the basis of measurement data from iterative trials. A linear parameterization of the feedforward controller in a two-degree- of-freedom control architecture is chosen, which for a linear time-invariant (LTI) plant results in a feedforward controller that is applicable to a class of motion profiles as well as in a convex optimization problem with the objective function being a quadratic function of the tracking error. Optimization by iterative trials results in the controller parameter values that are optimal with respect to the actual plant, which leads to a high tracking performance. The use of iterative trials in general outperforms techniques that are based on a detailed a priori plant model only, whereas the fixed structure of the feedforward controller, i.e., the approximative inverse plant model, guarantees a high tracking performance for a class of motion profiles, unlike for example iterative learning control (ILC). Experimental results on a high-precision wafer stage illustrate the procedure.

http://www.mate.tue.nl/mate/pdfs/7506.pdf

Fixed Structure Feedforward Controller Tuning Exploiting Iterative Trials, Applied to a High-Precision Electromechanical Servo System

A pushbelt continuously variable transmission (CVT) is a stepless power transmission device with infinitely many transmission ratios within a certain range. This is enabled by the variator, which consists of a segmented steel V-belt that is clamped in between two pairs of conical sheaves, see Figure 1. High clamping forces are exerted by a hydraulic actuation system to prevent global slip of the belt at all times, which leads to increased hydraulic pump losses and increased friction losses.

/pdf/hydraulic-cvt-slip-control-new-challenges-3qo268p3y8.pdf

S. van der Meulen

Papers

Improving Continuously Variable Transmission Efficiency With Extremum Seeking Control

Fixed Structure Feedforward Controller Tuning Exploiting Iterative Trials, Applied to a High-Precision Electromechanical Servo System

Hydraulic CVT Slip Control: New Challenges