Chek Sing Teo

Discrete Composite Control of Piezoelectric Actuators for High-Speed and Precision Scanning

The scanning accuracy of piezoelectric mechanisms over broadband frequencies is limited due to inherent dynamic hysteresis. This phenomenon has been a key bottleneck to the use of piezoelectric mechanisms in fast and precision scanning applications. This paper presents a systematic model identification and composite control strategy without hysteresis measurement for such applications. First, least squares estimation using harmonic signals is applied to achieve the Preisach density function. Next, the hysteresis output is estimated, such that the non-hysteretic dynamics can be identified. The discrete composite control strategy is proposed with a feedforward-feedback structure. The feedforward controller is the primary component designed for the performance. The secondary proportional-integral (PI) feedback controller is employed to suppress disturbances for robustness. Finally, the identification and composite control strategy is implemented with a dSPACE 1104 board for a real piezoelectric actuator setup. The experimental results indicate that adequate scanning performance can be sustained at a rate higher than the first resonant frequency.

Development of an Approach Toward Comprehensive Identification of Hysteretic Dynamics in Piezoelectric Actuators

This paper presents a comprehensive approach for the identification of the hysteresis and coupled nonhysteretic dynamics of piezoelectric actuators over a broad range of frequencies. The approach leverages on the special characteristics and distinctions of the hysteretic and nonhysteretic components to identify them in sequence, efficiently. The nonhysteretic dynamics is identified using square wave input signals. The creep dynamics is identified using an input signal with a long period. Conversely, electric and vibration dynamics are identified using an input signal with a small period. Moreover, the drift due to the creep is eliminated by employing its model inversion. The Preisach hysteresis is identified with specially designed harmonic input signals and sampling rules, which overcome the persistent excitation problem of hysteresis identification and improve the computational efficiency. Simulation and experiments are conducted to validate the effectiveness of the identification approach.

Toward Comprehensive Modeling and Large-Angle Tracking Control of a Limited-Angle Torque Actuator With Cylindrical Halbach

The single-phase limited-angle torque (LAT) motor with cylindrical Halbach magnetic array provides a smaller form factor, lighter moving mass, and higher force throughput within ±60° angle range, compared with the three-phase permanent magnet synchronous motor. Due to the imperfect flux distribution within the air-gap of the Halbach array, as well as the inherent angular dependent characteristics, it is mainly used for point-to-point motion applications in prior literature. In this paper, we would like to deal with above issues, so that it can be extensively used for large-angle tracking applications. First, we derive the ideal model of this LAT actuator. Next, we propose to identify its nominal model parameters by the relay feedback with sufficiently small oscillations near the neutral position. Later, a robust output feedback control with high-gain observer is proposed to handle both model uncertainty and angular-dependent nonlinear current-torque relationship, so that the precision tracking of a defined smooth trajectory is achieved with only position sensing. The real-time experiment on a prototype validates the practical appeal of proposed methods.

A constrained linear quadratic optimization algorithm toward jerk-decoupling cartridge design

Abstract Linear direct feed drives are widely used in machine tools, but an abrupt counter force from the secondary part will induce the jerk to the metro frame contacted with the linear motor and cause the vibration of auxiliary devices on it. The jerk-decoupling cartridge (JDC) provides a buffer to reduce such an impact. Design target for such a system includes both the tracking error and the jerk induced to the metro frame. To achieve both targets systematically, this work presents an integrated approach to efficiently determine parameters in the JDC and the position controller of the feed drive. The problem is firstly formulated as a nonlinear constrained optimization problem, which is then converted to a series of projection gradient optimization problems and step searching problems, which are either convex or linear. Thus, fast convergence of parameters are achieved within first several iterations. Through a series of simulation, the effectiveness of proposed methodology is verified.

Composite jerk feedforward and disturbance observer for robust tracking of flexible systems

Abstract In this paper, a novel feedforward controller for flexible motion systems is proposed based on both the rigid-body mode and lump-sum of the flexible modes. It only requires the reference trajectory to be defined up to its jerk, and gives well-behaved high-pass feedforward sensitivity. For systems with severe low-frequency disturbance, an additional disturbance observer is introduced, using the same jerk feedforward as the inversion of the nominal model. Remarkably, with such proposed control scheme and novel loop-shaping criteria, the improvement of disturbance rejection and profile tracking does not result in obvious degrading of the noise attenuation.

Confocal and force probe imaging system for simultaneous three-dimensional optical and mechanical spectroscopic evaluation of biological samples

We present the design and operation of a novel instrument for the simultaneous three-dimensional measurements of localized properties using optical and mechanical probes. In this instrument the mechanical and optical probes are stationary relative to the instrument frame while the specimen can be navigated in three-dimensional space in the probing field, translating over a range of 64.5 microm by 49.7 microm by 31.5 microm in each axis, respectively, at closed loop speeds of 10 Hz. A large aperture is provided in the center of the moving platform so that an optical lens can image the specimen from below. An additional z-direction translator has been integrated with this instrument to independently move a force probe that contacts the specimen from above with a translation range of 16 microm. Furthermore, there is an additional seven degrees of freedom providing adjustments to independently position and/or align the scanner and force probe relative to the optical imaging lens. Initial results of both optical and mechanical scans demonstrate 6 nm localization from single molecule fluorescence measurements, as well as single pair fluorescence energy transfer measurements indicating molecular separations of about 2 nm.

Low-order feedforward control schemes for flexible motion systems with different rigid-body damping

Lightweight stages are becoming the new trend in industrial high performance motion systems. They are generally less stiff than the traditional designs and more pronounced resonant dynamics usually appear in low frequency region. Control design methods to deal with these flexible modes effectively are known as the Beyond Rigid Body (BRB) control. In high performance tracking control, such as wafer scanning and lithography, feedforward control is widely used to improve their tracking accuracy. In this paper, novel feedforward controllers are proposed to reduce tracking error of light-weight motion systems with presence of different rigid-body damping. Their performances are then compared with the traditional rigid body feedforward controller as well as the recently proposed snap feedforward controller to show the advantages.

Data-Based Tuning of Reduced-Order Inverse Model in Both Disturbance Observer and Feedforward With Application to Tray Indexing

Performance of traditional model-based control relies upon accurate modeling. In motion control of flexible systems, it is desirable to use the reduced-order model for ease of trajectory planning and pole placement, but its performance is constrained by modeling inaccuracies due to the existence of friction and multiple flexible modes. To improve the tracking performance, we have developed a data-based method for iterative tuning of the parameters in the reduced-order inverse model within a three-degree-of-freedom composite control structure. The proposed method solely makes use of the input-output data obtained during closed-loop experiments to fine-tune the inverse system model, and accurate system modeling is not required. Unbiasedness of the cost function gradient estimation is proven under reasonable assumptions of stochastic properties of the perturbations. Simulation and experiments are conducted to further illustrate the proposed method and show its practical appeals in industrial applications.

Dynamic modeling and adaptive control of a multi-axial gantry stage

This paper addresses the physical dynamic modeling and simulates the adaptive control of a precision gantry stage. The stage is posed as a three-degree-of-freedom system, based on a patented air-bearing stage provided by the Singapore Institute of Manufacturing Technology. Using this stage as the target model, a mathematical model is then built using the Lagrangian equation. An adaptive control method is formulated for the positioning of the stage, with minimal a priori information assumed of the model. A stability analysis is given for the proposed control scheme. Simulation results are also documented to illustrate the feasibility of the scheme. Future direction is to implement the adaptive controller to the actual gantry stage.

Neural network-based correction and interpolation of encoder signals for precision motion control

Precision control is the core of many applications in the industry, particularly robotics and drive control. To achieve it, precise measurement of the signals generated by incremental encoder sensors is essential. High precision and resolution motion control relies critically on the precision and resolution achievable from the encoders. In this paper, a dynamic neural network-based approach for the correction and interpolation of quadrature encoder signals is developed. In this work, the radial basis functions (RBF) neural network is employed to carry out concurrently the correction and interpolation of encoder signals in realtime. The effectiveness of the proposed approach is verified in the simulation results provided.