Huifang Dou

High precision linear motor control via relay-tuning and iterative learning based on zero-phase filtering

In this paper, with a modest amount of modeling effort, a feedback-feedforward control structure is proposed for precision motion control of a permanent magnet linear motor for applications which are inherently repetitive in terms of the motion trajectories. First, a proportional-integral-derivative (PID) feedback controller is designed using an automatic relay tuning method. An iterative learning controller based on zero-phase filtering is applied as feedforward controller to the existing relay-tuned PID feedback controller to enhance the trajectory tracking performance by utilizing the experience gained from the repeated execution of the same operations. Experimental results are presented to demonstrate the practical appeal and effectiveness of the proposed scheme.

State-periodic adaptive compensation of cogging and Coulomb friction in permanent-magnet linear motors

This paper focuses on the state-periodic adaptive compensation of cogging and Coulomb friction for permanent-magnet linear motors (PMLMs) executing a task repeatedly. The cogging force is considered as a position-dependent disturbance and the Coulomb friction is non-Lipschitz at zero velocity. The key idea of our disturbance compensation method is to use past information for one trajectory period along the state axis to update the current adaptation law. The new method consists of three different steps: 1) in the first repetitive trajectory, an adaptive compensator is designed to guarantee the l/sub 2/-stability of the overall system; 2) from the second repetitive trajectory and onward, a trajectory-periodic adaptive compensator stabilizes the system; and 3) to make use of the stored past state-dependent cogging information, a search process is utilized for adapting the current cogging coefficient. We illustrate the validity of our state-periodic adaptive cogging and friction compensator by actual PMLM-model-based simulation.

Iterative learning control of permanent magnet linear motor with relay automatic tuning

Abstract In this paper, a feedforward–feedback control structure is proposed for precision motion control of a permanent magnet linear motor (PMLM) for applications which are inherently repetitive in terms of the motion trajectories. The control scheme utilises an efficient marriage of conventional PID feedback control and an intelligent feedforward control using an iterative learning control (ILC) algorithm. The PID feedback control stabilizes the PMLM system, while the ILC feedforward control enhances the trajectories tracking performance by capitalising on the experience gained from the repeated execution of the same operations. A relay automatic tuning method is developed and incorporated, so that an initial set of control settings may be automatically derived from a few cycles of self-induced controlled oscillations. This self-tuning feature enables the PMLM application system to be operated quickly near optimal conditions simply at a push-button efficiency. Extensive experimental results are presented to demonstrate the appeal and effectiveness of the proposed scheme.

Iterative learning feedback control of human limbs via functional electrical stimulation

Abstract A high-order iterative learning controller (ILC) is proposed for the tracking control of an electrically stimulated human limb that is repeatedly required to perform a given task. The limb is actuated by the muscles, which are out of the control of the central nerve systems (CNS), through functional electrical stimulation (FES) or functional neuromuscular stimulation (FNS). By using the proposed discrete-time high-order P-type ILC updating law and the PD-type feedback controller, it is shown that the proposed control strategy, which learns from repetitions, provides strong robustness in tracking control of the uncertain time-varying FES systems, which is essential for the adaptation and customization of FES applications. The effectiveness of the proposed control scheme is demonstrated by simulation results on a one-segment planar system. Some experimental results are also presented to validate the proposed control method.

A robust tuning method for fractional order PI controllers

Abstract The application of fractional controller attracts more attention in the recent years. In this paper, a new tuning method for PI α controller design is proposed for a class of unknown, stable, and minimum phase plants. We are able to design a PI α controller to ensure that the phase Bode plot is flat, i.e., the phase derivative w.r.t. the frequency is zero, at a given gain crossover frequency so that the closed-loop system is robust to gain variations and the step responses exhibit an iso-damping property. Several relay feedback tests can be used to identify the plant gain and phase at the given frequency in an iterative way. The identified plant gain and phase at the desired tangent frequency are used to estimate the derivatives of amplitude and phase of the plant with respect to frequency at the same frequency point by Bodes integral relationship. Then, these derivatives are used to design a PI α controller for slope adjustment of the Nyquist plot to achieve the robustness of the system to gain variations. No plant model is assumed during the PI α controller design. Only several relay tests are needed.

Coordinated motion control of moving gantry stages for precision applications based on an observer-augmented composite controller

High-precision operation in gantry systems is required to meet higher demands on positioning accuracy in a wide range of applications such as circuit assembly, precision metrology, and wafer stepping. In this paper, the experimental study of an observer-augmented composite control scheme for coordinated motion control of moving gantry stages for precision applications is presented. The scheme will be implemented and compared to other control schemes currently available for this purpose, including a master-slave and a set-point coordinated scheme. Experimental results will illustrate the enhanced performance of the fully coordinated control scheme with respect to tight trajectory tracking purposes.

Adaptive robust motion control for precise trajectory tracking applications

Abstract This paper presents a robust servo control method for high precision motion control using linear actuators. The controller consists of three components : a simple feedforward compensator, a PID feedback controller, and a RBF (radial-basis function) adaptive compensator, each to fulfill a specific objective. The first two control components can be directly tuned based on only an estimated dominant second-order linear model. The RBF compensator is self-tuning, and it will compensate for remaining uncertainties in the system, residual of the linear model. Rigid proofs are provided, guaranteeing the robust stability of the proposed controller. Experimental results confirm the much superior performance of the 3-tier composite control over a standard motion controller.

Robust higher order repetitive learning control algorithm for tracking control of delayed repetitive systems

A robust higher-order PID (proportional plus integral plus derivative)-type ILC (iterative learning control) algorithm is presented for tracking control of delayed nonlinear time-varying MIMO (multiple-input multiple-output) repetitive systems. A convergence proof is given in a more general case. When initial state bias exists, a repetitive ILC scheme (i.e. forward learning and backward learning) is proposed to make the algorithm more robust with respect to this bias. Simulation results indicate that the proposed method converges faster than previous methods. The effect of system delay (or even multidelays and time-varying delays) on the ILC convergence is very small. Examples are provided to demonstrate the efficiency of the proposed methods.<<ETX>>

Development of an integrated and open-architecture precision motion control system

Abstract In this paper, the development of an integrated and open-architecture precision motion control system is presented. The control system is generally applicable, but it is developed with a particular focus on direct drive servo systems based on linear motors. The overall control system is comprehensive, comprising of various selected control and instrumentation components, integrated within a configuration of hardware architecture centred around a dSPACE DS1004 DSP processor board. These components include a precision composite controller (comprising of feedforward and feedback control), a disturbance observer, an adaptive notch filter, and a geometrical error compensator. The hardware architecture, software development platform, user interface, and all constituent control components will be elaborated on in the paper.

Force ripple suppression in iron-core permanent magnet linear motors using an adaptive dither

This paper presents the design and realization of an adaptive dither to reduce the force ripple in an iron-core permanent magnet linear motor (PMLM). A composite control structure is used, consisting of three components: a simple feedforward component, a PID feedback component and an adaptive feedforward compensator (AFC). The first two components are designed based on a dominant linear model of the motor. The AFC generates a dither signal with the motivation to eliminate or suppress the inherent force ripple, thus facilitating smooth precise motion while uncompromising on the maximum force achievable. An analysis is given in the paper to show the parameter convergence. Computer simulations and real-time experimental results verify the effectiveness of the proposed scheme for high precision motion trajectory tracking using the PMLM.