Repetitive control system: a new type servo system for periodic exogenous signals

Hara, Shinji; Yamämoto, Yasushi; Omata, Teppei; Nakano, Michio

doi:10.1109/9.1274

Cited by 1,255 publications

(691 citation statements)

References 21 publications

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“…rc was developed as a way to cancel periodic disturbances and/or tracking periodic reference trajectories in a continuous system, whereas ilc emerged as means to achieve run-to-run improvements in robotics and servomechanical systems. In the development of the rc methods, the internal model principle has played a major role (Hara et al, 1988), while ilc designs have mostly followed the direction of successive model inversion (Moore, 1998). In fact, both control concepts share the same basic principles and underlying issues (Longman, 1997).…”

Section: Introductionmentioning

confidence: 99%

Iterative nonlinear model predictive control. Stability, robustness and applications

Cueli

Bordons

2008

Control Engineering Practice

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This paper describes the control of a batch pH reactor by a nonlinear predictive controller that improves performance by using data of past batches. The control strategy combines the feedback features of a nonlinear predictive controller with the learning capabilities of run-to-run control. The inclusion of real-time data collected during the on-going batch run in addition to those from the past runs make the control strategy capable not only of eliminating repeated errors but also of responding to new disturbances that occur during the run. The paper uses these ideas to devise an integrated controller that increases the capabilities of Nonlinear Model Predictive Control (nmpc) with batch-wise learning. This controller tries to improve existing strategies by the use of a nonlinear controller devised along the last-run trajectory as well as by the inclusion of filters. A comparison with a similar controller based upon a linear model is performed. Simulation results are presented in order to illustrate performance improvements that can be achieved by the new method over the conventional iterative controllers. Although the controller is designed for discrete-time systems, it can be applied to stable continuous plants after discretization.

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Section: Introductionmentioning

confidence: 99%

Iterative nonlinear model predictive control. Stability, robustness and applications

Cueli

Bordons

2008

Control Engineering Practice

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“…Here e(t) [= r(t) − y(t)] is the tracking error between the reference input and the output. As explained by Hara et al (1988), if the original closed-loop system without the delay line is stable and if…”

Section: Problem Descriptionmentioning

confidence: 99%

“…The resulting system is called a modified RCS (MRCS, Fig. 1) (Hara et al, 1988). In an MRCS, the low-pass filter relaxes the stability condition, but degrades * Corresponding author the tracking precision for signals in the high-frequency band.…”

Section: Introductionmentioning

confidence: 99%

Robust aperiodic-disturbance rejection in an uncertain modified repetitive-control system

Zhou

She

et al. 2016

International Journal of Applied Mathematics and Computer Science

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This paper concerns the problem of designing an EID-based robust output-feedback modified repetitive-control system (ROFMRCS) that provides satisfactory aperiodic-disturbance rejection performance for a class of plants with time-varying structured uncertainties. An equivalent-input-disturbance (EID) estimator is added to the ROFMRCS that estimates the influences of all types of disturbances and compensates them. A continuous-discrete two-dimensional model is built to describe the EID-based ROFMRCS that accurately presents the features of repetitive control, thereby enabling the control and learning actions to be preferentially adjusted. A robust stability condition for the closed-loop system is given in terms of a linear matrix inequality. It yields the parameters of the repetitive controller, the output-feedback controller, and the EID-estimator. Finally, a numerical example demonstrates the validity of the method.

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“…An alternative approach is presented in Section 3.2. In this section is described that, since the harmonics in the input signal can be treated as periodic disturbances and since their period-time is exactly known, significant rejection is possible using repetitive control [Hara, Yamamoto, Omata, & Nakano, 1988, Tomizuka, Tsao, & Chew, 1988, Yau, & Tsai, 1999. Both approaches will be demonstrated with a simulation in order to objectively evaluate their effectiveness under well controlled circumstances.…”

Section: Likementioning

confidence: 99%

Measuring the higher order sinusoidal input describing functions of a non-linear plant operating in feedback

Nuij

Steinbuch

Bosgra

2008

Control Engineering Practice

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In this paper two measuring techniques are presented for measuring the Higher Order Sinusoidal Input Describing Functions (HOSIDF) of a non-linear plant operating in feedback. The HOSIDF relate the magnitude and phase of the harmonics of the periodic response of a non-linear system to the magnitude and phase of the sinusoidal excitation. In a controlled system the harmonics generated by the non-linear system will be fed back to the input changing the sinusoidal excitation into a harmonic excitation. The first method applies linear techniques to compensate the bias caused by the harmonic components in the excitation signal. The second method uses a modified repetitive control scheme to suppress the harmonic components in the excitation signal. The effectiveness of both methods is tested in simulations of a mass subjected to Coulomb friction, Stribeck-effect and hysteresis in the pre-sliding regime. The friction forces are modeled with the modified Leuven friction model. The results are compared with the HOSIDF simulated under open loop condition. Both methods prove able to produce reliable results.

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Repetitive control system: a new type servo system for periodic exogenous signals

Cited by 1,255 publications

References 21 publications

Iterative nonlinear model predictive control. Stability, robustness and applications

Iterative nonlinear model predictive control. Stability, robustness and applications

Robust aperiodic-disturbance rejection in an uncertain modified repetitive-control system

Measuring the higher order sinusoidal input describing functions of a non-linear plant operating in feedback

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