Jerk derivative feedforward control for motion systems

Boerlage, Mlg Matthijs; Tousain, R.L.; Steinbuch, M Maarten

doi:10.23919/acc.2004.1384080

Cited by 51 publications

(28 citation statements)

References 13 publications

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“…In this paper, it is shown that these deficiencies can be removed by connecting iterative feedforward tuning to system identification, and exploit concepts from closed-loop system identification in iterative feedforward tuning. In fact, in contrast to pre-existing procedures in Van der Meulen et al (2008), Boeren, Bruijnen et al (2014) and Heertjes et al (2010), the proposed procedure closely resembles manual feedforward tuning procedures for motion systems, see, e.g., Boerlage, Tousain, and Steinbuch (2004). This immediately confirms the practical relevance of the proposed approach for industrial motion systems.…”

Section: Introductionsupporting

confidence: 52%

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

Boeren

Oomen

Steinbuch

2015

Control Engineering Practice

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a b s t r a c tFeedforward control can significantly enhance the performance of motion systems through compensation of known disturbances. This paper aims to develop a new procedure to tune a feedforward controller based on measured data obtained in finite time tasks. Hereto, a suitable feedforward parametrization is introduced that provides good extrapolation properties for a class of reference signals. Next, connections with closed-loop system identification are established. In particular, instrumental variables, which have been proven very useful in closed-loop system identification, are selected to tune the feedforward controller. These instrumental variables closely resemble traditional engineering tuning practice. In contrast to pre-existing approaches, the feedforward controller can be updated after each task, irrespective of noise acting on the system. Experimental results confirm the practical relevance of the proposed method.

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Section: Introductionsupporting

confidence: 52%

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

Boeren

Oomen

Steinbuch

2015

Control Engineering Practice

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“…So it is quite common in linear motor control to use PID control. But general PID controller has the problems of poor position tracking accuracy and relative long settling time [2] [3] . The "Acceleration feedforward plus PID" method for air-guiding linear motor is proposed in this paper which makes full use of the merits of feedforward control to solve the above problems properly.…”

Section: Introductionmentioning

confidence: 99%

The Study of Feedforward Control Techniques of Linear Motor Guided by Air-bearing

Jin

Zhou

2012

2012 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring

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A combined "acceleration feedforward plus PID "control method is introduced to control the linear motor guided by air-bearing. The key technique of feedforward control system--obtaining the exact feedforward coefficient is proposed with which high positioning accuracy and high moving speed are achieved. The feedforward control method is described in detail. The experimental results are provided in the end.

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“…The structure of the feed-forward control can also be applied in the motion planning algorithm, where it maintains the characteristics such as optimizing time, reliability and precision. For the other implementation issues, authors [15,16] suggested a high order feed-forward planning strategy resulting in a significant performance improvement. The details of the fourth-order trajectory planning algorithm proved a practical, reliable and accurate outcome.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Fuzzy Self-Tuning PID and Feed-Forward Design for High-Performance Motion Control System

Ngo¹,

Kim

2014

International Journal of Fuzzy Logic and Intelligent Systems

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The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

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Jerk derivative feedforward control for motion systems

Cited by 51 publications

References 13 publications

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

The Study of Feedforward Control Techniques of Linear Motor Guided by Air-bearing

Implementation of Fuzzy Self-Tuning PID and Feed-Forward Design for High-Performance Motion Control System

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