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Proceedings of 1994 American Control Conference - ACC '94, 2005
Some new results in learning feedforward control are presented in this paper. The proposed procedures are applicable to processes with or without feedback control. Under the ideal situation, this discrete-time learning control (LC) scheme can perfect the task with one repeat. Convergence analyses are also included for noisy and imprecise learning.
K.M. Tao, R.L. Kosut, G. Aral
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Some new results in learning feedforward control are presented in this paper. The proposed procedures are applicable to processes with or without feedback control. Under the ideal situation, this discrete-time learning control (LC) scheme can perfect the task with one repeat. Convergence analyses are also included for noisy and imprecise learning.
K.M. Tao, R.L. Kosut, G. Aral
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IEEE Transactions on Industrial Informatics, 2019
Contouring motion control plays an important role in modern precision multiaxis motion systems. In order to enhance the coordination between each axis and promote contouring performance, many research works have been conducted that mainly focus on ...
Ze Wang, Chuxiong Hu, Y. Zhu
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Contouring motion control plays an important role in modern precision multiaxis motion systems. In order to enhance the coordination between each axis and promote contouring performance, many research works have been conducted that mainly focus on ...
Ze Wang, Chuxiong Hu, Y. Zhu
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Approximate feedforward control
2015 10th Asian Control Conference (ASCC), 2015Disturbances are inevitable in most control systems. They drive the systems away from their set points. It takes time for feedback control to reject them. The feedforward control offers great potentials for regulation performance if the disturbances are measurable.
null Xian Li +2 more
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Fuzzy feedforward and composite control
Transactions of the Institute of Measurement and Control, 1986The concept of fuzzy feedforward and composite control of complex, ill-defined, non-deterministic processes is offered. Fuzzy relational model of process suitable for feedforward control is developed and, using this model, the algorithms of the fuzzy feedforward and composite controls are derived.
Božičević, Juraj, Stipaničev, Darko
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IEEE transactions on industrial electronics (1982. Print), 2019
In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. Compared to iterative learning control (ILC), data-based fixed-structure feedforward control (DFFC) possesses robustness against ...
Min Li +4 more
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In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. Compared to iterative learning control (ILC), data-based fixed-structure feedforward control (DFFC) possesses robustness against ...
Min Li +4 more
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Feedforward Control With Disturbance Prediction for Linear Discrete-Time Systems
IEEE Transactions on Control Systems Technology, 2019A typical process control system, in most operations, works to regulate the output against the frequent and variable disturbances, while there is rarely a set-point change.
Xian Li +4 more
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IEEE/ASME transactions on mechatronics, 2019
A plant with unstable zeros is known to be difficult to be controlled, because of the initial undershoot of its step response and the unstable poles in its inversion system. There are two reasons why a plant has unstable zeros in the discrete-time domain:
W. Ohnishi, Thomas Beauduin, H. Fujimoto
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A plant with unstable zeros is known to be difficult to be controlled, because of the initial undershoot of its step response and the unstable poles in its inversion system. There are two reasons why a plant has unstable zeros in the discrete-time domain:
W. Ohnishi, Thomas Beauduin, H. Fujimoto
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2022 IEEE 61st Conference on Decision and Control (CDC), 2022
Model–based feedforward control improves tracking performance of motion systems if the model describing the inverse dynamics is of sufficient accuracy. Model sets, such as neural networks (NNs) and physics–guided neural networks (PGNNs) are typically used as flexible parametrizations that enable accurate identification of the inverse system dynamics ...
Bolderman, M. +2 more
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Model–based feedforward control improves tracking performance of motion systems if the model describing the inverse dynamics is of sufficient accuracy. Model sets, such as neural networks (NNs) and physics–guided neural networks (PGNNs) are typically used as flexible parametrizations that enable accurate identification of the inverse system dynamics ...
Bolderman, M. +2 more
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IEEE Journal of Emerging and Selected Topics in Power Electronics, 2018
Many power electronic systems require dual-active-bridge (DAB) converters with ultrafast dynamic response. This paper presents a load-feedforward control design for DAB converters with current-mode modulation, which can enhance the dynamic response to ...
Z. Shan +3 more
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Many power electronic systems require dual-active-bridge (DAB) converters with ultrafast dynamic response. This paper presents a load-feedforward control design for DAB converters with current-mode modulation, which can enhance the dynamic response to ...
Z. Shan +3 more
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Adaptive Feedforward Aircraft Control
AIAA Infotech@Aerospace 2010, 2010In this paper we present a feedforward adaptive control scheme with application to the control of a nonlinear aircraft model with uncertainty in the aerodynamic moment coefficients. The feedforward controller is represented by a basis function network. The learning algorithm consists of a gradient based rule plus e-modification.
Abraham Ishihara +4 more
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