Anti-Windup Using Switch for SISO System

Kosaka, Manabu; Uda, Hiroshi

doi:10.1260/026309207783700439

Cited by 7 publications

(7 citation statements)

References 12 publications

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“…where T p is the predicted temperature. Performance and stability analysis of (2) can be extended to (9), and the effect of dead-time is compensated if T d (t + θ) and e p are known. With the sampling time of t s = 0.1 s, the order of 1 is considered for both temperature and control input…”

Section: Predictive Approach For Feedback Control and Final Control Smentioning

confidence: 99%

“…This function can be estimated by an artificial neural network [30]. Considering (7)(8)(9)(10)(11) and the concept of dead-time…”

Section: Predictive Approach For Feedback Control and Final Control Smentioning

confidence: 99%

“…In other cases, the reference or setpoint is the input signal to the feedforward controller; this area of feedforward-feedback control system design lacks a general well-established methodology and is still subject to emerging ideas. In this area, the most popular feedforward control laws are the inverse models of the systems [2,6,[9][10][11]14], which are not always available, and artificial neural networks have also been used to generate the feedforward control command [5,17]. In 2009, the authors of this paper introduced the concepts of control equilibrium point and a steady state control law used as the feedforward controller [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Feedback‐feedforward control systems have many applications including in power systems , medical engineering , aircraft/helicopter control , vibration and noise control , manufacturing and temperature control of different processes . A variety of feedback controllers have been used in these systems such as PID , PD , state vector feedback , adaptive , iterative learning , and predictive , as well as nonlinear controllers designed by feedback linearization , optimal tracking control , and fuzzy logic .…”

Section: Introductionmentioning

confidence: 99%

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Neuro‐Predictive Control of an Infrared Dryer with a Feedforward‐Feedback Approach

Mohammadzaheri¹,

Chen²,

Mirsepahi³

et al. 2014

Asian Journal of Control

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In this research, a hybrid control system is proposed to address the temperature control of an infrared dryer. The control system includes a feedback-predictive controller and a neural network steady state control law. The feedback-predictive controller outputs the amplified value of the predicted error as the transient control command. The predictive model was employed to suppress the undesirable effect of the dead-time of the system. A multilayer perceptron was designed and tested based on a control equilibrium point and steady state control to be used as a feedforward controller. The stability of the control system in a continuous domain was proved with no limit on the amplification gain of the predictive-feedback controller. In other words, there is no concern about losing stability with accelerating convergence towards the reference. The entire control system was constructed in Simulink and compiled to a C code and applied on the experimental setup. Experimental results are outstanding in comparison with the results of an interactively tuned IMC-based PID controller.

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Section: Predictive Approach For Feedback Control and Final Control Smentioning

confidence: 99%

“…This function can be estimated by an artificial neural network [30]. Considering (7)(8)(9)(10)(11) and the concept of dead-time…”

Section: Predictive Approach For Feedback Control and Final Control Smentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Neuro‐Predictive Control of an Infrared Dryer with a Feedforward‐Feedback Approach

Mohammadzaheri¹,

Chen²,

Mirsepahi³

et al. 2014

Asian Journal of Control

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“…The deterioration can be reduced by some methods if the disturbance is not periodic. [3]- [6] The control performance of vibration suppression control systems is also deteriorated when the input is saturated. However, there is no report about methods to reduce the deterioration.…”

Section: Introductionmentioning

confidence: 99%

Vibration Suppression Control against Periodic Disturbances for Systems with Input Saturation

Kosaka¹

2008

Journal of Low Frequency Noise, Vibration and Active Control

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Compressors, pumps etc often generate noise and vibration due to periodic disturbances. It is known that vibration suppressing systems such as repetitive control are effective in suppressing periodic disturbances. However, there is no report about methods that can make control performance deterioration as small as possible when the control inputs of the vibration suppression system are saturated. This paper develops a disturbance observer that is effectively suppressing periodic disturbances, and proposes a method that can make control performance deterioration minimal even if the control inputs are saturated. First, the proposed system estimates disturbances using the disturbance observer. Next the estimated disturbances are passed into a filter of unity gain and zero phase change at the disturbance's frequencies, and are added into the control input in order to cancel the periodic disturbance. Some motor system simulations show that the phase of the estimated disturbances corresponds to that of the periodic disturbances so that the method can make control performance deterioration minimal. The method is appropriate to rotational machine systems such as compressors and pumps in which vibration and noise should be avoided.

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