Quantitative feedback–feedforward control for model matching and disturbance rejection

Elso, Jorge; Gil-Martínez, Montserrat; García-Sanz, Mario

doi:10.1049/iet-cta.2012.0596

Cited by 29 publications

(37 citation statements)

References 16 publications

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“…This scheme is very popular in process control literature [10][11][12], where the feedforward element is often tuned using inversion techniques. However, it is shown in [13] that a QFT solution of this 2DOF problem yields less conservative designs than inversion-based techniques. Rather than beginning with the feedforward design, QFT firstly deals with the feedback controller, limiting its action to the minimum required for a subsequent successful feedforward design on the Nichols plot.…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of this article is to extend the results of [13] to the MIMO case. In other words, it aims to introduce a QFT solution for the multivariable disturbance rejection problem when measurements of the disturbances are available.…”

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confidence: 99%

“…But apart from being slightly more intuitive, a model matching solution is no better than a tracking error one. Hence, the real contribution of [13] is the solution to a problem never considered before in the QFT literature: the presence of measurable disturbances. Up to that point, QFT had solved disturbance rejection problems only by feedback corrective actions, ignoring that sometimes disturbances are predictable or measurable, and that in those cases, some anticipative action helps to reduce the demand for feedback.…”

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confidence: 99%

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Quantitative feedback control for multivariable model matching and disturbance rejection

Elso

Gil-Martínez

García-Sanz

2016

Int. J. Robust. Nonlinear Control

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SUMMARYThis article extends two recent contributions in the field of quantitative feedback theory to the multivariable case. They concern the model matching and the measured disturbance rejection problems. The model matching problem is a tracking control problem with specifications given as acceptable deviations from an ideal response. The measured disturbance rejection problem balances feedback and feedforward actions to reject disturbances. Both perspectives present advantages over classical quantitative feedback theory techniques in certain situations. This paper develops the necessary tools to solve both control problems in the case of multi-input multi-output plants. In particular, it shows how to derive nonconservative controller bounds for each of the single-input single-output control problems in which the overall multivariable problem is divided. The result is a systematic controller design methodology for multi-input multi-output plants with structured uncertainty. The application of the technique to the well-known quadruple-tank process illustrates the benefits of the method.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Quantitative feedback control for multivariable model matching and disturbance rejection

Elso

Gil-Martínez

García-Sanz

2016

Int. J. Robust. Nonlinear Control

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“…With the road friction coefficient known, the feedforward and feedback methods can be combined for a better performance with both a fast response and good stability. 23 In this paper, a robust and effective tyre-road friction estimation algorithm for the traction control system is proposed, and a coordinative control method is designed for straight acceleration. For the requirements of different driving conditions, a sliding-mode observer and a state-based calculator are designed for estimation of the tyre forces.…”

Section: Introductionmentioning

confidence: 99%

Coordinative traction control of vehicles based on identification of the tyre–road friction coefficient

Zhao

Zhang

Zhu

2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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Traction control, which can be performed by different types of chassis control system, plays an important role in vehicle motion control. Since the propulsive force is actually produced by the friction between the tyre and road, information on the tyre-road friction is crucial for traction control. In this paper, a robust and effective tyre-road friction coefficient identification algorithm for straight acceleration is proposed, and a coordinative traction control method is designed by integrated usage of gear shifting control, engine control and braking control. For different driving conditions, the tyre forces were observed by a sliding-mode observer or calculated from the states of the vehicle directly, and the tyre-road friction coefficients were estimated by the recursive least-squares method or calculated from the linear characteristics between the friction coefficient and the slip ratio consequently. Based on the estimated tyre-road information, a practical and systematic coordinative traction control algorithm was designed to integrate shifting control, engine torque control and braking pressure control. Finally, the proposed methods are verified by both simulations and road tests. The results show that the estimation algorithms can identify the variation in the road conditions with considerable accuracy and response speed, and the controller successfully adjusted the slip ratios of the driving wheels in the stable region with good performances on different types of road.

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“…The MPC feedback and feedforward co-design procedure results in a tradeoff, where the controller tuning procedure is carried out taking into account the most important aspects. There exist several MPC formulations that can be used for disturbance compensation analysis providing the specific methodology in accordance with the analyzed features [17,22,23]. In [3,22,24], it was shown that the optimal MPC controller setup for disturbance attenuation results in high bandwidths in the feedback loop, and it is necessary to compensate this issue.…”

Section: Introductionmentioning

confidence: 99%

Measurable Disturbances Compensation: Analysis and Tuning of Feedforward Techniques for Dead-Time Processes

et al. 2016

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Abstract:In this paper, measurable disturbance compensation techniques are analyzed, focusing the problem on the input-output and disturbance-output time delays. The feedforward compensation method is evaluated for the common structures that appear between the disturbance and process dynamics. Due to the presence of time delays, the study includes causality and instability phenomena that can arise when a classical approach for disturbance compensation is used. Different feedforward configurations are analyzed for two feedback control techniques, PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control) that are widely used for industrial process-control applications. The specific tuning methodology for the analyzed process structure is used to obtain improved disturbance rejection performance regarding classical approaches. The evaluation of the introduced disturbance rejection schemes is performed through simulation, considering process constraints in order to highlight the advantages and drawbacks in common scenarios. The performance of the analyzed structure is expressed with different indexes that allow us direct comparisons. The obtained results show that the proper design and tuning of the feedforward action helps to significantly improve the overall control performance in process control tasks.

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Quantitative feedback–feedforward control for model matching and disturbance rejection

Cited by 29 publications

References 16 publications

Quantitative feedback control for multivariable model matching and disturbance rejection

Quantitative feedback control for multivariable model matching and disturbance rejection

Coordinative traction control of vehicles based on identification of the tyre–road friction coefficient

Measurable Disturbances Compensation: Analysis and Tuning of Feedforward Techniques for Dead-Time Processes

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