A robust feedback linearization force control of a pneumatic actuator

Khayati, Karim; Bigras, Pascal; Dessaint, L.-A.

doi:10.1109/icsmc.2004.1401358

Cited by 12 publications

(12 citation statements)

References 14 publications

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“…However, it is very sensitive to environmental impedance variations and external disturbances [10], [11]. Conventionally, external disturbances are canceled by using model-based control methods such as feedback lin- earization, and a force control feedback loop is implemented by estimating the environmental impedance to suppress the effects of environmental impedance variations [12]. However, it is obvious that the modeling errors of external disturbances degrade the performance of an explicit force control system.…”

Section: Introductionmentioning

confidence: 99%

On the Explicit Robust Force Control via Disturbance Observer

Sarıyıldız

Ohnishi

2015

IEEE Trans. Ind. Electron.

103

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This paper analyzes the robustness and stability of disturbance observer (DOb)-based explicit force control systems. Conventional analysis methods, which only consider ideal robustness, are impractical due to the design constraints of a DOb, e.g., bandwidth limitations. This paper shows that not only the stability but also the robustness of a DOb-based explicit force control system changes by environmental impedance variations. The robustness of a DOb-based explicit force control system is clarified by deriving new sensitivity functions. Implicit and explicit environmental impedance estimation methods are considered by analyzing the dynamics of a force sensor and a reaction force observer (RFOb), respectively. It is shown that the stability and performance of an explicit force control system can be improved by using an explicit environmental impedance estimation method, i.e., an RFOb, intrinsically. However, an RFOb is more sensitive than a force sensor to external disturbances, and the stability of the explicit force control system drastically changes by the design parameters of a DOb and an RFOb. Force-sensorand RFOb-based explicit robust force control systems are compared in terms of stability, robustness, and performance in detail. The validity of the proposals is verified by simulation and experimental results.

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Section: Introductionmentioning

confidence: 99%

On the Explicit Robust Force Control via Disturbance Observer

Sarıyıldız

Ohnishi

2015

IEEE Trans. Ind. Electron.

103

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“…By setting uncertain bounds in the model and adjusting appropriate weightings, this technique offers an acceptable trade-off between performance and robustness, which is suitable for servo design of uncertain and complex pneumatic systems. [7][8][9][10][11][12][13][14] A nominal plant model is mandatory in the H N control design process and can be obtained by performing standard system identification techniques. 14,16 The nonlinearities and unmodeled dynamics can be simply treated as model uncertainties to formulate robust control problems.…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies regarding robust control of pneumatic actuating systems can be found in three primary groups: adaptive robust control, 1,2 sliding mode control, 3–6 and H ∞ control-related techniques. 7–14 To perform state feedback control based on a limited output measurement, deriving an accurate mathematical model or adding extra sensors is necessary for the first two methods. However, because air compressibility and thermal influences in parameters change, for implementation, building a perfect model to perform such model-based design is difficult.…”

Section: Introductionmentioning

confidence: 99%

Robust µ control and repetitive control for precision motion control of a pneumatic actuating table

Lin

Hsu

2015

Proceedings of the Institution of Mechanical Engineers, Part I:

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Because of uncertain and time-varying parameters influenced by air pressure and thermal parameters, applying H N robust control techniques to a pneumatic servo design has proven to be an efficient control strategy over the past few decades. However, because this method is a worst-case design that must yield robustness under given uncertainties, the inevitable trade-off may be too conservative and thus deteriorates its motion control performance. This study presents a robust m control and repetitive control method for attaining precise dynamic tracking control of a pneumatic actuating table. The applied hybrid control structure consists of two feedback controllers. The first is a repetitive controller used to improve periodic tracking performance, and the second is a m controller used to manage the dominant nonlinearities and uncertainties in pneumatic servo systems. This study presents an independent design of two controllers and takes advantage of the synergetic effect that results in an enhanced robust repetitive control design. In this study, a weighted average method is applied to determine optimal performance weights between these two control actions without violating robust stability. The experimental results on tracking dynamic motion profiles at perturbed operating regions for a heavy-duty pneumatic actuating table demonstrate the effectiveness of the proposed control method.

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“…[8][9][10][11] However, the robustness of the method cannot be guaranteed in the presence of parameter uncertainty or un-modeled dynamics. Theoretically, the exact model of the nonlinear system is unavailable in performing feedback linearization.…”

Section: Introductionmentioning

confidence: 99%

Feedback linearization-based self-tuning fuzzy proportional integral derivative control for atmospheric pressure simulator

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part I:

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A new robust nonlinear controller is proposed to improve the performance of the atmospheric pressure simulator that has some special characteristics such as asymmetry and nonlinearity. The three major components in such systems, the chamber, the servo valve and the vacuum pump, are studied to develop a full nonlinear model which encompasses all the major nonlinearities. Based on the model expressed in the controllability canonical form, a feedback linearization controller is developed to handle the strong asymmetry and nonlinearity of the atmospheric pressure simulator. Considering the parametric uncertainties and un-modeled dynamics existing in the atmospheric pressure simulator, a self-tuning fuzzy proportional integral derivative controller integrating with feedback linearization is introduced to improve the performance of the atmospheric pressure simulator at high-altitude simulations. Simulations and experiments indicate that the proposed controller can effectively raise the dynamic response performance, and in the meantime stability can be ensured.

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A robust feedback linearization force control of a pneumatic actuator

Cited by 12 publications

References 14 publications

On the Explicit Robust Force Control via Disturbance Observer

On the Explicit Robust Force Control via Disturbance Observer

Robust µ control and repetitive control for precision motion control of a pneumatic actuating table

Feedback linearization-based self-tuning fuzzy proportional integral derivative control for atmospheric pressure simulator

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