Optimal Design of a Fractional-Order Proportional-Integer-Differential Controller for a Pneumatic Position Servo System

Ren, Hai‐Peng; Fan, Jun-Tao; Kaynak, Okyay

doi:10.1109/tie.2018.2870412

Cited by 82 publications

(57 citation statements)

References 29 publications

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“…On the other hand, fractional-order control theories and applications of traditional integer-order and fractional-order systems have attracted increasing attention over the past two decades [24]. The fractional-order PI/PID control algorithm has been considered as one of the most widely and successfully used methods in complex systems, such as servo systems [25,26], a nonlinear vertical tank system [27], electric balance vehicle system [28], an induction motor drive system [29], permanent magnetic synchronous generator [30], automatic voltage regulator systems [31], single-area delayed power systems [32], and multi-area interconnected power systems [33]. One particular concern is the fractional-order frequency control of an isolated microgrid.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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Optimal frequency control of an islanded microgrid has been a challenging issue in the research field of microgrids. Recently, fractional-order calculus theory and some related control methods have attempted to handle this issue. In this paper, a novel fractional-order model predictive control (FOMPC) method is proposed to achieve the optimal frequency control of an islanded microgrid by introducing a fractional-order integral cost function into model predictive control (MPC) algorithm. Firstly, a discrete state-space model is derived for the optimal frequency control problem of an islanded microgrid. Afterward, a fractional-order integral cost function is designed to guide the FOMPC algorithm to obtain optimal control law by borrowing the Grünwald-Letnikov (GL) definition of fractional order calculus. Six simulation studies have been carried out to illustrate the superiority of FOMPC to conventional MPC under dynamical load disturbances, perturbed system parameters and random dynamical power fluctuation of wind turbines.

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Section: Introductionmentioning

confidence: 99%

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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“…Fundamentally, this pneumatic system has complicated over some nonlinearity factors due to the inherent problems associated with its natural features. Recently, many studies in this area have been emphasizing on the development of various model-free control approaches to cope with precision in pneumatic positioning with minor computational effort in real-time implementation such as PID-based control (Lai et al 2012;Sy Salim 2012;Salim et al 2013;Syed Salim et al 2014;Saleem et al 2015;Ren et al 2019a), fuzzy logic control (FLC) (Najjari et al 2014; Soares dos Santos and Ferreira 2014; Azahar et al 2019), and even trained neural network (NN)-based control (Dehghan and Surgenor 2013;Abu Mallouh 2019). Model-free control system approach relies on the input-output behavior of the plant without any uncertain parameter as compared to the model-based control almost completely depending on overall plant information.…”

Section: Introductionmentioning

confidence: 99%

Cascade Control Strategy on Servo Pneumatic System with Fuzzy Self-Adaptive System

Irawan

Azahar

2020

J Control Autom Electr Syst

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Servo pneumatic position control has gained considerable attention due to its superiority in improving the precision of automation and mechatronic systems. This paper presents the proposed cascaded fuzzy self-adaptive with proportional, integral, and derivative (CFSAPID) control strategy in providing an accurate rod-piston displacement as desired input with stable pressure in chambers. Unlike the conventional cascade strategy, the control law of proposed CFSAPID was designed based on the Mamdani-type fuzzy approach as a dynamic tuner to each stage in the proportional, integral, and derivative (PID) controller that deals with the nonlinearity of servo pneumatics adequately. The bounder sector zone of Mamdani-type fuzzy was determined based on position and velocity states on servo pneumatic rod-piston, and the parameter was constructed to obtain the optimum gain parameters of PID in each stage. The proposed CFSAPID was verified using a pneumatic proportional valve with a double-acting cylinder dynamic model plant. Simulation and analyses were emphasized on steady-state error, difference in pressures of pneumatic cylinder's chambers, hysteresis effect, tuning parameters convergence, performance criteria, and performance indices. The results show that the proposed CFSAPID controller was able to withstand the load disturbances, at variable input trajectory with a stable pressure in chambers at almost minimum hysteresis effect compared to the FSAPID and single PID controllers.

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“…Generally, the research efforts on the pneumatic servo systems can be divided into two aspects. One is based on the modification of the conventional linear controllers such as friction compensation-based linear controller, proportional-integral-derivative gain scheduling techniques and intelligent control-based controller [3][4][5]. To further enhance the achievable performance, another research effort has paid attention to the model-based nonlinear control strategies such as self-tuning control, model reference adaptive control, disturbance-observer-based control and adaptive robust control [6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Output feedback motion control of pneumatic servo systems with desired compensation approach

Wei-ping

Meng

2020

J Braz. Soc. Mech. Sci. Eng.

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In this study, an output feedback control strategy for the pneumatic asymmetric cylinder is established by integrating a robust controller with the proposed desired compensation adaptive law and extended sliding mode observer (ESMO). Specifically, in order to attenuate the parametric uncertainties, a desired compensation indirect-type estimation method, based on physical model and desired system states, is designed to achieve estimates of model parameters, and the parameter estimation error can be regarded as part of the lumped uncertainties. Since only displacement signal is available, both the unmeasured system states and lumped uncertainties are estimated by the proposed ESMO, and the global stability is guaranteed by the presented robust control law. As a result, structured (i.e., parametric uncertainties) and unstructured (i.e., lumped uncertainties such as unmodeled dynamics, external disturbance and parameter estimation error) uncertainties can be handled and compensated, respectively, in one controller. The comparative experimental results indicate that the prescribed tracking trajectory can be achieved by the proposed controller in the presence of time-varying uncertainties.

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Optimal Design of a Fractional-Order Proportional-Integer-Differential Controller for a Pneumatic Position Servo System

Cited by 82 publications

References 29 publications

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Cascade Control Strategy on Servo Pneumatic System with Fuzzy Self-Adaptive System

Output feedback motion control of pneumatic servo systems with desired compensation approach

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