Tuning and implementation methods for fractional-order controllers

This article presents a fuzzy fractional-order PID (FFOPID) controller scheme for a pneumatic pressure regulating system. The industrial pneumatic pressure systems are having strong dynamic and nonlinearity characteristics; further, these systems come across frequent load variations and external disturbances. Hence, for the smooth and trouble-free operation of the industrial pressure system, an effective control mechanism could be adopted. The objective of this work is to design an intelligent fuzzy-based fractional-order PID control scheme to ensure a robust performance with respect to load variation and external disturbances. A novel model of a pilot pressure regulating system is developed to validate the effectiveness of the proposed control scheme. Simulation studies are carried out in a delayed nonlinear pressure regulating system under different operating conditions using fractional-order PID (FOPID) controller with fuzzy online gain tuning mechanism. The results demonstrate the usefulness of the proposed strategy and confirm the performance improvement for the pneumatic pressure system. To highlight the advantages of the proposed scheme a comparative study with conventional PID and FOPID control schemes is made.

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“…The equation given in (4) is very useful to obtain a numerical solution of fractional differential equation [19]. …”

Section: Mathematical Background Of Fractional Calculusmentioning

confidence: 99%

Fuzzy Fractional-Order PID Controller for Fractional Model of Pneumatic Pressure System

Al‐Dhaifallah

Kanagaraj

Nisar

2018

Mathematical Problems in Engineering

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“…Agrawal and his co-workers [4], [6], [12] developed formulations and numerical schemes for FOCPs based on the fractional variational principles. Petráš [64] presented methods of tuning and implementation of Fractional-Order Controllers. Machado discussed the design of fractional-order discrete-time controllers [86] and proposed a new method for optimal tuning of fractional controllers by using genetic algorithms [87].…”

Section: Stochastic Fractional Optimal Controlmentioning

confidence: 99%

Stochastic dynamics and fractional optimal control of quasi integrable Hamiltonian systems with fractional derivative damping

Chen

Zhu

2013

fcaa

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In the present survey, some progress in the stochastic dynamics and fractional optimal control of quasi integrable Hamiltonian systems with fractional derivative damping is reviewed. First, the stochastic averaging method for quasi integrable Hamiltonian systems with fractional derivative damping under various random excitations is briefly introduced. Then, the stochastic stability, stochastic bifurcation, first passage time and reliability, and stochastic fractional optimal control of the systems studied by using the stochastic averaging method are summarized. The focus is placed on the effects of fractional derivative order on the dynamics and control of the systems. Finally, some possible extensions are pointed out.MSC 2010 : Primary 26A33; Secondary 33E12, 34A08, 34K37, 35R11, 60G22

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“…Recently, Lanusse et al shows that the firstgeneration CRONE control-system design methodology is able to provide robust fractional order PID for uncertain gain perturbed plants [9]. For a review of the recent design methods, please refer to [21] and [14].…”

Section: Introductionmentioning

confidence: 99%

Bode shaping-based design methods of a fractional order PID controller for uncertain systems

et al. 2014

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This paper deals with robust fractional order PID controller design via numerical optimization. Three new frequency-domain design methods are proposed. They achieve good robustness to the variation of some parameters by maintaining the open-loop phase quasi-constant in a pre-specified frequency band, i.e., maintaining the iso-damping property of the controlled system. The two first methods are extensions of the well-known Monje-Vinagre et al. method for uncertain systems. They ameliorate the numerical optimization algorithm by imposing the open-loop phase to be flat in a frequency band not only around a single frequency. The third method is an interval-based design approach that simplifies the algorithm by reducing the constraints number and offers a more large frequency band with an iso-damping property. Several numerical examples are presented to show the efficiency of each proposed method and discuss the obtained results. Also, an application to the liquid carbon monoxide level control is presented.B. Saidi · M. Amairi (B) · S. Najar · M. Aoun Research Unit Modeling, Analysis and Control of Systems (MACS)06/UR/11-12, National Engineering

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Tuning and implementation methods for fractional-order controllers

Cited by 116 publications

References 25 publications

Fuzzy Fractional-Order PID Controller for Fractional Model of Pneumatic Pressure System

Fuzzy Fractional-Order PID Controller for Fractional Model of Pneumatic Pressure System

Stochastic dynamics and fractional optimal control of quasi integrable Hamiltonian systems with fractional derivative damping

Bode shaping-based design methods of a fractional order PID controller for uncertain systems

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