Approximation Of Fractional Order Systems Research Articles

Efficacy of Continued Fraction Expansion technique in the approximation of fractional order systems

Efficacy of Continued Fraction Expansion technique in the approximation of fractional order systems

FOMCON Toolbox-Based Direct Approximation of Fractional Order Systems Using Gaze Cues Learning-Based Grey Wolf Optimizer

This study discusses a new method for the fractional-order system reduction. It offers an adaptable framework for approximating various fractional-order systems (FOSs), including commensurate and non-commensurate. The fractional-order modeling and control (FOMCON) toolbox in MATLAB and the gaze cues learning-based grey wolf optimizer (GGWO) technique form the basis of the recommended method. The fundamental advantage of the offered method is that it does not need intermediate steps, a mathematical substitution, or an operator-based approximation for the order reduction of a commensurate and non-commensurate FOS. The cost function is set up so that the sum of the integral squared differences in step responses and the root mean squared differences in Bode magnitude plots between the original FOS and the reduced models is as tiny as possible. Two case studies support the suggested method. The simulation results show that the reduced approximations constructed using the methodology under consideration have step and Bode responses more in line with the actual FOS. The effectiveness of the advocated strategy is further shown by contrasting several performance metrics with some of the contemporary approaches disseminated in academic journals.

Approximation of Fractional-Order Systems Using Balanced Truncation with Assured Steady-State Gain

Approximation of Fractional-Order Systems Using Balanced Truncation with Assured Steady-State Gain

Analysis of fractional order systems using newton iteration-based approximation technique

<span lang="EN-US">Fractional differential equations play a major role in expressing mathematically the real-world problems as they help attain good fit to the experimental data. It is also known that fractional order controllers are more flexible than integer order controllers. But when it comes to the numerical approximation of fractional order functions inaccuracies arise if the conversion technique is not chosen properly. So, when a fractional order plant model is approximated to an integer order system, it is required that the approximated model be accurate, as the overall system performance is based on the estimated integer order model. Nitisha-Pragya-Carlson (NPC) is a recent approximation technique proposed in 2018 to derive the rational approximation of fractional order differ-integrators. In this paper, three fractional order plant models having fractional powers 3.1, 1.25 and 1.3 is analyzed in frequency domain in terms of magnitude and phase response. The performance of approximated third and second order NPC based integer model is studied and compared with the integer models developed using other existing technique. The approximation error is calculated by comparing the frequency response of the developed models with the ideal response. It has been found that in all the three examples NPC based models are very much close to the ideal values. Hence proving the efficacy of NPC technique in approximation of fractional order systems.</span>

Multiple Fixed Pole-Based Rational Approximation for Fractional Order Systems

Abstract Our topic is the rational approximation of fractional order systems under Riemann–Liouville definition. This is a venerable, vast, fundamental area which attracts ongoing attention in coming years. In this work, the multiple fixed-pole scheme is developed. First, new schemes with different relative degree are developed to approximate fractional operators. Then, the fractional order is extended to the case of α>1. A discussion is made on the uniformity between the differentiator-based method and the integrator-based method. Afterward, the multiplicity of pole/zero is further generalized. In this framework, the nonzero initial instant and nonzero initial state are considered. Four examples are finally provided to show the feasibility and effectiveness of the developed algorithms.

Direct approximation of fractional order systems as a reduced integer/fractional-order model by genetic algorithm

In this paper, a new method is proposed for the reduced-order model approximation of commensurate/incommensurate fractional order (FO) systems. For integer order approximation, the model order is determined via Hankel singular values of the original system; while the order of FO approximations is determined via optimization. Unknown parameters of the reduced model are obtained by minimizing a fitness function via the genetic algorithm (GA). This fitness function is the weighted sum of differences of Integral Square Error (ISE), steady-state errors, maximum overshoots, and ISE of the magnitude of the frequency response of the FO system and the reduced-order model. Therefore, both time and frequency domain characteristics of the system considered in obtaining the reduced-order model. The stability criteria of the reduced-order systems were obtained in various cases and added to the cost function as constraints. Three fractional order systems were approximated by the proposed method and their properties were compared with famous approximation methods to show the out-performance of the proposed method.

An Integer-Order Transfer Function Estimation Algorithm for Fractional-Order PID Controllers

Fractional-order systems and controllers have been extensively used in many control applications to achieve robust modeling and controlling performance. To implement these systems, curve fitting based integer-order transfer function estimation techniques namely Oustaloup and Matsuda are most widely used. However, these methods are failed to achieve the best approximation due to the limitation of the desired frequency range. Thus, this article presents a simple curve fitting based integer-order transfer function estimation method for fractional-order differentiator/integrator using frequency response. The advantage of this technique is that it is simple and can fit the entire desired frequency range. Using the approach, an approximation table for fractional-order differentiator has also been obtained which can be used directly to obtain the approximation of fractional-order systems. A simulation study on fractional systems shows that the proposed approach produced better parameter approximation for the desired frequency as compared to Oustaloup, refined Oustaloup and Matsuda techniques.

An Effective Approach of Approximation of Fractional Order System using Real Interpolation Method

Fractional-order controllers are recognized to guarantee better closed-loop performance and robustness than conventional integer-order controllers. However, fractional-order transfer functions make time, frequency domain analysis and simulation significantly difficult. In practice, the popular way to overcome these difficulties is linearization of the fractional-order system. Here, a systematic approach is proposed for linearizing the transfer function of fractional-order systems. This approach is based on the real interpolation method (RIM) to approximate fractional-order transfer function (FOTF) by rational-order transfer function. The proposed method is implemented and compared to CFE high-frequency method; Carlson’s method; Matsuda’s method; Chare ’s method; Oustaloup’s method; least-squares, frequency interpolation method (FIM). The results of comparison show that, the method is simple, computationally efficient, flexible, and more accurate in time domain than the above considered methods. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Rational approximation of fractional order systems by vector fitting method

A novel method for approximating fractional order systems is presented. Vector fitting is involved in this method. As the basis of approximation of fractional order systems, approximation of fractional order operators is mostly achieved by curve fitting in frequency domain, such as the well-known Oustaloup’s method. However, these methods have several serious defects in principle. A new perspective based on system identification is adopted to deal with approximation of fractional order operators in this paper. Moreover, nonzero initial condition for approximating fractional order systems is considered. And the proposed assignment of initial values for the Caputo case offers an effective solution for the simulation with nonzero initial condition. Finally, numerical examples are given to verify the efficiency of the proposed method.

Criteria for response monotonicity preserving in approximation of fractional order systems

In approximation of fractional order systems, a significant objective is to preserve the important properties of the original system. The monotonicity of time frequency responses is one of these properties whose preservation is of great importance in approximation process. Considering this importance, the issues of monotonicity preservation of the step response and monotonicity preservation of the magnitude-frequency response are independently investigated in this paper. In these investigations, some conditions on approximating filters of fractional operators are found to guarantee the preservation of step magnitude-frequency response monotonicity in approximation process. These conditions are also simplified in some special cases. In addition, numerical simulation results are presented to show the usefulness of the obtained conditions.

Approximate realization of digital fractional forward operator using digital IIR filter

In this paper, a simple and an efficient approach for approximating the digital fractional forward operator zm (0 < m < 1) using digital infinite impulse response (IIR) filter is proposed. In this method, the coefficients of the closed form digital IIR filter derived for the approximation of the fractional forward operator, in a given frequency band, are based on approximation of fractional order systems. First, analog rational function approximation, in a given frequency band, of the fractional power zero (FPZ) is given. Then, the forward difference generating function is used to obtain a closed form IIR digital filter equivalent of the continuous FPZ, which approximates the digital fractional forward operator. Finally, illustrative examples have been presented to illustrate the effectiveness of the proposed design technique of the fractional forward operator zm approximation and its use in performing a fractional m-step prediction.

Unified Galerkin- and DAE-Based Approximation of Fractional Order Systems

We consider numerical solutions of nonlinear multiterm fractional integrodifferential equations, where the order of the highest derivative is fractional and positive but is otherwise arbitrary. Here, we extend and unify our previous work, where a Galerkin method was developed for efficiently approximating fractional order operators and where elements of the present differential algebraic equation (DAE) formulation were introduced. The DAE system developed here for arbitrary orders of the fractional derivative includes an added block of equations for each fractional order operator, as well as forcing terms arising from nonzero initial conditions. We motivate and explain the structure of the DAE in detail. We explain how nonzero initial conditions should be incorporated within the approximation. We point out that our approach approximates the system and not a specific solution. Consequently, some questions not easily accessible to solvers of initial value problems, such as stability analyses, can be tackled using our approach. Numerical examples show excellent accuracy.