A Robust Fractional Order Parallel Control Structure for Flow Control using a Pneumatic Control Valve with Nonlinear and Uncertain Dynamics

Goyal, Vishal; Mishra, Puneet; Deolia, Vinay Kumar

doi:10.1007/s13369-018-3328-6

Cited by 23 publications

(9 citation statements)

References 29 publications

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“…The effectiveness of the model was promising compared to the PIDIM controller and conventional PID controller in hysteresis effects and dealing with nonlinearities of the system. [147], V. Goyal et al…”

Section: Bsa-based Inverse Model Identifying Nonlinear Dynamic Systemmentioning

confidence: 99%

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Hassan

Rashid

2020

Applied Mathematics and Computation

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Backtracking search optimisation algorithm (BSA) is a commonly used meta-heuristic optimisation algorithm and was proposed by Civicioglu in 2013. When it was first used, it exhibited its strong potential for solving numerical optimisation problems. Additionally, the experiments conducted in previous studies demonstrated the successful performance of BSA and its non-sensitivity toward the several types of optimisation problems.This success of BSA motivated researchers to work on expanding it, e.g., developing its improved versions or employing it for different applications and problem domains. However, there is a lack of literature review on BSA; therefore, reviewing the aforementioned modifications and applications systematically will aid further development of the algorithm. This paper provides a systematic review and meta-analysis that emphasise on reviewing the related studies and recent developments on BSA. Hence, the objectives of this work are twofold: (i) First, two frameworks for depicting the main extensions and the uses of BSA are proposed. The first framework is a general framework to depict the main extensions of BSA, whereas the second is an operational framework to present the expansion procedures of BSA to guide the researchers who are working on improving it. (ii) Second, the experiments conducted in this study fairly compare the analytical performance of BSA with four other competitive algorithms: differential evolution (DE), particle swarm optimisation (PSO), artificial bee colony (ABC), and firefly (FF) on 16 different hardness scores of the benchmark functions with different initial control parameters such as problem dimensions and search space. The experimental results indicate that BSA is statistically superior than the aforementioned algorithms in solving different cohorts of numerical optimisation problems such as problems with different levels of hardness score, problem dimensions, and search spaces. This study can act as a systematic and meta-analysis guide for the scholars who are working on improving BSA.In artificial intelligence (AI), besides the existing traditional symbolic and statistical methods [1], computational intelligence (CI) has emerged as a recent research area [2]. According to [3], CI deals with collections of nature-inspired algorithms and approaches that in turn have been used to deal with complex practical problems that cannot be feasibly or effectively solved by traditional methods. CI comprises three subfields: fuzzy logic, evolutionary computation, and neural network.The concept of swarm intelligence (SI) is a part of evolutionary computation. It deals with artificial and natural systems that comprise several individuals and possess the ability of self-organisation and decentralised control.This concept, which was primarily initiated by Gerardo Beni and Jing Wang in 1989 in the context of cellular robotic systems, is used in AI [4]. Typically, the SI system comprises a collection of agents. The agents interact with their own environment or with each other. SI syst...

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Section: Bsa-based Inverse Model Identifying Nonlinear Dynamic Systemmentioning

confidence: 99%

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Hassan

Rashid

2020

Applied Mathematics and Computation

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“…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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“…This paper is an effort to study the same and investigates the enhancement in the performance for the control structure in terms of better control operation. A fractional order PCS (FOPCS) [23] is studied in this paper regarding the tuning of its parameters. The FOPCS structure uses FOPID controllers to provide better robustness along with decoupled tracking and regulatory actions.…”

Section: Introductionmentioning

confidence: 99%

“…To design integer order controller for conventional PCS in this work, λ and µ were set to unity. Figure 1 shows the structure of analyzed FOPCS [23], where the controllers for setpoint tracking G ST c (s µ ) and disturbance rejection G DR c (s µ ) have a PID structure but are now extended to fractional order. In other words, the conventional PCS which decouples the setpoint tracking and disturbance rejection actions can now be thought as to provide robustness to handle the parametric uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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A fractional order parallel control structure tuned with meta-heuristic optimization algorithms for enhanced robustness

Goyal

Mishra

Shukla

et al. 2019

Journal of Electrical Engineering

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This paper studies an improved fractional order parallel control structure (FOPCS) for enhancing the robustness in an industrial control loop having a first order process with dead time along with its tuning aspects. Since inclusion of fractional order calculus also increase the number of parameters to be determined for a particular control loops, tuning becomes an essential task. Four different tuning methods are considered to optimize the gains of parallel control structure (PCS) and FOPCS. Integral of time weighted absolute error for servo and regulatory problems along with overshoot value have been considered for performance evaluation. Extensive simulation studies including change in setpoint and mismatch in processmodel parameters have been carried out. On the basis of these studies, it was observed that FOPCS tuned by backtracking search algorithm, outperformed all other controllers in terms of considered performance measures.

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A Robust Fractional Order Parallel Control Structure for Flow Control using a Pneumatic Control Valve with Nonlinear and Uncertain Dynamics

Cited by 23 publications

References 29 publications

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

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

A fractional order parallel control structure tuned with meta-heuristic optimization algorithms for enhanced robustness

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