Harmony search algorithm and Lyapunov theory based hybrid adaptive fuzzy controller for temperature control of air heater system with transport-delay

Sharma, Kaushik Das; Chatterjee, Amitava; Rakshit, Anjan

doi:10.1016/j.asoc.2014.09.009

Cited by 19 publications

(8 citation statements)

References 20 publications

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“…The two hybrid adaptation schemes are named as (i) concurrent hybrid adaptation scheme and (ii) preferential hybrid adaptation scheme, and they are proposed and utilized to design the AFLCs in this paper, following similar philosophies previously adopted in (K. D. Sharma et al, 2009Sharma et al, , 2010. All the required parameters to construct an AFLC are encoded in a candidate solution vector (CSV) (K. D. Sharma et al, 2014b). In this proposed design process, the hybrid adaptation schemes, either in concurrent manner or in preferential manner, are applied to optimize the structure of the AFLC, that is, the number of MFs required to fuzzify the input variables, centre locations of the input MFs, positions of the output singletons and so forth and the scaling factors of the input and output variables.…”

Section: Hybrid Aflc Design Methodology For Disturbance Rejectionmentioning

confidence: 99%

“…Here the peak of any MF corresponds to the right base support of the previous MF. The contents of structural flags determine the number of MFs in which each input variable is fuzzified and accordingly the peaks are also organized (K. D. Sharma et al, 2009Sharma et al, , 2010Sharma et al, , 2014b.…”

Section: Hybrid Aflc Design Methodology For Disturbance Rejectionmentioning

confidence: 99%

“…The present work has employed harmony search (HS) algorithm, a music inspired meta-heuristic optimization technique (Geem, Kim, & Loganathan, 2001), to design not only the free parameters of the AFLCs but also the structures of the controllers, to reduce this fuzzy approximation error. Successful designs of optimal/ near optimal AFLCs, using Lyapunov theory based local adaptation in tandem with HS algorithm based global optimization, have already been reported in several earlier works (K. D. Sharma, Chatterjee, & Rakshit, 2010, 2014b, 2014a.…”

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A novel disturbance rejection factor based stable direct adaptive fuzzy control strategy for a class of nonlinear systems

et al. 2020

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This paper proposes a unique disturbance rejection factor (DRF) based design of direct stable adaptive fuzzy logic controllers (AFLCs) for a class of non‐linear systems with large and fast disturbances. The proposed AFLCs are realized by employing hybrid combinations of Lyapunov theory based local adaptation and harmony search algorithm based global optimization technique. These hybrid AFLCs are designed with the objective of optimizing both the structure and free parameters of it with guaranteed stability and, at the same time, simultaneously achieving satisfactory tracking performance and disturbance rejection. The novelty of the proposed work lies in the fact that, in a bid to perform the disturbance rejection, the nature of the disturbance itself is used in designing the tracking control law. The proposed DRF based hybrid stable AFLCs are implemented for several benchmark case studies and extensive performance evaluations demonstrate their usefulness.

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Section: Hybrid Aflc Design Methodology For Disturbance Rejectionmentioning

confidence: 99%

Section: Hybrid Aflc Design Methodology For Disturbance Rejectionmentioning

confidence: 99%

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confidence: 95%

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A novel disturbance rejection factor based stable direct adaptive fuzzy control strategy for a class of nonlinear systems

et al. 2020

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“…In the paper by Sharma et al [110], focusing on the Lapunov principle and the HS algorithm, the proposed hybrid stable adaptive fuzzy controllers were implemented for the real-life temperature regulation of the air heater process in various sections of the air flow duct. The obtained optimization results confirm the success of the proposed model.…”

Section: Harmony Search Algorithm and Fuzzy Controllersmentioning

confidence: 99%

Harmony Search Algorithm and Fuzzy Logic Theory: An Extensive Review from Theory to Applications

et al. 2021

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In recent years, many researchers have utilized metaheuristic optimization algorithms along with fuzzy logic theory in their studies for various purposes. The harmony search (HS) algorithm is one of the metaheuristic optimization algorithms that is widely employed in different studies along with fuzzy logic (FL) theory. FL theory is a mathematical approach to expressing uncertainty by applying the conceptualization of fuzziness in a system. This review paper presents an extensive review of published papers based on the combination of HS and FL systems. In this regard, the functional characteristics of models obtained from integration of FL and HS have been reported in various articles, and the performance of each study is investigated. The basic concept of the FL approach and its derived models are introduced to familiarize readers with the principal mechanisms of FL models. Moreover, appropriate descriptions of the primary classifications acquired from the coexistence of FL and HS methods for specific purposes are reviewed. The results show that the high efficiency of HS to improve the exploration of FL in achieving the optimal solution on the one hand, and the capability of fuzzy inference systems to provide more flexible and dynamic adaptation of the HS parameters based on human perception on the other hand, can be a powerful combination for solving optimization problems. This review paper is believed to be a useful resource for students, engineers, and professionals.

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“…It uses information from all solutions in the harmony memory to generate a new solution. Consequently, the HS algorithm imposes fewer mathematical requirements compared to other metaheuristics and it can easily be adapted to solve various types of engineering optimization problems (Ambia et al, 2015; Sharma et al, 2014; Tarkeshwar and Mukherjee, 2015).…”

Section: Introductionmentioning

confidence: 99%

Harmony search optimization for robust pole assignment in union regions for synthesizing feedback control systems

Zhai

Gao

2017

Transactions of the Institute of Measurement and Control

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This paper is concerned with robust pole assignment optimization for synthesizing feedback control systems via state feedback or observer-based output feedback in specified union regions using the harmony search algorithm. By using exact pole placement theory and the harmony search algorithm, robust pole assignment for linear discrete-time systems or linear continuous-time systems in union regions can be converted into a global dynamical optimization problem. The robust measured indices are derived for robust union region stability constraints and a robust [Formula: see text] performance. For the nonlinear, robust measured indices, a set of dynamic poles and the corresponding feedback controllers can be obtained by global dynamic optimization based on the harmony search algorithm and the idea of robust exact pole assignment. One key merit of the proposed approach is that the radius or the position of the sub-regions can be arbitrarily specified according to the transient performance request. Furthermore, the eigenstructure of the closed-loop system matrix can be optimized with better robustness for the proposed approach. Finally, the simulation results for a discrete-time system and a continuous-time system demonstrate the effectiveness and superiority of the proposed method.

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Harmony search algorithm and Lyapunov theory based hybrid adaptive fuzzy controller for temperature control of air heater system with transport-delay

Cited by 19 publications

References 20 publications

A novel disturbance rejection factor based stable direct adaptive fuzzy control strategy for a class of nonlinear systems

A novel disturbance rejection factor based stable direct adaptive fuzzy control strategy for a class of nonlinear systems

Harmony Search Algorithm and Fuzzy Logic Theory: An Extensive Review from Theory to Applications

Harmony search optimization for robust pole assignment in union regions for synthesizing feedback control systems

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