Dynamic optimization based on state transition algorithm for copper removal process

Hao, Miao; Zhou, Xiaojun; Huang, Tingwen; Yang, Chunhua; Gui, Weihua

doi:10.1007/s00521-017-3232-0

Cited by 29 publications

(10 citation statements)

References 33 publications

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“…Algorithm. In recent years, state transition algorithm (STA) [19] as a novel stochastic intelligent algorithm for global optimization has been broadly applied to different fields, such as image segmentation [20], fractional-order PID controller tuning [21], copper removal and goethite process in the hydrometallurgical process of zinc [22,23], sensor network localization [24], and other fields [25,26]. The inspiration of STA is derived from the concepts of state and state transition.…”

Section: Modified State Transitionmentioning

confidence: 99%

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

Zhou

Long

et al. 2019

Complexity

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This paper proposes an external archive-based constrained state transition algorithm (EA-CSTA) with a preference trade-off strategy for solving the power dispatch optimization problem in the electrochemical process of zinc (EPZ). The optimal power dispatch problem aims to obtain the optimal current density schedule to minimize the cost of power consumption with some rigorous technology and production constraints. The current density of each production equipment in different power stages is restricted by technology and production requirements. In addition, electricity price and current density are considered comprehensively to influence the cost of power consumption. In the process of optimization, technology and production restrictions are difficult to be satisfied, which are modeled as nonconvex equality constraints in the power dispatch optimization problem. Moreover, multiple production equipment and different power supply stages increase the amount of decision variables. In order to solve this problem, an external archive-based constrained state transition algorithm (EA-CSTA) is proposed. The external archive strategy is adopted for maintaining the diversity of solutions to increase the probability of finding the optima of power dispatch optimization problem. Moreover, a preference trade-off strategy is designed to improve the global search performance of EA-CSTA, and the translation transformation in state transition algorithm is modified to improve the local search ability of EA-CSTA. Finally, the experimental results indicate that the proposed method is more efficient compared with other approaches in previous papers for the optimal power dispatch. Furthermore, the proposed method significantly reduces the cost of power consumption, which not only guides the production process of zinc electrolysis but also alleviates the pressure of the power grid load.

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Section: Modified State Transitionmentioning

confidence: 99%

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

Zhou

Long

et al. 2019

Complexity

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“…The copper removal process of this plant consists of two continuous stirred reactors and one thickener. According to the principle of mass balance, the copper removal process model can be expressed by the following equations [35]:…”

Section: B Industrial Experiments 1) Copper Removal Processmentioning

confidence: 99%

Optimal Setting and Control Strategy for Industrial Process Based on Discrete-Time Fractional-Order PI$^{\lambda}$ D$^{\mu}$

et al. 2019

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Generally, the main task of the optimal operation in the industrial process is to satisfy the process technical requirements, and the PID controller is a well-known controller in industrial control applications. Nevertheless, due to the complicated mechanisms and the dynamic characteristics of a complex industrial process, the conventional PID controller fails to provide effective control to such systems. In this paper, we develop a novel discrete-time fractional order PID (DFOPID) control strategy to achieve the technical requirements of the complex industrial process. The proposed work is conducted through a combination of three novel interdependent efforts. First, on the basis of the widely used Tustin operator and its Taylor series, a digital structure of the DFOPID is proposed. Second, in order to solve the stability problem of the complex industrial process, an optimal setting of the approximation function's order (N) and five parameters (λ, µ, K p , K i , K d) is necessary. Hence, an integral time absolute error (ITAE) criterion is applied to convert the optimal setting problem to a nonconvex optimization problem. Finally, a novel intelligent optimization search algorithm called state transition algorithm is employed to carry out the aforementioned design procedure. Furthermore, the performance of the DFOPID control strategy in some practical industrial control systems, including the copper removal process and the electrochemical process of zinc are also investigated. INDEX TERMS Discrete-time system, PI λ D µ control, state transition algorithm, discretization method, complex industrial process.

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“…In general, model-based operational optimization techniques have been widely used. [8][9][10][11][12][13][14][15][16] Luo et al [14] optimized the crude oil distillation process and proposed a system optimization method that maximizes the annual economic benefit of the crude oil distillation system. In this method, the product output value and energy consumption were considered simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Multi‐stage intelligent operation optimization for a hydrocracking fractionation system with a multi‐fractionator series‐parallel structure

Wang

Sun

et al. 2020

Can J Chem Eng

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A fractionation system is an essential unit in the hydrocracking process. Its optimal operation is challenging because of the complexity in the structure of the distillation tower and composition of the stream. In addition, the seriesparallel structure between the distillation towers of different techniques aggravates the coupling and complexity of the hydrocracking fractionation system (HFS). This, in turn, increases the time complexity of the optimization problem. In this paper, a rigorous mechanism model of an actual HFS is first applied to describe the operating conditions of the HFS. Then, an improved state transition algorithm (STA) with a staged evaluation strategy is proposed to solve the above problem. To overcome problems caused by the series-parallel structure of HFS, the model is divided into multiple stages for evaluation by mechanism analysis. Furthermore, several typical convergence estimation criteria are introduced to reduce unnecessary model calculations. To solve time-consuming problems associated with HFS optimization, the adaptive change operator is used to improve the search function of the original algorithm and two performance criteria are presented to reduce the optimization time. The proposed algorithm is successfully applied to the operational parameter optimization problem of HFS with a multi-fractionator series-parallel structure. The experimental results indicated that the staged evaluation strategy improved the fast convergence probability of the HFS mechanism model and reduced unnecessary calculations, whereas the improved algorithm increased accuracy and significantly decreased optimization time.

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Dynamic optimization based on state transition algorithm for copper removal process

Cited by 29 publications

References 33 publications

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

Optimal Setting and Control Strategy for Industrial Process Based on Discrete-Time Fractional-Order PI$^{\lambda}$ D$^{\mu}$

Multi‐stage intelligent operation optimization for a hydrocracking fractionation system with a multi‐fractionator series‐parallel structure

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