• Title/Summary/Keyword: Optimal control algorithms

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Optimal Control Algorithms for the Full Storage Ice Cooling System (전축열방식 빙축열 시스템의 최적제어 알고리즘)

  • 한도영;이준호
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.14 no.4
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    • pp.350-357
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    • 2002
  • Optimal control algorithms for the full storage ice cooling system were developed by using a dynamic simulation program. Control algorithms for the storage charging mode were developed for the chiller outlet temperature setpoint control and the chiller capacity control. Control algorithms for the storage discharging mode were developed for the proper mode selection, the storage-only mode control, and the storage-priority chiller-shared mode control. Two different cases of the expected outdoor air temperature profile and the expected cooling load profile were used to analyze the effectiveness of these algorithms. Simulation results show the energy savings and the satisfactory controls of the ice storage system. Therefore, control algorithms developed for this study may effectively be used for the improved control of the ice storage cooling system.

Wind vibration control of stay cables using an evolutionary algorithm

  • Chen, Tim;Huang, Yu-Ching;Xu, Zhao-Wang;Chen, J.C.Y.
    • Wind and Structures
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    • v.32 no.1
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    • pp.71-80
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    • 2021
  • In steel cable bridges, the use of magnetorheological (MR) dampers between butt cables is constantly increasing to dampen vibrations caused by rain and wind. The biggest problem in the actual applications of those devices is to launch a kind of appropriate algorithm that can effectively and efficiently suppress the perturbation of the tie through basic calculations and optimal solutions. This article discusses the optimal evolutionary design based on a linear and quadratic regulator (hereafter LQR) to lessen the perturbation of the bridges with cables. The control numerical algorithms are expected to effectively and efficiently decrease the possible risks of the structural response in amplification owing to the feedback force in the direction of the MR attenuator. In addition, these numerical algorithms approximate those optimal linear quadratic regulator control forces through the corresponding damping and stiffness, which significantly lessens the work of calculating the significant and optimal control forces. Therefore, it has been shown that it plays an important and significant role in the practical application design of semiactive MR control power systems. In the present proposed novel evolutionary parallel distributed compensator scheme, the vibrational control problem with a simulated demonstration is used to evaluate the numerical algorithmic performance and effectiveness. The results show that these semiactive MR control numerical algorithms which are present proposed in the present paper has better performance than the optimal and the passive control, which is almost reaching the levels of linear quadratic regulator controls with minimal feedback requirements.

Optimal control of continuous system using genetic algorithms (유전 알고리듬을 이용한 연속 공정의 최적 제어)

  • Lee, Moo-Ho;Han, Chonghun;Chang, Kun-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.1
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    • pp.46-51
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    • 1997
  • The optimal control of a continuous process has been performed using genetic algorithms(GAs). GAs are robust and easily applicable for complex and highly nonlinear problems. We introduce the heuristics 'dynamic range' which reduces the search space dramaticaly keeping the robust search of GAs. GAs with dynamic range show the better performance than SQP(Successive Quadratic Programing) method which converges to a local minimum. The proposed methology has been applied to the optimal control of the continuous MMA-VA copolymerization reactor for the production of the desired molecular wieght and the composition of VA in dead copolymer.

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ANN-Based VRF (variable refrigerant flow) system control (인공신경망 기반 VRF 시스템 제어)

  • Moon, Jin Woo
    • Land and Housing Review
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    • v.10 no.3
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    • pp.9-16
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    • 2019
  • This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.

Optimal Wiener-Hopf Decoupling Controller Formula for State-space Algorithms

  • Park, Ki-Heon;Kim, Jin-Geol
    • International Journal of Control, Automation, and Systems
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    • v.5 no.4
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    • pp.471-478
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    • 2007
  • In this paper, an optimal Wiener-Hopf decoupling controller formula is obtained which is expressed in terms of rational matrices, thereby readily allowing the use of state-space algorithms. To this end, the characterization formula for the class of all realizable decoupling controller is formulated in terms of rational functions. The class of all stabilizing and decoupling controllers is parametrized via the free diagonal matrices and the optimal decoupling controller is determined from these free matrices.

The Optimal Control of an Absorption Air Conditioning System by Using the Steepest Descent Method

  • Han Doyoung;Kim Jin
    • International Journal of Air-Conditioning and Refrigeration
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    • v.12 no.3
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    • pp.123-130
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    • 2004
  • Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.

Optimal Control Algorithm for the Dual Source Chiller Air Conditioning System (복합 열원 공조시스템의 최적 제어 알고리즘)

  • Han, Do-Young;Kim, Jin
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.16 no.9
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    • pp.881-888
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    • 2004
  • Control algorithms for a dual source chiller air conditioning system were developed. These are control algorithms for the supply air temperature control, the supply header chilled water temperature control, the chiller chilled water temperature control, and the cooling tower water temperature control. These algorithms were analyzed by using a dynamic simulation program. Simulation results showed the energy savings and the satisfactory controls of an absorption and centrifugal chiller air conditioning system. Therefore, control algorithms developed for this study may effectively be used for the improved controls of the dual source chiller air conditioning system.

Integrated Engine-CVT Control Considering Powertrain Response Lag in Acceleration

  • Kim, Tal-Chol;Kim, Hyun-Soo
    • Journal of Mechanical Science and Technology
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    • v.14 no.7
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    • pp.764-772
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    • 2000
  • In this paper, an engine-CVT integrated control algorithm is suggested by considering the inertia torque and the CVT ratio change response lag in acceleration. In order to compensate for drive torque time delay due to CVT response lag, two algorithms are presented: (1) an optimal engine torque compensation algorithm, and (2) an optimal engine speed compensation algorithm. Simulation results show that the optimal engine speed compensation algorithm gives better engine operation around the optimal operation point compared to the optimal torque compensation while showing nearly the same acceleration response. The performance of the proposed engine-CVT integrated control algorithms are compared with those of conventional CVT control, and It is found that optimal engine operation can be achieved by using integrated control during acceleration, and improved fuel economy can be expected while also satisfying the driver's demands.

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Control of the Absorption Air Conditioning System by Using Steepest Descent Method (최속 강하법을 이용한 흡수식 냉동공조시스템 제어)

  • Han, Do-Young;Kim, Jin
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.15 no.6
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    • pp.495-501
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    • 2003
  • Control algorithms for the absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. The simulation results showed energy savings and the effective controls of an absorption air conditioning system.

A study on the structure evolution of neural networks using genetic algorithms (유전자 알고리즘을 이용한 신경회로망의 구조 진화에 관한 연구)

  • 김대준;이상환;심귀보
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.223-226
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    • 1997
  • Usually, the Evolutionary Algorithms(EAs) are considered more efficient for optimal, system design because EAs can provide higher opportunity for obtaining the global optimal solution. This paper presents a mechanism of co-evolution consists of the two genetic algorithms(GAs). This mechanism includes host populations and parasite populations. These two populations are closely related to each other, and the parasite populations plays an important role of searching for useful schema in host populations. Host population represented by feedforward neural network and the result of co-evolution we will find the optimal structure of the neural network. We used the genetic algorithm that search the structure of the feedforward neural network, and evolution strategies which train the weight of neuron, and optimize the net structure. The validity and effectiveness of the proposed method is exemplified on the stabilization and position control of the inverted-pendulum system.

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