• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.505-508
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• 2006

This paper presents a new analytical approach for designing multiloop PI controllers for disturbance rejection in multivariable processes with time delay. The proposed method is based on IMC-PID design approach. To overcome a sluggish load response by dominant pole in the process, the IMC filter is modified to compensate the dominant pole effect. Based on the modified IMC filter, an analytical tuning rule for multiloop PI controller is driven by extending the generalized IMC-PID method for single input/single output (SISO) systems [1] to multi input/multi output (MIMO) systems. Simulation results show that the proposed method gives a satisfactory load performance as well as servo performance in the multiloop system.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.496-498
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• 1998

This paper presents a mathod of reducing hunting size or steady state error occurred in the output signals via regulating the PID controllers gains. The PID controllers are widely used in industrial processes. Such processes have several inherent features like continuous operation, fixed set value, and difficulty in applyirty test signals. Thus, this paper suggests fuzzy rules of reducing hunting magnitude or steady state error using output signals only. Such an intelligent tuning technique utilizes both the experts, experience and control engineers' theortical background. For two kinds of systems such as temperature or DC motors speed control, we showed the validity of proposed method in this paper.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.212-218
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• 2021

The Proportional Integral Derivative (PID) controller is the most popular industrial controller and more than 90% process industries use this controller. During the past 50 years, numerous good tuning methods have been proposed for Single Input Single Output Systems. However, design of PI/PID controllers for multivariable processes is a challenge for the researchers. A comparative study of three PID controllers design methods has been carried-out. These methods include the DS (Direct Synthesis) method, IMC (Internal model Control) method and ETF (Effective Transfer Function) method. MIMO PID controllers are designed for a number of 2×2, 3×3 and 4×4 process models with multiple delays. The performance of the three methods has been evaluated through simulation studies in Matlab/Simulink environment. After extensive simulation studies, it is found that the Effective Transfer Function (ETF) Method produces better output responses among two methods. In this work, only decentralized methods of PID controllers have been studied and investigated.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.11-18
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• 2021

The Proportional Integral Derivative (PID) controller is the most popular industrial controller and more than 90% process industries use this controller. During the past 50 years, numerous good tuning methods have been proposed for Single Input Single Output Systems. However, design of PI/PID controllers for multivariable processes is a challenge for the researchers. A comparative study of three PID controllers design methods has been carried-out. These methods include the DS (Direct Synthesis) method, IMC (Internal model Control) method and ETF (Effective Transfer Function) method. MIMO PID controllers are designed for a number of 2×2, 3×3 and 4×4 process models with multiple delays. The performance of the three methods has been evaluated through simulation studies in Matlab/Simulink environment. After extensive simulation studies, it is found that the Effective Transfer Function (ETF) Method produces better output responses among two methods. In this work, only decentralized methods of PID controllers have been studied and investigated.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.47-54
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• 2023

This article reviews recent advances and perspectives in neuroscience related to consciousness, cognition, and neural networks in the brain. The neural mechanisms underlying cognitive processes, such as perception, attention, memory, and decision-making, are explored. The article also examines how these processes give rise to our experience of consciousness. The implications of these findings for our understanding of the brain and its functions are presented, as well as potential applications of this knowledge in fields such as medicine, psychology, and artificial intelligence. Additionally, the article explores the concept of a quantum viewpoint concerning consciousness, cognition, and creativity and how incorporating DNA as a key element could reconcile classical and quantum perspectives on human behaviour, consciousness, and cognition, as explained by genomic psychological theory. Furthermore, the article explains how the human brain processes external stimuli through the sensory nervous system and how it can be simulated using an artificial neural network (ANN) consisting of one input layer, multiple hidden layers, and an output layer. The law of learning is also discussed, explaining how ANNs work and how the modification of weight values affects the output and input values. The article concludes with a discussion of future research directions in this field, highlighting the potential for further discoveries and advancements in our understanding of the brain and its functions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.349-354
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• 1991

The power output behavior of the binary cycle composed of two Carnot cycles is analyzed with considering heat transfer processes, in which the finitely constant temperature differences between heat sources and working fluids exists. The power output has the maximum value as an extremum for cycle temperatures and capacities of heat exchangers. In the internally reversible cycle, the power output is independent of the cycle temperature in the intermediate heat exchanger. In this case when the total capacities of heat exchangers are given, three heat exchangers have the same capacities at the maximum power output condition. In addition, when the cycle is not extremum for cycle temperatures and capacities of heat exchangers. At the maximum power output condition, the capacity of heat exchanger at the cold side is slightly more than the hot side as the cycle effectiveness decreases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.82-88
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• 2007

Service engineering is a new discipline which aims at basically understanding of service and a concrete methodology using engineering approach for service design. In this paper is introduced the serviset graph [7] which is a comprehensive concept to represent service products, processes, and operation activities. The proposed concept is a degree of commonality index in a service product in order to deal with service mass customization using the input-output analysis in economic model.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.107-113
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• 1991

This article develops a control model for an open queueing network in terms of both the input and the output processes with stochastic intensities. The input and the output intensities are subject to some capacity limits and optimum control is characterized by a threshold type with a finite upper barrier. A discounted profit is used as a decision criteria, which is revenue minus operating and holding cost.