• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.10
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• pp.947-959
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• 2001

We propose a control scheme to control the indoor zone temperature via variable air volume (VAV) unit. To control the room temperature, state space model of the conditioned zone which is partitioned into nine artificial sectional regions is derived. The nonlinearity of the damper motion and actuator are considered for the practical use in the state space system description. The temperature control of the room temperature is performed by manipulating the degree of openness of the damper in relation to the local room temperature and the supplied air flow rate. In general, since a local temperature in the conditioned zone is measured, it is required to estimate the temperature values in each regions for the precise temperature control. We thus design a state observer to estimate the regional temperature, and use these values in the controller. The overall control system consists of the state observer based state feedback with the integral control. We compared the control results of the proposed scheme with those of cascade proportional and integral (PI) control, and showed that the scheme achieved precise control of the conditioned system.

• Transactions on Electrical and Electronic Materials
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• v.15 no.6
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• pp.297-304
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• 2014

Due to the nonlinearity and complexity of the three-phase photovoltaic inverter, we propose an intelligent control based on fuzzy logic and the classical proportional-integral-derivative. The feedback linearization method is applied to cancel the nonlinearities, and transform the dynamic system into a simple and linear subsystem. The system is transformed from abc frame to dq0 synchronous frame, to simplify the state feedback linearization law, and make the close-loop dynamics in the equivalent linear model. The controls improve the dynamic response, efficiency and stability of the three-phase photovoltaic grid system, under variable temperature, solar intensity, and load. The intelligent control of the nonlinear characteristic of the photovoltaic automatically varies the coefficients $K_p$, $K_i$, and $K_d$ under variable temperature and irradiation, and eliminates the oscillation. The simulation results show the advantages of the proposed intelligent control in terms of the correctness, stability, and maintenance of its response, which from many aspects is better than that of the PID controller.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.633-645
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• 2022

The active tuned mass damper (ATMD) is an efficient and reliable structural control system for mitigating the dynamic response of structures. The inertial force that an ATMD exerts on a structure to attenuate its otherwise large kinetic energy and undesirable vibrations and displacements is proportional to its excursion. Achieving a balance between the inertial force and excursion requires a control law or feedback mechanism. This study presents a technique for the optimum design of a sliding mode controller (SMC) as the control law for ATMD-equipped structures subjected to earthquakes. The technique includes optimizing an SMC under an artificial earthquake followed by testing its performance under real earthquakes. The SMC of a real 11-story shear building is optimized to demonstrate the technique, and its performance in mitigating the displacements of the building under benchmark near- and far-fault earthquakes is compared against that of a few other techniques (proportional-integral-derivative [PID], linear-quadratic regulator [LQR], and fuzzy logic control [FLC]). Results indicate that the optimum SMC outperforms PID and LQR and exhibits performance comparable to that of FLC in reducing displacements.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.270-282
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• 2015

A submerged body moving near the free surface needs to maintain its attitude and position to accomplish missions. It is necessary to validate the performance of a designed controller before a sea trial. The hydrodynamic coefficients of maneuvering are generally obtained by experiments or computational fluid dynamics, but these coefficients have uncertainty. Environmental loads such as the wave exciting force and suction force act on the submerged body when it moves near the free surface. Thus, a controller for the submerged body should be robust to parameter uncertainty and environmental loads. In this paper, the six-degree-of-freedom equations of motions for the submerged body are constructed. The suction force is calculated using the double Rankine body method. An adaptive control method based on an artificial neural network and proportional-integral-derivative control are used for the depth controller. Simulations are performed under various depth and speed conditions, and the results show the effectiveness of the designed controller.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.124-129
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• 2021

In this paper, an optimal controller design that guarantees absolute stability is proposed. The order of application of the thesis determines whether the delay time is included, and if the delay time is included, the delay time is approximated through the Pade approximation method. Then, the open loop transfer function for the process model and the controller transfer function is obtained, and the absolute stability interval is calculated by the Routh-Hurwitz discrimination method. In the last step, the optimal Proportional and Integral and Derivative(PID) control parameter value is calculated using a genetic algorithm using the interval obtained in the previous step. As a result, it was confirmed that the proposed method guarantees stability and is superior to the existing method in performance index by designing an optimal controller. If we study the compensation method for the delay time in the future, it is judged that better performance indicators will be obtained.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.70-78
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• 1997

Proportional-integral-derivative(P1D) controllers have been still widely used in industrial processes due to their simplicity, effectiveness, robustness for a wide range of operating conditions, and the familiarity of control engineers. And a number of recent papers in fuzzy systems are showing that fuzzy systems are universal approximators. That is, fuzzy controllers are capable of approximating any real continuous function on a compact set of arbitrary accuracy. In this paper, we derive the linear PID control law from the fuzzy control algorithm where all fuzzy sets for representing plant state variables and a control variable use common triangular types. We first lead a linear PD control law from a fuzzy logic control with only two fuzzy sets for error and change-of-error. And then we derive the linear PID control law from a fuzzy controller. We here assumed that the intervals of error, change-of-error, and integral error could be partitioned into arbitrary numbers, respectively. As a result, a linear PID controller is only a sort of various fuzzy logic controls.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1242-1244
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• 1992

This Paper deals with a Auto-Tuning Fuzzy PID Controller used in real time and its application for induction motor. The control strategy of the controller is able to develop and improve automatically. The new Auto-Tuning Fuzzy PID Control algorithm which modifies the fuzzy control decision table is presented in this paper. It can automatically refine an initial approximate set of fuzzy rules. The possibility of applying fuzzy algorithms in faster response, and more accurate was compared with other industrial processes, such as AC Motor driver. The performance of Proportional_Integral Derivative(PID) control and this fuzzy controllers is compared in terms of steady_state error, settling time, and response time. And then, Limitations of fuzzy control algorithms are also described.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1729_1730
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• 2009

This paper presents comparative experimental results of PI sliding mode control and PI control for a heavy duty robot which can handle an object of 600kg, The gains of the PI control was determined by TAE(Trial and Error) method. This paper presents a novel approach for the decoupling of the states cross-coupling using sliding mode control. The sliding mode control methode is based on the error between reference speeds and the actual speed. The proposed method has the advantages of PI control performance and the sliding mode control robustness. Its first step is to design PI controller, then the sliding mode control input term is added to it. This makes actual implementation of the controller easier. The robot and motion controllers were designed and made by author. The good control performance of the heavy duty robot was obtained by using simple algorithm. This means that the robot was designed very well in control respect.