• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.37 no.1 s.109
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• pp.61-66
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• 2005

The grade change operations In paper mills exhibit inherent nonlinear dynamic characteristics. For this reason, the conventional model predictive control techniques based on linear process models are not adequate for the grade change operations. In this paper, a bilinear model for the nonlinear grade change processes was presented first and optimal input variables were calculated by using one-step-ahead predictive control method. Numerical simulations showed that the control performance lied within acceptable range and that the bilinear model predictive control scheme was highly promising control strategy for the grade change operations.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1194-1198
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• 1993

Active roll control can improve handling and ride comfort. Dynamic characteristics of the hydraulic actuators for active suspension, which can be modeled as the 1'st order time lag system, hinders the performance improvement. To overcome this shortcoming a predictive controller is designed based on 3 d.o.f. linear vehicle handling model. The effect of this controller is studied through the simulation based on 10 d.o.f. nonlinear vehicle model and the results is compared to that of feedforward controller which uses lateral acceleration as control signal.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.5-155
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• 2001

The robust predictive control law which use the bound estimation is proposed for uncertain robot manipulators. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about model, it´s an important tend to design a robust control law that will guarantee the desired performance of the manipulator under uncertain elements. In the preceeding work, the robust predictive control law was proposed. In this work, we propose a class of robust predictive control of manipulators with the bound estimate technique and fe stability based on Lyapunov function is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.343-347
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• 1989

In this paper, predictive control method using actual applied input which is the weighted summation of past inputs is presented. In conventional predictive control methods, a set of control inputs is computed and in these only the first element is applied to the process at each time instant. But this predictive control method based on conventional methods considers all computed control inputs. Consequently, the characteristic of response and the reliability of the control scheme in the case of imperfact model are improved.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.318-322
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• 1996

In this study, a controller design method is proposed for controlling the discrete-time chaotic systems efficiently. Our proposed control method is based on Generalized Predictive Control and uses NARMAX models as a controlled model. In order to evaluate the performance of our proposed controller design method, a proposed controller is applied to Henon system which is a discrete-time chaotic system, and then the control performance of the proposed controller are compared with those of the previous model-based controllers through computer simulations. Through simulations, it is shown that the control performance of the proposed controller is superior to that of the conventional model-based controller.

• Journal of Power Electronics
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• v.17 no.3
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• pp.610-620
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• 2017

The Finite Control Set-Model Predictive Controller (FCS-MPC) for quasi Z-Source Inverters (qZSIs) is designed to reduce the number of sensors by proposing a current observer for the inductor current. Unlike the traditional FCS-MPC algorithm, the proposed model removes the inductor current sensor and observes the inductor current value based on the deposited prior optimized state as well as the capacitor voltage during this state. The proposed observer has been validated versus a typical MPC. Then, a comparative study between the proposed Modified Finite Control Set-Model Predictive Controller (MFCS-MPC) and a linear PID controller is provided under the same operating conditions. This study demonstrates that the dynamic response of the control objectives by MFCS-MPC is faster than that of the PID. On the other hand, the PID controller has a lower Total Harmonic Distortion (THD) when compared to the MFCS-MPC at the same average switching. Experimental results validate both methods using a DSP F28335.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1019-1023
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• 2012

This paper considers a model predictive control problem of discrete-time constrained systems with time-varying delay. For this problem, a delay dependent state feedback control approach is used to achieve asymptotic stabilization of systems with input constraints. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find cost monotonicity condition of the model predictive control algorithm which guarantee the closed loop stability. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• Advances in Energy Research
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• v.5 no.1
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• pp.79-90
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• 2017

The main objective of load frequency control (LFC) is to keep the frequency value at nominal value and force deviation of the frequency to zero in case of load change. This paper suggests LFC by using a model predictive control (MPC), based on Integral Square Error (ISE) method designed to optimize the damping of oscillations in a two-area power system. The MPC is designed and simulated with a model system in state space, for robust performance in the system response. The proposed MPC is tuned by ISE to achieve superior efficiency. Moreover, its performance has been assessed and compared with the PI and PID conventional controllers. The settling time and overshoot with MPC are extremely minimized as compared with conventional controllers.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.5
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• pp.415-421
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• 2014

This study proposes a model-based predictive control for interleaved multi-phase DC/DC converters. The power values necessary to adjust the output voltage in the succeeding are predicted using a converter model. The output power is controlled by selecting the optimal duty cycle. The proposed method does not require controller loops and modulators for converter switching. This method can control the converter by calculating the optimal duty cycle, which minimizes the error between the reference and actual output voltage. The effectiveness of the proposed method is verified through simulations and experiments.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.134-140
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• 2017

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.