• Title/Summary/Keyword: Predictive Control

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An Automatic Travel Control of a Container Crane using Neural Network Predictive PID Control Technique

  • Suh Jin-Ho;Lee Jin-Woo;Lee Young-Jin;Lee Kwon-Soon
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.1
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    • pp.35-41
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    • 2006
  • In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.

Input Constrained Robust Model Predictive Control with Enlarged Stabilizable Region

  • Lee, Young-Il
    • International Journal of Control, Automation, and Systems
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    • v.3 no.3
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    • pp.502-507
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    • 2005
  • The dual-mode strategy has been adopted in many constrained MPC (Model Predictive Control) methods. The size of stabilizable regions of states of MPC methods depends on the size of underlying feasible and positively invariant sets and the number of control moves. The results, however, may perhaps be conservative because the definition of positive invariance does not allow temporal departure of states from the set. In this paper, a concept of periodic invariance is introduced in which states are allowed to leave a set temporarily but return into the set in finite time steps. The periodic invariance can be defined with respect to sets of different state feedback gains. These facts make it possible for the periodically invariant sets to be considerably larger than ordinary invariant sets. The periodic invariance can be defined for systems with polyhedral model uncertainties. We derive a MPC method based on these periodically invariant sets. Some numerical examples are given to show that the use of periodic invariance yields considerably larger stabilizable sets than the case of using ordinary invariance.

Design of Envelope Protection Algorithm for Helicopters (헬리콥터의 비행영역제한 알고리즘 설계)

  • Ko, Joon Soo;Park, Sungsu;Kim, Kyungmok
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.23 no.2
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    • pp.63-68
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    • 2015
  • This paper presents the algorithm for envelope protection of helicopters. The algorithm consists of two feedback control loops: inner loop and outer loop. As an inner loop control, model following control is designed to meet the ADS-33 handling qualities specification by minimizing the tracking errors between the responses of the actual model and those of the command filter. In order to implement envelope protection, saturation limiter is imposed to command channels in command filter, whose limits are computed corresponding to the envelope limit. Fast model predictive control is designed as an outer loop control to deal with saturation constraints generated by the inner loop envelope protection and also imposed by outer loop envelope protection variables. Simulation results show that the proposed algorithm yields good envelope protection performance.

Parallel Connected High Frequency AC Link Inverters Based on Full Digital Control

  • Sha, Deshang;Guo, Zhiqiang;Deng, Kai;Liao, Xiaozhong
    • Journal of Power Electronics
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    • v.12 no.4
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    • pp.595-603
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    • 2012
  • This paper presents a full digital control strategy for parallel connected modular inverter systems. Each modular inverter is a high frequency (HF) AC link inverter which is composed of a HF inverter and a HF transformer followed by a cycloconverter. To achieve equal sharing of the load current and to suppress the circulating currents among the modules, a three-loop control strategy, consisting of a common output voltage regulation (OVR) loop, individual circulating current suppression (CCS) loops and individual inner current tracking (ICT) loops, is proposed. The ICT loops are implemented with predictive current control from which high precision current tracking can be obtained. The effectiveness of the proposed control strategy is verified by simulation and experimental results from parallel connected two full-bridge HF AC link inverter modules.

Temperature Control of a Reheating Furnace using Feedback Linearization and Predictive Control

  • Park, Jae-Hun;Jang, Yu-Jin;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.27.1-27
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    • 2001
  • Reheating furnace is a facility of heating up the billet to desired high temperature in the hot charge rolling process and it consists of 3 zones. Temperature control of reheating furnace is essential for successful rolling performance and high productivity. Mostly, temperature control is carried out using PID controller However, the PID control is not effective due to the nonlinearity of the reheating furnace(i.e, presence of the interference of neighboring zones and slow response of temperature etc.). In this paper, feedback linearization method is applied to obtain a linear model of the reheating furnace. Then, controller is designed using simple predictive control method. The effectiveness of this strategy is shown through simulations.

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Nonlinear Model Predictive Control Using a Wiener model in a Continuous Polymerization Reactor

  • Jeong, Boong-Goon;Yoo, Kee-Youn;Rhee, Hyun-Ku
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.49-52
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    • 1999
  • A subspace-based identification method of the Wiener model, consisting of a state-space linear block and a polynomial static nonlinearity at the output, is used to retrieve from discrete sample data the accurate information about the nonlinear dynamics. Wiener model may be incorporated into model predictive control (MPC) schemes in a unique way which effectively removes the nonlinearity from the control problem, preserving many of the favorable properties of linear MPC. The control performance is evaluated with simulation studies where the original first-principles model for a continuous MMA polymerization reactor is used as the true process while the identified Wiener model is used for the control purpose. On the basis of the simulation results, it is demonstrated that, despite the existence of unmeasured disturbance, the controller performed quite satisfactorily for the control of polymer qualities with constraints.

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Predictive Control of Bilateral Teleoperation with Short Time Delay (시간 지연이 있는 양방향 원격제어 시스템의 예측 제어)

  • Im, Heung-Jae;Chung, Wan-Kyun;Suh, Il-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.4
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    • pp.295-304
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    • 2000
  • In the teleoperation system, force and velocity signals are communicated between a master and a slave robot. The addition of force feedback to a teleoperation system benefits the operator by providing more information to perform given tasks especially for tasks requiring contact with environment. When the master and slave arms are located in different places, time delay is unavoidable and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The control scheme proposed in this paper is based on the estimator with virtual master model. Delayed signal from the master robot can be replaced by the estimated signal with the virtual master model. This control scheme makes the teleoperation system stable for the given time delay while the conventional scheme is not. This new control scheme is verified through numerical simulations and an experiments using the dual axis testbed of the teleoperation system.

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Obstacle Parameter Modeling for Model Predictive Control of the Unmanned Vehicle (무인자동차의 모델 예측제어를 위한 장애물 파라미터 모델링 기법)

  • Yeu, Jung-Yun;Kim, Woo-Hyun;Im, Jun-Hyuck;Lee, Dal-Ho;Jee, Gyu-In
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.12
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    • pp.1132-1138
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    • 2012
  • The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

An application study for generalized predictive control in distillation column (증류탑에서의 일반형 예측제어(GPC) 응용 연구)

  • Cha, M. H.;Lo, K.;Yoon, E. S.;Yeo, Y. K.;Song, H. K.
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.225-228
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    • 1990
  • The major difficulty in distillation column control lies in executing the set point tracking and the disturbance rejection, because of continuous changes in model order and dead time. For that, generalized predictive control(GPC) was applied to distillation column control. Recursive least square method was used to adjust the changes of model order and dead time. Quadratic progamming(QP) was used to solve the constraint problems in control action and the rate of control action. As a result of the simulation on the dynamic simulator(SPEEDUP) and the experiment on pilot plant, the ability of the set point tracking and the disturbance rejection was acceptable to apply to the real distillation column.

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Temperature Control of Ultrasupercritical Once-through Boiler-turbine System Using Multi-input Multi-output Dynamic Matrix Control

  • Moon, Un-Chul;Kim, Woo-Hun
    • Journal of Electrical Engineering and Technology
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    • v.6 no.3
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    • pp.423-430
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    • 2011
  • Multi-input multi-output (MIMO) dynamic matrix control (DMC) technique is applied to control steam temperatures in a large-scale ultrasupercritical once-through boiler-turbine system. Specifically, four output variables (i.e., outlet temperatures of platen superheater, finish superheater, primary reheater, and finish reheater) are controlled using four input variables (i.e., two spray valves, bypass valve, and damper). The step-response matrix for the MIMO DMC is constructed using the four input and the four output variables. Online optimization is performed for the MIMO DMC using the model predictive control technique. The MIMO DMC controller is implemented in a full-scope power plant simulator with satisfactory performance.