• Journal of Power Electronics
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• v.19 no.5
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• pp.1193-1202
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• 2019

A SMPMSM drive system is a typical nonlinear system with time-varying parameters and unmodeled dynamics. The speed outer loop and current inner loop control structures are coupled and coexist with various disturbances, which makes the speed control of SMPMSM drive systems challenging. First, an ultra-local model of a PMSM driving system is established online based on the algebraic estimation method of model-free control. Second, based on the backstepping control framework, model-free adaptive integral backstepping (MF-AIB) control is proposed. This scheme is applied to the permanent magnet synchronous motor (PMSM) drive system of an electric vehicle for the first time. The validity of the proposed control scheme is verified by system simulations and experimental results obtained from a SMPMSM drive system bench test.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.351-358
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• 2023

This study designed a model-based Vehicle Control Unit (VCU) software for electric vehicles. Electric vehicles have transitioned from conventional powertrains (e.g., engines and transmissions) to electric powertrains. The primary role of the VCU is to determine the optimal torque for driving control. This decision is based on the driver's power request and current road conditions. The determined torque is then transmitted to the electric drive system, which includes motors and controllers. The VCU employs an Artificial Neural Network (ANN) and calibrated reference torque to enhance the electric vehicle's performance. The designed VCU software further refines the final reference torque by comparing the control logic with the torque calculation functions and ANN-generated reference torque. Vehicle tests confirmed the effective optimization of vehicle performance using the model-based VCU software, which includes an ANN.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.6 s.165
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• pp.903-911
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• 1999

A high speed tracking control system for 6-6 Stewart platform manipulator is designed for performing the model based joint-axis sliding mode control. Because of the complex dynamics and kinematics of the Stewart platform manipulator, two computer systems, consisting of a PC and a DSP, are adopted, so that real time tasks are run in synchronous and asynchronous modes. It is experimentally proven that the proposed control system makes the convenience in implementation of model based tracking control, so that it can achieve effective tracking control under relatively high speed and additional payload conditions.

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.2
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• pp.54-60
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• 2007

In this paper, we suggest the high efficient control method based on general PI control law for a variable speed refrigeration system. In the variable speed refrigeration system, the capacity and the superheat are mainly controlled by an inverter and an electronic expansion valve, respectively, for saving energy and improving coefficient of performance. Thus, we proposed a decoupling model to eliminate the interfering loop between the capacity and superheat at first. Next, we designed PI controller to control the capacity and superheat independently and simultaneously. Finally, the control performance was investigated through some experiments. The experimental results showed that the proposed PI controller based on the decoupling model can obtain good control performance under the various control references and thermal load.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.192-196
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• 2001

This work describes the modeling of cutting process for feedback control based on signal processing in end-milling. Here, cutting force is used to design control model by a variety of schemes which are moving average, ensemble average, peak value, root mean square and analog low-pass filtering. It is expected that each model offers its own peculiar advantage in following cutting force control.

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.70-73
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• 2010

In order to provide theoretical analysis for the active roll stabilizer (ARS), the simulation model based on AMESim is developed in the paper. The simplified vehicle rolling motion model is derived firstly, and then the entire ARS control system model is constructed. Furthermore, the simulation is implemented to confirm the roll control effect. The simulation results show that the derived model can be used as theoretical analysis for developing components of ARS control system.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.368-373
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• 2005

This paper presents a new framework for the traffic flow control based on integrated model descriptions as the Hybrid Dynamical System (HDS).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.165-168
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• 1996

In this paper, we propose a design method of PID adaptive controller based on frequency domain analysis. The method is based on the estimation of a nonparametric process model in the frequency domain and the determination of the PID controller parameters by achieving partial model matching so as to minimize a performance function concerning to relative model error between the loop transfer function of the control system and the desired system. In the design method the process is represented only by a discrete set of points on the Nyquist curve of the process. Therefore it is not necessary to estimate a full order parameterized process model.

• Structural Engineering and Mechanics
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• v.26 no.4
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• pp.377-392
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• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.