Earticle

욕창은 아직 해결되지 않은 인류의 난제이다. 본 연구에서는 건반형 의료용 침대를 개발하고 체압센서를 장착하 여 욕창이 임계압력에 이르지 않도록 건반을 제어하는 방법을 제시한다. 이를 위해 4bar 링크를 이용한 건반형 매트리스 를 개발하고 건반의 높낮이를 체압센서를 통해 임계압력 이내로 제어하는 방법을 사용한다. 압력x시간이 중요 요인인 욕창에서 건반을 승하강하며 시간제어만을 할 때는 신체의 불편감이 있으나, 제시한 방법을 사용하면 압력을 임계압력이 내로 제어함으로서 편안한 상태에서 욕창을 예방하는 효과를 거둔다. 개발한 의료용 침대 시스템의 유효성과 타당성을 이론과 실험을 통해 검증하였다.

Pressure sores are an unresolved human challenge. In this study, a keyboard-type medical bed was developed and a body pressure sensor was installed to provide a method to control the keyboard so that the pressure sores do not reach the critical pressure. For this, a keyboard-type mattress using a 4bar link is developed, and a method of controlling the height adjustment of the keyboard within the critical pressure through a body pressure sensor is used. There is a feeling of discomfort in the body when the keyboard is raised and lowered from pressure sores, which is an important factor: pressure x time, and only time control is performed, but if the proposed method is used, pressure is controlled within the critical pressure, thereby preventing bedsores in a comfortable state. The effectiveness and validity of the developed medical bed system were verified through theories and experiments.

In order to ensure that wind turbines could be online under the condition of power grid transient fault, the technology of low voltage ride-through (LVRT) for wind turbine has become a research focus of experts and scholars at home and abroad. In current wind turbine control strategy, the PI parameters of the control system keep unchanged when the wind turbine is in the process of LVRT, which affects the performance of the control system. Therefore, the adaptive PI parameter adjustment system based on BP neural network is proposed, which realize the adaptive adjustment of PI parameters in the process of LVRT. The simulation model of the LVRT process was built, the simulation results show that this control algorithm can effectively restrain the current oscillation caused by the voltage sag, shorten the fault recovery time of the system, and has a good dynamic performance. Besides, the adaptability and robustness of the system has been increased, which has improved the low voltage ride-through capability of the system.

The pure electric vehicle with dual-energy storage system is driven under complex driving states. Owing to its nonlinear model, the fuzzy control is usually used in energy distribution. It is difficult for the conventional fuzzy controller without integral part to eliminate the static errors. Its control effect is not satisfactory. The required power minus actual power is the deviation. The self-adaptive fuzzy PI control adjusts the deviation values through tuning the parameters of PI controller in real time. Its control effect is satisfactory. The results of simulation experiment indicate that the self-adaptive fuzzy PI control is more economical than the fuzzy control under the same driving states.

Transmission accuracy of traditional Transmission Control Protocol (TCP) in high-bandwidth wireless network is low, and its efficiency is low. For these problems, the thesis proposes a virtual router model from the perspective of end-to-end, and on this basis of using the classical control theory the thesis proposes an end-to-end PI rate control algorithm--SPI RCP on the transmitter. According to the RTT information collected by the transmitter, the real-time queue length of virtual router is calculated, and by using the PI control theory the transmission rate of the transmitter is calculated to make the queue length of the bottleneck node is stabilized at a target location, at the same time to avoid the wrong adjust of congestion windows caused by wireless link packet loss. The end-to-end design of new algorithm saves router resources, enhances the stability of the queue length, and reduces network congestion packet loss. The simulation results show that compared with the traditional congestion control protocol, the new mechanism can better control the queue length of the router and improve the stability and network throughput of the network load.

Predictive functional control and multivariate PI predictive functional control is presented based on state space equation for non-linear, fast time-varying, multivariable coupling near-space vehicle attitude control system. Transforming nonlinear optimal problems into online optimization in the linear time-invariant systems and solve the control law in a rolling way. Lyapunov’s second stability theorem proved that the solved control law can ensure a certain degree of robustness of the closed-loop system. Tuning parameters of multivariable PI predictive functional controller based on particle swarm optimization algorithm. Designed near-space vehicle attitude controller and simulate it. Results show that both of the two control strategy can get good control performance, comparatively, multivariable PI predictive functional control has a better control effect. It has the advantages of non-overshoots, faster response, and smaller steady state error etc.

To minimize the longitudinal strip thickness error in the hydraulic cold rolling industries and improve traditional AGC control scheme on this problem, we put forward a secure gauge control system based on Advanced RISC Machines (ARM) and intelligent PI control strategy. The traditional automatic gauge control (AGC) scheme depended on personal experience about the parameters. The new gauge control system decreases the longitudinal strip thickness error via fuzzy control and ARM-based computing. Besides, this new system can be smaller than the traditional AGC system, and so is much easier to transport. The Fuzzy control scheme can increase the robustness of the ARM-based gauge control system against some disturbances. The Matlab-based experimental simulations show that our secure gauge control system with Fuzzy control and ARM is better than the traditional one.

The use of smart devices worldwide has been increasing day by day and its applications based on IoT have been also extended. But the power control system requires complicated control and processing information from the various sensors in practice. One of the best ways to save the power consumption is to manage elec-trical equipment individually on the Internet. In this paper, remote power control system for managing the power through the relay switch module via Python server was implemented by using Raspberry Pi. The pro-posed power control system can be used anywhere over the Internet.

A compound control method of sliding-model variable structure and fractional order PIλDμ(SMC-FOPID) is proposed based on such factors as strong nonlinearity, time-varying parameters, disturbance, time delay, as well as the rapidity of a working clutch system in the process of automated manual transmission (AMT) clutch control. The self-tuning of the composite weight coefficient is realized by the fuzzy inference algorithm with single input and output. The coordinated control of the SMC-FOPID is realized through the real-time adjustment of the composite weight coefficient. The control performances of proportional-integral-derivative (PID), fractional order PIλDμ (FOPID), sliding-model variable structure control (SMC), and SMC-FOPID were compared based on the performance index integral of time multiplied by absolute value of error (ITAE) to study the position tracking of an AMT clutch in the working process. The simulation result showed that the SMC-FOPID control method had higher synthetic control performance compared with the PID, FOPID, and SMC control methods. The feasibility and superiority of the position tracking of an AMT clutch with an SMC-FOPID controller were verified.

This paper proposes new fuzzy type sliding mode controller for multi-DOF joints to reduce/eliminate motor vibration. The fuzzy (PI+D)2 single-input single-output (SISO) fuzzy system is applied to modify each element of the control in a sliding mode controller. The proposed method is designed based on the Lyapunov method. Mathematical proof for the stability and the convergence of the system is presented. Various operation situations such as the set point control and the trajectory control are simulated. The simulation results demonstrate that the chattering and the steady state errors, which usually occur in the classical sliding mode control, are eliminated and satisfactory trajectory tracking is achieved.

The performance of an inverter-driven water-to-water heat pump with an electronic expansion valve (EEV) was measured as a function of compressor frequency, load conditions, and EEV opening. Based on the test results, a controller using proportional integral (PI) feedback or PI feedforward algorithm was designed and tested to investigate capacity modulation and transient response control of the system. Although the relation between superheat and EEV opening of the heat pump showed nonlinear characteristics, a control gain obtained at the rated frequency was applicable to various operating conditions without causing large deviations. When the simple PI feedback control algorithm was applied, a large overshoot of superheat and wet compression were observed due to time delay effects of compressor frequency. However, applying PI feedforward control scheme yielded better system performance and higher reliability, compared to the PI feedback algorithm.

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.

In this paper, a sliding mode and proportional plus integral (SM-PI) control combined with self-sustained phase shift modulation (SSPSM) for LLC resonant converters is presented. The proposed control scheme improves the transient response while preserving good steady-state performance. An averaged large signal model of an LLC converter with the ZVS modulation technique is developed for the SM control design. The sliding surface is obtained based on the input-output linearization concept. A system identification method is adopted to obtain the transform function of the LLC resonant converter, which is used to design the PI control. In order to reduce the inherent chattering problem in the steady state, the combined SM-PI control strategy is derived with fuzzy control, where the SM control is responsive during the transient state while the PI control prevails in the steady state. The combination of SSPSM and the SM-PI control provides ZVS operation, robustness and a fast transient response against step load variations. Simulation and experimental results validate the theoretical analysis and the attractive features of the proposed scheme.

In this paper, we suggest PI control with the Smith predictive controller to improve transient response of a variable speed refrigeration system (VSRS). As the refrigeration system has long dead time inherently, it is difficult to get fast responses of super-heat and reference temperature. We incorporated the Smith predictive controller into PI to compensate the effect of the long dead time of the system. At first, we introduced the decoupling model of the system to control capacity and superheat simultaneously and independently. Next, we designed the predictive controller of the superheat based on PI control law. Finally, the control performance by the proposed method was investigated through some numerical simulations and experiments. The results of the simulations and experiments showed that the proposed PI control with the predictive controller could obtain acceptable transient behaviour for the system.

Tracking harmonic current quickly and precisely is one of the keys to designing active power filters (APF). In the past, the current state feedback decoupling PI control was an effective means for three-phase systems in the current control of constant voltage constant frequency inverters and high frequency PWM reversible rectifiers. This paper analyzes in detail the limitation of the conventional PI conditioner in the APF application field and presents a novel PI control method. Canceling the delay of one sampling period and the misadjustment for tracking the harmonic current is the key problem of this PI control. In this PI control, the predictive output current value is obtained by a state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by a repetitive predictor synchronously. The repetitive predictor can achieve better predictions of the harmonic current. By this means, the misadjustment of the conventional PI control for tracking the harmonic current is cancelled. The experiment results with a three-level NPC APF indicate that the steady-state accuracy and dynamic response of this method are satisfying when the proposed control scheme is implemented.

Real and reactive power flows on a transmission line interact inherently. This situation degrades power flow controller performance when independent real and reactive power flow regulation is required. In this study, a quasi multi-pulse interline power flow controller (IPFC), consisting of eight six-pulse voltage source converters (VSC) switched at the fundamental frequency is proposed to control real and reactive power flows dynamically on a transmission line in response to a sequence of set-point changes formed by unit-step reference values. It is shown that the proposed hybrid fuzzy-PI commanded IPFC shows better decoupling performance than the parameter optimized PI controllers with analytically calculated feed-forward gains for decoupling. Comparative simulation studies are carried out on a 4-machine 4-bus test power system through a number of case studies. While only the fuzzy inference of the proposed control scheme has been modeled in MATLAB, the power system, converter power circuit, control and calculation blocks have been simulated in PSCAD/EMTDC by interfacing these two packages on-line.

The diesel Auxiliary Power Unit (APU) for vehicle applications is a complex nonlinear system. For the purpose of this paper presents a dynamic average model of the whole system in an entirely physical way, which accounts for the non-ideal behavior of the diode rectifier, the nonlinear phenomena of generator-rectifier set in an elegant way, and also the dynamics of the dc load and diesel engine. Simulation results show the accuracy of the model. Based on the average model, a simple PI control scheme is proposed for the multivariable system, which includes the steps of model linearization, separate PI controller design with robust tuning rules, stability verification of the overall system by considering it as an uncertain one. Finally it is tested on a detailed switching model and good performances are shown for both set-point following and disturbance rejection.

This paper addresses the output control of a utility-connected double-fed induction machine (DFIM) for wind power generation systems (WPGS). DFIM has a back-to-back converter to control outputs of DFIM driven by the wind turbine for WPGS. To supply commercially the power of WPGS to the grid without any problems related to power quality, the real and reactive powers (PQ) at the stator side of DFIM are strictly controlled at the required level, which in this paper is realized with the Fuzzy PI controller based on the field orientation control. For the Sinusoidal Pulse Width Modulation (SPWM) converter connected to the rotor side of DFIG to maintain the controllability of PQ at the state side of DFIM, the DC voltage of the DC link capacitor is also controlled at a certain level with the conventional Proportion-Integral (PI) controller of the real power. In addition, the power quality at the grid connected to the rotor side of DFIM through the back-to-back converter is maintained in a certain level with a PI controller of the reactive power. The controllers for the PQ at the stator side of DFIM, the DC link voltage of the back-to-back inverter and the reactive power at the grid connected to the rotor side of DFIM are designed and simulated in the PSIM program, of which the result verifies the performance of the proposed controllers.

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.