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Adaptive Torque Demand Control of SI Engine with a Continuous Variable Valve Train
Shigehiro Sugihira,Noriaki Sato,Hiromitsu Ohmori 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In recent years, integrated vehicle control system has been designed based on the information of torque. There-fore, engine is teated as the actuator generating torque and necessity of controlling engine torque has been increased. This paper describes adaptive torque demand control of SI(Spark Ignition) engine with continuous variable valve lift which is based on STC(Self Tuning Control).
New Simple Filtered-x Algorithm for Parallel Hammerstein Systems
Tomohiro Ohno,Akira Sano,Hiromitsu Ohmori 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
A new nonlinear filtered-x algorithm is proposed for adaptive feed forward compensation for parallel Ham-merstein systems, which has many applications such as nonlinear active no is econtrol and predistortion for nonlinear high power amplifiers. To attenuate the compensation error, a virtual error and prediction error are introduced and forced into zero by adjusting three nonlinear adaptive filter sin a non-line manner. It is shown that the convergence of the compen-sation error to zero can be assured by forcing the prediction error and virtual error to zero separately. The proposed method can adjust the adaptive feed forward controller by using the newly introduced virtual error, unlike the or dinary nonlinear filtered-x algorithm using the compensation error directly. Further more, the PE property of the reference signal is not needed, which is agreat advantage of the proposed direct approach. Its effectiveness is examined and clarified incomparison with an ordinary nonlinear filtered-x algorithm in numerical simulations.
Power Consumption/Supply Control Using Neural Network for Micro Grids
Tsunashi Kaneko,Shohei Shimizu,Hiromitsu Ohmori 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper proposes the control scheme using neural network for micro grids with isolated operation mode. Normally, the micro grid operates in interconnected mode with the medium voltage network, however when the power go down, the micro grid must have the ability to operate stably autonomously. So this paper evaluates the stability of the micro grids with isolated operation mode using the feedback error learning scheme in neural networks.
Recursive Sample-Entropy Method and Its Application for Complexity Observation of Earth Current
Shohei Shimizu,Koichi Sugisaki,Hiromitsu Ohmori 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
The effectiveness of Sample-Entropy was practically shown as the measure index of irregularity from time series, by the development of research to quantify complexity. This Sample-Entropy calculated from at least 100 sample points, can classify a various system which contains a deterministic chaos system and/or a stochastic system, and is strong against noise. Therefore it is applied to the wide fields such as the ecology, finance, the medical treatment, etc. In this paper, the recursive Sample-Entropy technique is proposed and it is applied to the earthquake forecast. The earthquake forecast is generally performed by using the vibration wave, however it is extremely short that time from the forecast to the occurrence. Then, in this research, I use the earth current data based on the technique called the VAN method that used an abnormal earth current that is the one of the macroscopic anomalies that the difference of time until the earthquake occurrence is long. As a result, it is confirmed that there is a possibility that the precursor of an earthquake are able to be observed in real time.