• 제목/요약/키워드: dynamic tuning

검색결과 290건 처리시간 0.031초

실시간 적응 학습 제어를 위한 진화연산(I) (Evolutionary Computation for the Real-Time Adaptive Learning Control(I))

  • 장성욱;이진걸
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집B
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    • pp.724-729
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    • 2001
  • This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

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MODELING AND PI CONTROL OF DIESEL APU FOR SERIES HYBRID ELECTRIC VEHICLES

  • HE B.;OUYANG M.;LU L.
    • International Journal of Automotive Technology
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    • 제7권1호
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    • pp.91-99
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    • 2006
  • 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.

공작기계 주축용 스핀들 전동기를 위한 관성추정알고리즘 (Inertia Identification Algorithm for Spindle Motor of Machine Tool)

  • 정병환;최규하;최경진;이태리
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2007년도 하계학술대회 논문집
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    • pp.43-45
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    • 2007
  • This Paper proposes a simple identification method of the moment of inertia for high performance spindle motor of machine tool. It uses the dynamic equation of a simple mechanical system, the torque reference of a speed controller, and the actual rotating speed of machine. The identified inertia can be for auto-tuning of the gains in the speed controller. The effectiveness of the proposed method is proved by the computer simulation.

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A Fiber Laser Spectrometer Demodulation of Fiber Bragg Grating Sensors for Measurement Linearity Enhancement

  • Kim, Hyunjin;Song, Minho
    • Journal of the Optical Society of Korea
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    • 제17권4호
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    • pp.312-316
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    • 2013
  • A novel fiber-optic sensor system is suggested in which fiber Bragg grating sensors are demodulated by a wavelength-sweeping fiber laser source and a spectrometer. The spectrometer consists of a diffraction grating and a 512-pixel photo-diode array. The reflected Bragg wavelength information is transformed into spatial intensity distribution on the photo-diode array. The peak locations linearly correspond to the Bragg wavelengths, regardless of the nonlinearities in the wavelength tuning mechanism of the fiber laser. The high power density of the fiber laser enables obtaining high signal-to-noise ratio outputs. The improved demodulation characteristics were experimentally demonstrated with a fiber Bragg grating sensor array with 5 gratings. The sensor outputs were in much more linear fashion compared with the conventional tunable band-pass filter demodulation. Also it showed advantages in signal processing, due to the high level of photo-diode array signals, over the broadband light source system, especially in measurement of fast varying dynamic physical quantities.

A design of tuning band and structure to generate diverse properties by stretching

  • Ruqi Wang;Ruoyun Li
    • Advances in nano research
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    • 제14권5호
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    • pp.451-461
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    • 2023
  • Two-dimensional (2D) materials have been attracting attention since graphene monolayer was firstly separated. However, after an explosive boom, there is always quandary and stagnancy following and soon will come the refractory period of capital market. To avoid that undesired future, a paradigm of quasi 2D monolayer has been contemplated and devised in this article, with examples studied theoretically. The results show the general dynamic nonlinearity, and the expected tunability of bandgap without extra doping or substitution. These together suggest its intriguing both electronical and mechanical properties, which will enrich the arsenal of potential 2D materials.

High Performance Adjustable-Speed Induction Motor Drive System Incorporating Sensorless Vector Controlled PWM Inverter with Auto-Tuning Machine-Operated Parameter Estimation Schemes

  • Soshin, Koji;Okamura, Yukiniko;Ahmed, Tarek;Nakaoka, Mutsuo
    • Journal of Power Electronics
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    • 제3권2호
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    • pp.99-114
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    • 2003
  • This paper presents a feasible development on a highly accurate quick response adjustable speed drive implementation fur general purpose induction motor which operates on the basis of sensorless slip frequency type vector controlled sine-wave PWM inverter with an automatic tuning machine parameter estimation schemes. In the first place, the sensorless vector control theory on the three-phase voltage source-fed inverter induction motor drive system is developed in slip frequency based vector control principle. In particular, the essential procedure and considerations to measure and estimate the exact stator and rotor circuit parameters of general purpose induction motor are discussed under its operating conditions. The speed regulation characteristics of induction motor operated by the three-phase voltage-fed type current controlled PWM inverter using IGBT's is illustrated and evaluated fur machine parameter variations under the actual conditions of low frequency and high frequency operations for the load torque. In the second place, the variable speed induction motor drive system, employing sensorless vector control scheme which is based on three -phase high frequency carrier PWM inverter with automatic toning estimation schemes of the temperature -dependent and -independent machine circuit parameters, is practically implemented using DSP-based controller. Finally, the dynamic speed response performances for largely changed load torque disturbances as well as steady state speed vs. torque characteristics of this induction motor control implementation are illustrated and discussed from an experimental point of view.

상태(狀態)벡터 모형(模型)에 의한 하천유출(河川流出)의 실시간(實時間) 예측(豫測)에 관한 연구(研究) (Real-Time Prediction of Streamflows by the State-Vector Model)

  • 서병하;윤용남;강관원
    • 대한토목학회논문집
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    • 제2권3호
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    • pp.43-56
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    • 1982
  • 상태공간(狀態空間) 개념(槪念)에 기초(基礎)를 두어 시스템의 동적(動的) 거동(擧動)을 나타낸 Kalman filter와 자기공진(自己共振) 예측자(豫測子)의 순환(循還) 알고리즘에 의한 예측방법(豫測方法)을 연구(硏究)하여 하천유출(河川流出) 예측(豫測)에의 적용성(適用性)을 검토(檢討)하고 그 결과(結果)를 제시하였다. 강우(降雨)-유출과정(流出過程)의 동적(動的) 거동(擧動)을 자색(白色) Gaussian 잡음(雜音)이 있는 선형(線型), 이산형(離散型)시스템으로 보아서 낮은 차수(次數)의 ARMA 과정(過程)으로 나타내었으며 예측모형(豫測模型)의 상태(狀態)벡터를 random walk로 나타내었다. 예측오차(豫測誤差)에 대한 통계적(統計的)인 분석(分析)으로 모형구조(模型構造)를 결정하였으며 적용(適用)된 예측(豫測)알고리즘의 검정(檢正)을 위하여 시우량(時雨量)과 시유량(時流量)의 과거(過去) 기록치(記錄値)를 사용하였다. 예측결과(豫測結果)를 분석(分析)하나 Kalman filter에 의한 알고리즘이 자기공진(自己共振) 예측자(豫測子)보다 우수하다는 것을 알 수 있었다.

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Adaptive-length pendulum smart tuned mass damper using shape-memory-alloy wire for tuning period in real time

  • Pasala, Dharma Theja Reddy;Nagarajaiah, Satish
    • Smart Structures and Systems
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    • 제13권2호
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    • pp.203-217
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    • 2014
  • Due to the shift in paradigm from passive control to adaptive control, smart tuned mass dampers (STMDs) have received considerable attention for vibration control in tall buildings and bridges. STMDs are superior to tuned mass dampers (TMDs) in reducing the response of the primary structure. Unlike TMDs, STMDs are capable of accommodating the changes in primary structure properties, due to damage or deterioration, by tuning in real time based on a local feedback. In this paper, a novel adaptive-length pendulum (ALP) damper is developed and experimentally verified. Length of the pendulum is adjusted in real time using a shape memory alloy (SMA) wire actuator. This can be achieved in two ways i) by changing the amount of current in the SMA wire actuator or ii) by changing the effective length of current carrying SMA wire. Using an instantaneous frequency tracking algorithm, the dominant frequency of the structure can be tracked from a local feedback signal, then the length of pendulum is adjusted to match the dominant frequency. Effectiveness of the proposed ALP-STMD mechanism, combined with the STFT frequency tracking control algorithm, is verified experimentally on a prototype two-storey shear frame. It has been observed through experimental studies that the ALP-STMD absorbs most of the input energy associated in the vicinity of tuned frequency of the pendulum damper. The reduction of storey displacements up to 80 % when subjected to forced excitation (harmonic and chirp-signal) and a faster decay rate during free vibration is observed in the experiments.

A Study on Path Planning Algorithm of a Mobile Robot for Obstacle Avoidance using Optimal Design Method

  • Tran, Anh-Kim;Suh, Jin-Ho;Kim, Kwang-Ju;Kim, Sang-Bong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.168-173
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    • 2003
  • In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

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A Neural Network and Kalman Filter Hybrid Approach for GPS/INS Integration

  • Wang, Jianguo Jack;Wang, Jinling;Sinclair, David;Watts, Leo
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.277-282
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    • 2006
  • It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

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