A long short-term memory neural network approach for the hardware-in-the-loop simulation of diesel generator sets

Wang, Jianlin

doi:10.1177/0020294019883402

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…24,25 Since the two requirements are in conflict, we are interested in achieving a good balance between coverage and specificity. 26 Therefore, we can resort to a two-objective optimization problem and look at the resulting pareto front. 27 One can consider the aggregation of the two requirements, which can be succinctly completed as a product of coverage and specificity,…”

Section: Systematic Samplingmentioning

confidence: 99%

Granular data modeling and analysis based on optimized subsets of data

Dong

Wang

et al. 2022

Measurement and Control

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The study proposes a way of developing granular models based on optimized subsets of data with different sampling sizes, in which three generally used models, namely Support Vector Machine, K-Nearest Neighbor, and Long Short-Term Memory, are designed and transformed into granular version for achieving a good performance with sufficient functionality. First, a collection of subsets are determined using different sampling methods, which are subsequently applied to play as an essential prerequisite of the proposed models. Then, the principle of justifiable granularity is utilized to the design of interval information granules based on the subsets of data. The design process is associated with a well-defined optimization problem realized by achieving a sound compromise between two conflicting criteria: coverage and specificity. To evaluate the performance of the granular models, two aspects are considered: (i) sampling methods used in determining suitable subsets of data; (ii) different models applied to be transformed into granular models. A series of experimental studies are conducted to verify the feasibility of the proposed granular models.

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Section: Systematic Samplingmentioning

confidence: 99%

Granular data modeling and analysis based on optimized subsets of data

Dong

Wang

et al. 2022

Measurement and Control

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“…In addition, HIL simulator is widely used in various industries because it can perform evaluation of various test conditions with high reliability in a short time. [12][13][14][15] Due to the reliability of HIL simulator and the shortening of the development period, the most research cases in the automotive industry have been published. [16][17][18][19][20][21][22][23][24] As the automobile industry is advanced, various control functions are added and HIL simulator is the most widely applied industrial field to reflect it in products.…”

Section: Introductionmentioning

confidence: 99%

Development and verification of individual motor control technology to improve the driving performance of independently rotating wheel type railway vehicle using hardware-in-the-loop (HIL) Simulator

Cho¹

2020

Measurement and Control

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In order to realize the tram’s low-floor structure, most of the trams that have been recently introduced adopt an independently rotating wheelset. In the case of trains driving in two regions with different gauges, an independently rotating wheelset may be applied to utilize the variable track technology. Since the independent rotation type wheelset has no rotational restraint of the left and right wheels, the difference in rotational speed between the outer and inner wheels occurs naturally during curved driving, and it is applied to railroad vehicles traveling in sharp curve sections because it smoothly drives curved driving. However, the longitudinal creep force and the lateral restoring force are weakened as the left and right rotational constraints disappear. Lack of lateral direction restoring force weakens stability while causing continuous flange contact driving or zigzag phenomenon against disturbance. Under the conditions of driving in a sharp curve, these railway vehicles generate excessive wear, noise, and lateral pressure, as well as deterioration of ride comfort and derailment. In order to overcome these drawbacks, a method has been proposed in which the torque of a motor mounted on each wheel is individually controlled to generate lateral restoring force or to improve driving performance through lateral displacement control using a yaw moment. In this paper, development using HIL (hardware in the loop) simulator was performed to check the performance and stability of the individual motor torque control technology before verifying by applying the individual motor torque control to the actual vehicle. HIL simulator were constructed by combining a real-time dynamic analysis model of a railway vehicle with a drive motor to which real individual motor control was applied. Under the conditions of driving the test track where the actual test vehicle was tested, the analysis of the driving characteristics and the control characteristics of the disturbance was performed to confirm the proposed individual motor torque control performance.

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A long short-term memory neural network approach for the hardware-in-the-loop simulation of diesel generator sets

Cited by 2 publications

References 40 publications

Granular data modeling and analysis based on optimized subsets of data

Granular data modeling and analysis based on optimized subsets of data

Development and verification of individual motor control technology to improve the driving performance of independently rotating wheel type railway vehicle using hardware-in-the-loop (HIL) Simulator

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