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Method of time Petri net analysis for analysis of fault trees with time dependencies

IEE PROCEEDINGS-COMPUTERS AND DIGITAL TECHNIQUES 2002年第6期149卷 257-271页

作者： Magott, J Skrobanek, P Wroclaw Tech Univ Inst Engn Cybernet PL-50370 Wroclaw Poland

In order to make computer-aided control systems as safe as possible, a number of analysis techniques have been developed. One of these is fault tree analysis. A fault tree (FT) represents causal and generalisation relations between events (e.g. a hazard and its causes). However, it can express neither time relations between events nor detection and protection times. Time Petri nets (TPNs) can model all the above aspects. Thus, TPNs can be used for analysing and verifying time-dependent fault trees (FTs). One of the limitations of classical TPN analysis is the large number of TPN states. Even for a small FT this number can turn out to be vast. The authors introduce a new method for analysing such TPNs that model FTs. We do not consider all states that are reachable from the initial marking in classical TPN analysis but only those that lead to the occurrence of a hazard. Such an approach simplifies the procedure and results in cleaner final conclusions. If the hazard is reachable there is a need for safety measures to be taken. FT analysis and modelling of protection using TPNs will be illustrated using an example.

关键词： computer-aided control systems Petri net analysis Reliability theory time Petri net Combinatorial mathematics TPNs Petri nets fault trees fault tree analysis Maintenance and reliability control engineering computing computerised control

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Reduced switch multilevel inverter for performance enhancement of induction motor drive with intelligent rotor resistance estimator

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IET POWER ELECTRONICS 2015年第12期8卷 2444-2453页

作者： Chitra, A. Himavathi, S. VIT Univ Sch Elect Engn Vellore 632014 Tamil Nadu India Pondicherry Engn Coll Dept Elect & Elect Engn Pondicherry 605014 India

Multilevel inverters (MLI) are suitable for renewable energy sources as they operate at lower switching frequency and voltage. The sinusoidal PWM (SPWM) techniques are popularly employed in MLIs to improve the drive performance. However as the number of switches increase it leads to more switching losses, higher price and size of the inverter. In this study, a modified reduced switch MLI (RSMLI) with five switches is proposed. Various multilevel inverter topologies with different multicarrier SPWM techniques such as phase disposition, phase opposition disposition, and alternative phase opposition disposition (APOD) are derived, analysed and presented for the proposed RSMLI. All the inverter topologies are simulated and the scheme with lowest THD is identified. The hardware setup is built for the proposed RSMLI using F28335 digital signal processor (DSP) for pulse generation and the results are validated. The vector control scheme of industrial standard requires an accurate and fast R-r estimator for stable performance. Neural based R-r estimator proposed by the authors is implemented on FPGA. The proposed RSMLI fed induction motor drive is examined with and without the neural based R-r estimator. Encouraging results obtained using the proposed RSMLI are reported.

关键词： induction motor drives machine vector control control engineering computing electric machine analysis computing PWM invertors digital signal processing chips field programmable gate arrays rotors reduced switch multilevel inverter performance enhancement RSMLI fed induction motor drive intelligent rotor resistance estimator renewable energy sources switching frequency switching voltage sinusoidal PWM techniques MLI drive performance improvement switching losses higher price modified reduced switch MLI multicarrier SPWM techniques phase disposition phase opposition disposition alternative phase opposition disposition APOD F28335 digital signal processor DSP pulse generation vector control scheme industrial standard FPGA

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Deep reinforcement learning based active safety control for distributed drive electric vehicles

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第6期16卷 813-824页

作者： Wei, Hongqian Zhao, Wenqiang Ai, Qiang Zhang, Youtong Huang, Tianyi Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China

Distributed drive electric vehicles are regarded as the promising transportation due to the advanced power flow architecture. Optimizing the yaw motion to enhance vehicle safety is a challenging job. Besides, the nonlinear features in vehicles affect the control accuracy of the yaw motion controllers. To this end, a deep reinforcement learning (DRL) based direct yaw moment control (DYC) strategy is put forward here. Vehicle dynamics can be approximated with the DRL algorithm, which reduces the complex nonlinear solving process. Concretely, the DYC problem is formulated as Markov Decision Process in which the observed signals and external yaw moment are incorporated as the state and action sets. Thereupon, actor-critic network is exhibited to approximate action-value function and policy function for better control performance. Furthermore, to guarantee the continuous solution of external yaw moment, the deep deterministic policy gradient algorithm is employed, in which target and online network parameters are simultaneously trained to maintain learning process stability. The proposed DRL based DYC strategy is verified using the Carsim/Simulink platform under the typical lane change manoeuvres. Numerical test results demonstrate that the proposed DYC strategy outperforms the linear approaches on taking full advantage of understeer features and enhancing the lateral stability, especially under the critical steering manoeuvres.

关键词： steering systems external yaw moment electric vehicles road vehicles DYC problem nonlinear features deep learning (artificial intelligence) control performance control engineering computing Markov decision process optimisation deep deterministic policy gradient algorithm Carsim platform complex nonlinear solving process yaw motion controllers DRL algorithm learning process stability road safety vehicle safety critical steering manoeuvres DYC strategy reinforcement learning deep reinforcement learning distributed drive electric vehicles lateral stability vehicle dynamics stability motion control Markov processes control accuracy active safety control Simulink platform gradient methods direct yaw moment control strategy advanced power flow architecture approximate action-value function traffic engineering computing

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ONLINE COMPUTER control OF LINEAR-MULTIVARIABLE SYSTEMS BY OUTPUT FEEDBACK

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PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON 1974年第9期121卷 1025-1030页

作者： SANDOZ, DJ STEINER, DJ Department of Electrical Engineering & Electronics University of Liverpool Liverpool UK Department of Industrial Management & Engineering Massey University Palmerston North New Zealand

This paper derives a minimal representation of linear multivariable systems on the basis of input and output records. Two optimal-control algorithms are established from the minimal structure. The algorithms generate a minimum-time response and a general-optimal response, respectively. The latter is based on minimisation of a quadratic cost criterion. A description of an online implementation of the minimum-time controller is presented. A 4th-order servo system is used for the study. A recursive least-squares procedure is applied to model process dynamics for controller design. It is demonstrated that incorporation of auxiliary error feedback reduces the requirement for accurate knowledge of process parameters.

关键词： multivariable control systems fourth order servo system linear multivariable systems process dynamics auxiliary error feedback optimal control minimal representation Optimal control output feedback Multivariable control systems algorithms control engineering applications of computers control engineering computing linear systems online computer control online operation

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ELECTRICAL INTERLOCK DESIGN FOR COMPLEX HIGH-POWER SWITCHING NETWORKS

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PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON 1979年第2期126卷 152-158页

作者： LIDGATE, D AITCHISON, PW ACOCK, D CENT ELECTR GENERATING BOARD DIV GENERAT DEV & CONSTRUCTBARNWOODNJ

The paper reviews the derivation of interlock logic and the resultant interlock circuits for conventional double-busbar substations. These methods are then shown to be inadequate when the number of operating constraints on each switch and the degree of network interconnection are increased. A new method of deriving the interlock logic that can be converted directly into hard-wired form is then presented. The application of this method to the Dinorwic pumped storage scheme is given as an example. The ways by which conflicts between safety and operating requirements can be overcome are then described. Finally, the methods by which such complex interlock logic may be checked are discussed and examples given of the application of decision tables to this task.

关键词： switching substations power system protection conventional double busbar substations interlock design complex high power switching networks Substations Power engineering computing Switchgear control engineering computing control of electric power systems Electric actuators and final control equipment busbars network interconnection safety pumped storage scheme interlock circuits interlock logic power system computer control Power system protection operating requirements

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Comparison of digital PWM control strategies for high-power interleaved DC-DC converters

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IET POWER ELECTRONICS 2018年第2期11卷 391-398页

作者： Calderon-Lopez, Gerardo Villarruel-Parra, Alejandro Kakosimos, Panagiotis Ki, Shu-Kong Todd, Rebecca Forsyth, Andrew J. Univ Manchester Sch Elect & Elect Engn Power Convers Grp Manchester Lancs England Texas A&M Univ Qatar Educ City Dept Elect & Comp Engn Doha Qatar

Three pulse-width-modulation (PWM) digital control approaches are evaluated to provide the current sharing between phases in high-power dual-interleaved DC-DC converters. The implementation of a digital peak current, multi-sample averaged current and an enhanced single-sample averaged current control in a TMS320F28377D is described. A summary of stability requirements is provided for designing the controllers and experimental results from a 60kW, 75kHz silicon carbide DC-DC converter are used to evaluate the steady-state and dynamic performance of the three control methods. Overall the best performance in terms of tracking and speed of response was achieved by the enhanced single-sample method. The multi-sampled technique provided the highest tracking accuracy, but at the expense of the slowest dynamic response. The fastest dynamic response was achieved by the digital peak current control, but this method is limited by poor noise immunity and instability for duty ratios in the region of 0.5.

关键词： DC-DC power convertors electric current control microcontrollers PWM power convertors digital control power engineering computing control engineering computing digital PWM control strategies digital pulse-width-modulation control strategies high-power dual-interleaved DC-DC converters current sharing digital peak current control multisample averaged current enhanced single-sample averaged current control TMS320F28377D stability requirements silicon carbide DC-DC converter enhanced single-sample method multisampled technique dynamic response duty ratios

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Current-sharing bus and fuzzy gain scheduling of proportional-integral controller to control a parallel-connected AC/DC converter

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IET POWER ELECTRONICS 2014年第10期7卷 2525-2532页

作者： Kanthaphayao, Yutthana Chunkag, Viboon Rajamangala Univ Technol Fac Engn & Architecture Solar Energy Res & Technol Training Ctr Dept Elect Engn Mueang Dist 11000 Nonthaburi Thailand King Mongkuts Univ Technol North Bangkok Dept Elect & Comp Engn Fac Engn Bangkok Thailand

In this study, a current-sharing bus and fuzzy gain scheduling of proportional-integral (PI) controller to control a parallel-connected AC/DC converter are proposed. A simple current-sharing circuit is applied to divide the load current to calculate the peak input current of each converter module. Fuzzy gain scheduling of PI controller is used to compensate for the error of the output voltage. The dsPIC30F6010 microcontroller is applied in the voltage loop control. In addition, a hysteresis control circuit is used to control the current loop. The experimental performance evaluation is conducted on a prototype, with three converter modules that are parallel-connected, has 250 W/module and has a -48 V DC output voltage. The system offers the following advantages: the tight output voltage regulates both the steady-state operation and the transient response. The current sharing is quite good, and it is simpler to operate in the redundant mode.

关键词： electric current control fuzzy control PI control AC-DC power convertors microcontrollers voltage control hysteresis transient response error compensation control engineering computing current-sharing bus fuzzy gain scheduling proportional-integral controller parallel-connected AC-DC converter load current division peak input current calculation output voltage error compensation dsPIC30F6010 microcontroller voltage loop control hysteresis control circuit current loop control experimental performance evaluation tight output voltage steady-state operation regulation transient response regulation voltage-48 V power 250 W

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Field programmable gate array implementation of wheel-rail contact laws

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IET control THEORY AND APPLICATIONS 2010年第2期4卷 303-313页

作者： Zhou, Y. J. Mei, T. X. Freear, S. Univ Leeds Sch Elect & Elect Engn Leeds W Yorkshire England Univ Salford Sch Comp Sci & Engn Salford M5 4WT Lancs England

This study presents the development of a field programmable gate array (FPGA)-based accelerator that is highly suited to the implementation of complex and computationally demanding control or real-time simulation tasks. The application studied in this article is for the real-time simulation of wheel-rail contact laws, which may be used for hardware-in-the-loop experimental studies of the latest active control technology for wheelset stabilisation and steering. The complex wheel-rail contact laws are implemented using a single FPGA chip that outperforms substantially modern general-purpose CPU or DSP in the aspects of processing time, configuration flexibility and cost. The algorithms are restructured to utilise the FPGA's parallel processing capability. Reusable IP core are used for the floating point operations. The scheduling of the operations is optimised to ensure effective and efficient use of the FPGA's resources.

关键词： FPGA general-purpose CPU FPGA chip Logic and switching circuits active control technology field programmable gate array-based accelerator stability Stability in control theory wheelset stabilisation hardware-in-the-loop parallel processing floating point operations control engineering computing field programmable gate arrays DSP control engineering computing railways steering Rail-traffic system control FPGA parallel processing capability

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Self-organizing traffic control using carrying capacity modelling in adjacent weaving sections

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IET INTELLIGENT TRANSPORT SYSTEMS 2023年第2期17卷 327-340页

作者： Ma, Qinglu Lu, Jiaping Zhang, Shu Yuan, Xinxin Ullah, Saleem Chongqing Jiaotong Univ Sch Traff & Transportat Chongqing 400074 Peoples R China Chongqing Key Lab Human Vehicle Rd & Safety Mt Co Chongqing Peoples R China Khwaja Fareed Univ Sch Engn & Informat Technol Rahim Yar Khan Pakistan

The traffic carrying capacity of the road network is limited. When the limit is exceeded, traffic congestion will restrict the control and development of transportation systems. This paper aims to determine the connotation of traffic carrying capacity in some adjacent weaving sections (AWS) and put forward a novel calculation model for self-organizing carrying capacity. Firstly, the in-depth analysis found that each weaving section has a local-whole and interactive relationship with AWS. Secondly, the self-organizing critical state of AWS is analyzed by calculating the threshold from slow to congestion. Finally, the Renhe Interchange was used as an experimental object to study the carrying capacity under the self-organizing critical state of AWS. The VISSIM software and Microsoft Visual Studio 2020-C# software are employed to verify the model. The self-organizing critical occupancy rate before the optimization is 38.60%, and the carrying capacity is 7527 pcu/h. After optimization, the self-organizing critical occupancy rate is 48.70%, and the carrying capacity is 9497 pcu/h. The results show that the model can simulate the carrying capacity of self-organized criticality. It can also provide a basis for urban managers to maintain the stable development of the system and ensure the overall operation quality of the AWS.

关键词： traffic engineering computing transportation traffic control traffic congestion Microsoft Visual Studio 2020-C# software self-organized criticality Renhe Interchange self-organised criticality control engineering computing road traffic control self-organizing carrying capacity modelling Traffic engineering computing AWS VISSIM software critical occupancy rate Road-traffic system control road network adjacent weaving sections critical state traffic carrying capacity self-organizing traffic control

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Spatio-temporal adaptive graph convolutional networks for traffic flow forecasting

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IET INTELLIGENT TRANSPORT SYSTEMS 2023年第4期17卷 691-703页

作者： Ma, Qiwei Sun, Wei Gao, Junbo Ma, Pengwei Shi, Mengjie Shanghai Maritime Univ Sch Informat Engn Shanghai 201306 Peoples R China Shandong Jianzhu Univ Sch Management Engn Jinan Shandong Peoples R China

Accurate forecasting of traffic flow is crucial for intelligent traffic control and guidance. It is very challenging to forecast the traffic flow due to the high non-linearity, complexity and dynamicity of the data. Most existing forecasting methods focus on designing complicated graph neural network architectures to capture the spatio-temporal features of traffic data with the help of predefined graphs. However, traffic data exhibit a strong spatial dependency, which means that there are often complex correlations between nodes in a road network topology graph. Moreover, the spatial correlations of the road network change over time. To capture the properties of the road network topology graph, a novel spatio-temporal adaptive graph convolutional networks model (STAGCN) based on deep learning is proposed. Utilize adaptive graph generation block to capture the static and dynamic structures of the traffic road network respectively, and they are integrated to construct an adaptive road network topology graph. Then the spatio-temporal features of the traffic data are captured using spatio-temporal convolution blocks. Experiments were conducted on publicly available traffic datasets for freeway traffic in California, USA, and the results showed that the prediction accuracy of the STAGCN model outperformed multiple baseline methods.

关键词： traffic engineering computing complicated graph neural network architectures freeway traffic traffic flow graph neural networks intelligent traffic control spatio-temporal adaptive graph convolutional networks model Neural nets Regression analysis control engineering computing convolutional neural nets road traffic control spatio-temporal features Traffic engineering computing deep learning (artificial intelligence) spatiotemporal phenomena Computational complexity Road-traffic system control regression analysis intelligent transportation systems predefined graphs road network change adaptive graph generation block spatio-temporal convolution blocks adaptive road network topology graph forecasting methods traffic data publicly available traffic datasets traffic road network complex correlations computational complexity Combinatorial mathematics

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