Safety Verification of IEC 61131-3 Structured Text Programs

Xiong, Jiawen; Bu, Xiangxing; Huang, Yanhong; Shi, Jian; He, Weigang

doi:10.1109/tii.2020.2999716

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…Rawlings et al [56] use symbolic model checking tools st2smv and SynthSMV to verify and falsify a ST program controlling batch reactor systems. Xiong et al [21] use the behavior model (BM) to specify the behavior of ST programs, and provide an method based on automatic theoretical to verify LTL attributes on BM. Our work differs from them because these works attempt to transformed PLC programs into intermediate languages or other programming language which are suitable for verifying or detecting potential issues in associated versifiers or checkers lack analysis and proof of equivalence in the conversion process, and the analysis they can perform is very limited.…”

Section: Related Workmentioning

confidence: 99%

“…This has motivated a surge of research on analyzing and verifying PLC programs [7], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], although few work focuses on ST implementations/compilers. Specifically, Zhang et al [22] propose VetPLC, a temporal context-aware, program-based approach to produce timed event sequences that can be used for automatic safety vetting.…”

Section: Introductionmentioning

confidence: 99%

“…In [25], the proposed method transforms IL to Petri-nets [29], and manually builds two additional Petri-nets for modeling the PLC and its environment. Xiong et al [21] propose an algorithm based on variable state analysis for automatically extracting the behavior model (BM) from an ST program. These works attempt to transform PLC programs into an intermediate language or another programming language (i.e., C) which is suitable for verifying or detecting potential issues using existing associated verifiers or checkers.…”

Section: Introductionmentioning

confidence: 99%

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K-ST: A Formal Executable Semantics of PLC Structured Text Language

Wang¹,

Wang²,

Poskitt³

et al. 2022

Preprint

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Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). However, a lack of formal semantics makes it difficult to ascertain the correctness of their translators and compilers, which vary from vendor-to-vendor. In this work, we develop K-ST, a formal executable semantics for ST in the K framework. Defined with respect to the IEC 61131-3 standard and PLC vendor manuals, K-ST is a high-level reference semantics that can be used to evaluate the correctness and consistency of different ST implementations. We validate K-ST by executing 509 ST programs extracted from Github and comparing the results against existing commercial compilers (i.e., CODESYS, CX-Programmer, and GX Works2). We then apply K-ST to validate the implementation of the open source OpenPLC platform, comparing the executions of several test programs to uncover five bugs and nine functional defects in the compiler.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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K-ST: A Formal Executable Semantics of PLC Structured Text Language

Wang¹,

Wang²,

Poskitt³

et al. 2022

Preprint

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show abstract

“…These were collecting and selecting raw data tasks managed by the edge server using IEC 61131-3 standard, which is run on PLCs. The IEC 61131-3 standard is a widely accepted international standard for PLCs and specifies five programming languages: LD, FBD, Instruction List (IL), SFC, and ST [13]. The ST programming language is used in this research.…”

Section: System Overviewmentioning

confidence: 99%

Forecasting PM2.5 Concentration Using a Single-Dense Layer BiLSTM Method

et al. 2021

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In recent times, particulate matter (PM2.5) is one of the most critical air quality contaminants, and the rise of its concentration will intensify the hazard of cleanrooms. The forecasting of the concentration of PM2.5 has great importance to improve the safety of the highly pollutant-sensitive electronic circuits in the factories, especially inside semiconductor industries. In this paper, a Single-Dense Layer Bidirectional Long Short-term Memory (BiLSTM) model is developed to forecast the PM2.5 concentrations in the indoor environment by using the time series data. The real-time data samples of PM2.5 concentrations were obtained by using an industrial-grade sensor based on edge computing. The proposed model provided the best results comparing with the other existing models in terms of mean absolute error, mean square error, root mean square error, and mean absolute percentage error. These results show that the low error of forecasting PM2.5 concentration in a cleanroom in a semiconductor factory using the proposed Single-Dense Layer BiLSTM method is considerably high.

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Design of a smart control system for the management of sustainable energy supplies in remote areas: A case study

KASAPBAŞI

Canbolat

2022

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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Safety Verification of IEC 61131-3 Structured Text Programs

Cited by 6 publications

References 20 publications

K-ST: A Formal Executable Semantics of PLC Structured Text Language

K-ST: A Formal Executable Semantics of PLC Structured Text Language

Forecasting PM2.5 Concentration Using a Single-Dense Layer BiLSTM Method

Design of a smart control system for the management of sustainable energy supplies in remote areas: A case study

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