Petri net modeling and performance analysis of can fieldbus

The CAN FB (Controller Area Network FieldBus) has been in existence for ten years. It supports automated manufacturing and process control environments to interconnect intelligent devices such as valves, sensors, and actuators. CAN FieldBus has a high bit rate and the ability to detect errors. It is immune to noise and resistant to shock, vibration, and heat. Two recently introduced mechanisms, Distributed Priority Queue (DPQ) and Priority Promotion (PP) enable CAN FieldBus networks to share out the system bandwidth and grant ail upper bound on the transmission times so as to meet the requirements in real-time communications. Modeling and analysis of such networks are an important research area for their wide applications in manufacturing automation. This thesis presents a Petri net methodology which models and analyzes CAN FieldBus access protocol. A Reachability Graph of the Petri net model is -utilized to study the behavioral properties of the protocol. A timed Petri net simulator is used to evaluate the performance of the protocol. Performance measures include the completion time for successful events and operations. Operational parameters investigated using the Petri Net model are FieldBus speed, the length of each frame, and the number of frames in a message

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Methods: Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). Conclusion: The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller

Petri-net-based supervisory control of discrete event systems and their ladder logic diagram implementations

The last decade has witnessed rapid developments in computer technology, which inreturn, has found widespread applications in manufacturing systems, communicationnetworks, robots etc. Such systems are called Discrete Event Systems (DESs), in whichproperties such as non-determinism, conflict and parallelism are exhibited. As DESsbecome more complex, the need for an effective design tool and its implementationbecomes more important. Supervisory control theory, based on finite state machines(FSM) and formal languages, is a well established framework for the study of DESs. Insupervisory control, given a model of the system and the desired system behaviourspecifications, the objective is to find a supervisor (controller) such that the controlledbehaviour of the system does not contradict the specifications given and does notunnecessarily constrain the behaviour of the system. In general, the classes ofspecifications that have been considered within the supervisory control fall into twocategories: the forbidden state problem, in which the control specifications are expressedas forbidden conditions that must be avoided, and the desired string problem, in whichthe control specifications are expressed as sequence of activities that must be provided.In supervisory control, there are some problems when using FSMs as an underlyingmodelling tool. Firstly, the number of states grows exponentially as the system becomesbigger. Secondly, FMSs lack from graphical visivalisation. To overcome these problemsPetri nets have been considered as an alternative modelling tool for the analysis, designand implementation of such DESs, because of their easily understood graphicalrepresentation in addition to their well formed mathematical formalism.The thesis investigates the use of Petri nets in supervisory control. Both the forbiddenstate problem and the desired string problem are solved. In other words, this workpresents systematic approaches to the synthesis of Petri-nets-based supervisors(controllers) for both the forbidden state problem and the desired string problem andintroduces the details of supervisory design procedures. The supervisors obtained are the form of a net structure as oppose to supervisors given as a feedback fiinction. Thismeans that a controlled model of the system can be constructed and analysed using thetechniques regarding to Petri net models.In particular the thesis considers discrete manufacturing systems. The results obtainedcan be applied to high level control of manufacturing systems, where the role of thesupervisor is to coordinate the control of machines, robots, etc. and to low-level controlof manufacturing systems, where the role of the supervisor is to arrange low-levelinteractions between the control devices, such as motors, actuators, etc.An approach to the conversion from the supervisors to ladder logic diagrams (LLDs)for implementation on a programmable logic controller (PLC) is proposed. A discretemanufacturing system example is then considered. The aim of this is to illustrate theapplicability, strengths and drawbacks of the design techniques proposed

Consistency and Sensitivity Analysis of Multi-level Petri Net Models of Biological Systems

The recent developments in biological experiments have awarded the research community with valuable information, which describe finely regulated systems that govern the cell dynamics. One of the greatest challenges, however, remains to represent this extensive amount of knowledge in a proper way that can be used in simulations, and validated automatically, in order to understand the dynamics and ultimately achieve a desired behaviour for the system (cell) under control. Many tools and techniques have been proposed in the literature to address this important problem. In this research, the use of Petri nets for knowledge representation is investigated. The initial focus of this research is then to introduce a concept of consistency between Petri nets obtained from various knowledge sources. Two algorithms are provided to construct Petri net models for cell dynamics using data available in public domain biological database. The first algorithm generates a low-level model capturing protein- protein interactions and the second, produces a high-level model which describes pathway sequences and is considerably easier to analyze. Appropriate tests are developed to study consistency of such models. In the context of biological systems, diseases that alter cell dynamics, such as cancer, can be regarded as faults in the system, and disease diagnosis and treatment will correspond to fault detection and control. In this research a framework has been proposed for sensitivity analysis in Petri net representation of biological systems. Efficient tools and procedures are developed to achieve sensitivity analysis. It is demonstrated using actual biological system models, that the results of such analysis can be used as a basis of drug discovery

Fluidization of Petri nets to improve the analysis of Discrete Event Systems

Las Redes de Petri (RdP) son un formalismo ampliamente aceptado para el modelado y análisis de Sistemas de Eventos Discretos (SED). Por ejemplo sistemas de manufactura, de logística, de tráfico, redes informáticas, servicios web, redes de comunicación, procesos bioquímicos, etc. Como otros formalismos, las redes de Petri sufren del problema de la ¿explosión de estados¿, en el cual el número de estados crece explosivamente respecto de la carga del sistema, haciendo intratables algunas técnicas de análisis basadas en la enumeración de estados. La fluidificación de las redes de Petri trata de superar este problema, pasando de las RdP discretas (en las que los disparos de las transiciones y los marcados de los lugares son cantidades enteras no negativas) a las RdP continuas (en las que los disparos de las transiciones, y por lo tanto los marcados se definen en los reales). Las RdP continuas disponen de técnicas de análisis más eficientes que las discretas. Sin embargo, como toda relajación, la fluidificación supone el detrimento de la fidelidad, dando lugar a la pérdida de propiedades cualitativas o cuantitativas de la red de Petri original. El objetivo principal de esta tesis es mejorar el proceso de fluidificación de las RdP, obteniendo un formalismo continuo (o al menos parcialmente) que evite el problema de la explosión de estados, mientras aproxime adecuadamente la RdP discreta. Además, esta tesis considera no solo el proceso de fluidificación sino también el formalismo de las RdP continuas en sí mismo, estudiando la complejidad computacional de comprobar algunas propiedades. En primer lugar, se establecen las diferencias que aparecen entre las RdP discretas y continuas, y se proponen algunas transformaciones sobre la red discreta que mejorarán la red continua resultante. En segundo lugar, se examina el proceso de fluidificación de las RdP autónomas (i.e., sin ninguna interpretación temporal), y se establecen ciertas condiciones bajo las cuales la RdP continua preserva determinadas propiedades cualitativas de la RdP discreta: limitación, ausencia de bloqueos, vivacidad, etc. En tercer lugar, se contribuye al estudio de la decidibilidad y la complejidad computacional de algunas propiedades comunes de la RdP continua autónoma. En cuarto lugar, se considera el proceso de fluidificación de las RdP temporizadas. Se proponen algunas técnicas para preservar ciertas propiedades cuantitativas de las RdP discretas estocásticas por las RdP continuas temporizadas. Por último, se propone un nuevo formalismo, en el cual el disparo de las transiciones se adapta a la carga del sistema, combinando disparos discretos y continuos, dando lugar a las Redes de Petri híbridas adaptativas. Las RdP híbridas adaptativas suponen un marco conceptual para la fluidificación parcial o total de las Redes de Petri, que engloba a las redes de Petri discretas, continuas e híbridas. En general, permite preservar propiedades de la RdP original, evitando el problema de la explosión de estados