32 results about "Hybrid automaton" patented technology

The invention provides a high speed regular expression matching hybrid system and method based on FPGA and NPU (field programmable gate array and network processing unit); the system is mainly composed of an FPGA chip and a multicore NPU; a plurality of parallel hardware matching engines are implemented on the FPGA chip, a plurality of software matching engines are instantiated on the NPU, and the hardware engines and the software engines operate in running water manner. In addition, a high speed RAM (random-access memory) on the FGPA chip and an off-chip DDR3 SDARM (double-date-rate three synchronous dynamic random-access memory) are used to construct two-level storage architecture; secondly, a regular expression rule set is compiled to generate a hybrid automaton; thirdly, state table items of the hybrid automaton are configured; fourthly, network messages are processed. The high speed regular expression matching hybrid system and method based on FPGA and NPU have the advantages that matching performance under complex rule sets is improved greatly, and the problem that the complex rule sets have poor performance is solved.

The present disclosure relates to exemplary embodiments of method, computer-accessible medium, system and software arrangements for, e.g., Cancer Hallmark Automata, a formalism to model the progression of cancers through discrete phenotypes (so-called hallmarks). The precise computational model described herein includes the automatic verification of progression models (e.g., consistency, causal connections, etc.), classification of unreachable or unstable states (e.g., “anti-hallmarks”) and computer-generated (individualized or universal) therapy plans. Exemplary embodiments abstractly model transition timings between hallmarks as well as the effects of drugs and clinical tests, and thus allows formalization of temporal statements about the progression as well as notions of timed therapies. Certain exemplary models discussed herein can be based on hybrid automata (e.g., with multiple clocks), for which relevant verification and planning algorithms exist.

The invention provides a CPS modeling and property verification method based on a possibility space-time hybrid automaton. The verification method comprises the steps that 1, the possibility space-time hybrid automaton and a cyber-physical system (CPS) are determined; 2, the properties of the possibility space-time CPS are verified. The method is based on a possibility space-time hybrid automaton model and used for modeling of the CPS, a description language of the possibility space-time CPS is given to be used for verifying and measuring system responsiveness, regular security and other properties, the effectiveness of the CPS modeling and property verification and measurement method in an uncertain environment is verified in terms of theory and instance, and a theoretical basis is provided for intelligent control and optimization of the complicated CPS.

The invention discloses a CPS rare event probability prediction method based on statistical model inspection. The system is based on a statistical model inspection method and is composed of a samplingmonitor, a protocol verifier and a probability predictor. The method comprises the specific implementation steps that a sampling monitor adopts an importance random sampling algorithm to randomly sample and generate a CPS system state feature sequence described based on a hybrid automaton; a protocol verifier based on linear temporal logic can generate a system visible characteristic state sequence and a verification result corresponding to protocol satisfaction, and the verifier can take the verification result as a training sample set of a probability predictor based on an HMM implicit Markov model; on the basis of sufficient sample set learning, the probability predictor calculates the probability that the subsequent state of the system is a rare event state, and outputs the result, inaddition, the method also has the function of correcting the prediction capability of the predictor by using the probability prediction result.

The invention provides a reachability analysis method of a hybrid system. The reachability analysis method comprises the following steps that input files of a hybrid automaton are analyzed, and the bounded figure structure of the automaton is encoded into a propositional logic formula set; an SAT solver is used for solving the formula set, if the formula set can not be solved, an output result is insoluble, and if the output result is soluble, an assignment capable of being met is decoded to be a path on the figure structure of the automaton; a target path is encoded to form linear constraint according to the meaning of the hybrid automaton; the linear constraint is solved, if the linear constraint is soluble, the path is output as a result, and if the linear constraint is insoluble, a next step is turned; an irreducible and insoluble set of the linear constraint is given; an unreachable path is encoded into the propositional logic formula set and then is added into the formula set of the figure structure of the automaton. The reachability analysis method is used so that the candidate path for reaching a target node can be quickly found out, and the time for searching the figure structure of the hybrid automaton can be shortened.

The invention discloses an SHA-based spacecraft ACS mission life prediction method and belongs to the technical field of spacecraft attitude control. The method carries out life prediction based on astochastic hybrid automaton, and simulates stochastic hybrid motion of a spacecraft ACS during in-orbit operation, and the lift predication result is not only based on system reliability, but also takes constraint of system performance degradation on life into consideration, so that the limitation that a traditional life prediction method can only predict the life from the perspective of reliability is overcome, and the predicted result is more in line with requirements of space missions.

The invention discloses a hybrid modeling method of an ECPT system with a load self-adaption characteristic. The method comprises the following steps: according to the on/off conditions of a switchingtube S, a diode D and switching tubes S1-S4 of a full-bridge inverter, setting a plurality of working modes for the ECPT system, and determining a state space equation corresponding to each working mode; determining the boundary conversion conditions among the working modes according to the boundary conversion conditions of a Buck converter and the boundary conversion conditions of the full-bridge inverter, and establishing a hybrid automaton model of the ECPT system according to the state space equation corresponding to each working mode and the conversion conditions among the working mode.The ECPT system model established through the method provided by the invention is more accurate, can simplify a control problem of the ECPT system into a boundary calculation and selection problem, and provides a new idea for realizing the control of the ECPT system with the load adaptive characteristic.

The invention discloses a CPS-oriented AADL expansion modeling language and a conversion method for converting the CPS-oriented AADL expansion modeling language into a weighted probability hybrid automaton. An AADL is used for modeling an information system, probability and weight properties are added through an AADL behavior attachment function, and Modelica is used for modeling a physical system. As the AADL expansion modeling language is a semi-formalized model, the AADL expansion modeling language is converted into a formalized automaton model through conversion rules and algorithms. Aiming at the characteristics of probability events and resource consumption of an information physical fusion system, a weighted probability hybrid automaton is adopted as a formalized model, and the formalized model has probability uncertainty and weight measurement properties. Finally, mutual simulation verification is performed on the two models to ensure the mutual simulation equivalence of the two models, namely the result consistency of subsequent verification work is ensured. According to the method, the information physical fusion system with uncertainty and resource consumption can be modeled, and the model can be used for subsequent model detection and reliability verification work.

The invention discloses a comprehensive passenger transport hub group network modeling method based on a dynamic graph hybrid automaton. The method comprises the following steps: dividing a hub groupnetwork; dividing city/region ranges according to administrative regions, numbering the city/region ranges, classifying hub types of each city/region, and selecting a main hub and a branch hub; describing the hub group by using the graph, and establishing a topological network of the hub group, a dynamic graph hybrid automaton model of the single passenger transport hub and a parallel combinationmodel of a dynamic graph hybrid automation machine of the hub group network. Based on a dynamic graph and a hybrid automaton theory, a network model of a comprehensive passenger transport hub group isestablished, and a state space model of a hub group network is derived by taking passenger flow volume as a state quantity in a hub; therefore, an effective means is provided for estimating and predicting the passenger flow volume in the hub, a basis is provided for improving the integrated cooperative operation efficiency of the hub group and the optimal configuration of transport capacity resources, and an effective support is provided for guaranteeing the collecting, distributing and transporting capacity of the hub.

The invention relates to a logistics network optimization method based on a hybrid automata. The method comprises the following steps: 1) constructing a hybrid automata model of each device in the logistics network of an iron and steel enterprise; 2) the hybrid automata model of each device is extended to the whole process of steel production logistics optimization scheduling, and the hybrid automata model of steel enterprise logistics network scheduling system is constructed; 3) Optimize the hybrid automata model of the logistics network scheduling system of the iron and steel enterprise by using the graph search two-layer optimization algorithm; 4) the optimized model is used to optimize the scheduling of the steel enterprise logistics network, and the optimized scheduling scheme is obtained. Compared with the prior art, the invention scientifically and reasonably solves the problems of coordination and optimization in the optimization of the logistics network, which is conducive torealizing the maximization of the production profit and the comprehensive benefit of the production characteristic performance.

The invention discloses a micro-energy network state transition space modeling method based on a hybrid automaton. The method specifically comprises the following steps: (1) dividing a micro-energy network into an energy production unit, an energy transmission unit, an energy conversion unit, an energy storage unit and an energy consumption unit according to the structure of the micro-energy network; (2) respectively describing the operation states of the energy unit and the micro energy grid system; (3) establishing a state transition model of the energy unit based on the hybrid automaton; and (4) establishing a state transition model of the micro energy network system based on the hybrid automaton. According to the method, the operation state, the transfer condition and the transfer process of each energy unit of the micro-energy network can be accurately described, and staged management and optimization control of all the energy units of the micro-energy network in the whole process from starting, operation to stopping are facilitated.

The invention relates to a train dispatching operation danger prediction method and system based on runtime verification. The method comprises the steps: firstly building a train operation control parameterized model, then taking line engineering data, train operation data and a driving permission end point position as the input, calculating an invariant set, a flow condition and a migration condition among four operation states, and configuring the parameterized model to obtain an instantiated model; and subjecting the instantiated model to linearization to obtain a train operation control hybrid automaton model, a train operation control hybrid automaton model is obtained, finally, solving a train operation control hybrid automaton model through a polyhedral over-approximation hybrid automaton reachable set calculation algorithm to obtain a train operation reachable set, determining whether a train will be in danger or not according to the train operation reachable set, and before the dispatching command is issued, predicting whether the dispatching command can cause the danger of train operation, so that the safety and efficiency of dispatching operation are improved.

The invention discloses a mode-based letter fusion system modeling and verification method for a period controller, and the method comprises the steps: respectively constructing a discrete mode and a continuous mode on an abstract level, and a discrete control flow and a continuous control flow on a specific level through employing a letter fusion system modeling language; combining the obtained modeling models of the abstract layer and the specific layer to obtain a complete letter fusion system model, and representing the complete letter fusion system model in a graphical mode; and converting the variables, the discrete mode, the continuous mode, the discrete mode control flow and the continuous mode control flow in the obtained complete belief fusion system model into a hybrid automaton according to a translation rule, and carrying out formalized verification and property analysis. According to the method, an interface can be displayed in a graphical mode, a user can conveniently understand and establish a model, an effective bridge is also established between the model and a high-confidence formalized property verification tool, and time and cost for development of a belief fusion system model and high-confidence property verification are saved.