Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications.Although there is an extensive literature on qualitative properties such as safety and liveness,there is still a lack of quantitative and uncertain property verifications for these systems.In uncertain environments,agents must make judicious decisions based on subjective epistemic.To verify epistemic and measurable properties in multi-agent systems,this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge(FCTLK).We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy epistemic interpreted systems.In addition,we provide a transformation algorithm from fuzzy epistemic interpreted systems to fuzzy Kripke structures,as well as transformation rules from FCTLK formulas to Fuzzy Computation Tree Logic(FCTL)formulas.Accordingly,we transform the FCTLK model checking problem into the FCTL model checking.This enables the verification of FCTLK formulas by using the fuzzy model checking algorithm of FCTL without additional computational overheads.Finally,we present correctness proofs and complexity analyses of the proposed algorithms.Additionally,we further illustrate the practical application of our approach through an example of a train control system.

Modeling and Control of a Continuous Stirred Tank Reactor Based on a Mixed Logical Dynamical Model

A novel control strategy for a continuous stirred tank reactor(CSTR)system,which has the typical characteristic of strongly pronounced nonlinearity,multiple operating points,and a wide operating range,is initiated from the point of hybrid systems.The proposed scheme makes full use of the modeling power of mixed logical dy- namical(MLD)systems to describe the highly nonlinear dynamics and multiple operating points in a unified framework as a hybrid system,and takes advantage of the good control quality of model predictive control(MPC) to design a controller.Thus,this approach avoids oscillation during switching between sub-systems,helps to relieve shaking in transition,and augments the stability robustness of the whole system,and finally achieves optimal(i.e. fast and smooth)transition between operating points.The simulation results demonstrate that the presented ap- proach has a satisfactory performance.

FUZZY COMPREHENSIVE EVALUATION MODEL OF ECOLOGICAL DEMONSTRATION AREA

Ecological demonstration area (EDA) is an authorized nomination, which should be assessed from several aspects, including ecological, social, environmental, economic ones and so on. It is difficult to advance an exact developing level index of EDA due to its indicator system’s complexity and disequilibrium. In this paper, a framework of indicators was set to evaluate, monitor and examine the comprehensive level of ecological demonstration area (EDA). Fuzzy logic method was used to develop the fuzzy comprehensive evaluation model (FCEM), which could quantitatively reveal the developing degree of EDA. Huiji District of Zhengzhou, Henan Province, one of the 9th group of national EDAs, was taken as a study case. The framework of FCEM for the integrated system included six subsystems, which were social, economic, ecological, rural, urban and accessorial description ones. The research would be valuable in the comprehensive quantitative evaluation of EDA and would work as a guide in the construction practices of Huiji ecological demonstration area.

Nonlinear inverse modeling of sensor based on back-propagation fuzzy logical system

Objective To correct the nonlinear error of sensor output,a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System(BP FS) is presented.Methods The BP FS is a computationally efficient nonlinear universal approximator,which is capable of implementing complex nonlinear mapping from its input pattern space to the output with fast convergence speed.Results The neuro-fuzzy hybrid system,i.e.BP FS,is then applied to construct nonlinear inverse model of pressure sensor.The experimental results show that the proposed inverse modeling method automatically compensates the associated nonlinear error in pressure estimation,and thus the performance of pressure sensor is significantly improved.Conclusion The proposed method can be widely used in nonlinearity correction of various kinds of sensors to compensate the effects of nonlinearity and temperature on sensor output.

Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System

Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.

Undulatory Theory with Paraconsistent Logic (Part I): Quantum Logical Model with Two Wave Functions

Paraconsistent logic (PL) is a non-classical logic that accepts contradiction in its foundations. It can be represented in the form of paraconsistent annotated logic with annotation of two values (PAL2v). When used to model quantum phenomena, PAL2v is called paraquantum logic (PQL). In this work, the concept of PQL is applied to create a logical model presenting the fundamental principles of quantum mechanics that support particle-wave theory. This study uses the well-known Young’s double-slit experiment, wherein quantum phenomena appear when a monochromatic light beam passes through the two slits. We focused on a reference point located between the slits, where we observed the effects of two types of wave interferences in a region defined as a two-wave region (2W region). Considering that the effect in this 2W region is very similar to that studied by Huygens, we adopt a paraquantum logical model in which a particle (or quantum) is represented by two wave functions. The two wave functions result in four State Vectors (Ket, Bra,,) in the PQL Lattice that express the symmetry and the entanglement of Quantum Mechanics. The constructed model adapts well to the quantum phenomena, is strongly consistent, and can be considered as an innovative form of analysis in the field of quantum mechanics. Based on this model, we present in two parts (Part I and Part II) the comparative analysis of values found in SchrÖdinger’s equation and probabilistic models of wave-particle theory using Bonferroni inequality.

A study of the logical model of capital market complexity theories

Analyzes the shortcomings of the classic capital market theories based on EMH and discloses the complexity essence of the capital market. Considering the capital market a complicated, interactive and adaptable dynamic system, with complexity science as the method for researching the operation law of the capital market, this paper constructs a nonlinear logical model to analyze the applied realm, focal point and interrelationship of such theories as dissipative structure theory, chaos theory, fractal theory, synergetics theory, catastrophe theory and scale theory, and summarizes and discusses the achievements and problems of each theory. Based on the research, the paper foretells the developing direction of eomplexity science in a capital market.

CONCEPTUAL MODELING BASED ON LOGICAL EXPRESSION AND EVOLVEMENT

Aiming at the problem of abstract and polytype information modeling in product conceptual design, a method of conceptual modeling based on logical expression and evolvement is presented. Based on the logic expressions of the product conceptual design information, a fimction/logic/strucmre mapping model is set up. First, the fimction semantics is transformed into logical expressions through fimction/logic mapping. Second, the methods of logical evolvement are utilized to describe the fimction analysis, fimction/strucmre mapping and structure combination. Last, the logical structure scheme is transformed into geometrical sketch through logic/structure mapping. The conceptual design information and modeling process are described uniformly with logical methods in the model, and an effective method for computer aided conceptual design based on the model is implemented.

A Probabilistic Paraconsistent Logical Model for Non-Relativistic Quantum Mechanics Using Interlaced Bilattices with Conflation and Bernoulli Distribution

In this work, we make a representation of non-relativistic quantum theory based on foundations of paraconsistent annotated logic (PAL), a propositional and evidential logic with an associated lattice FOUR. We use the PAL version with annotation of two values (PAL2v), named paraquantum logic (PQL), where the evidence signals are normalized values and the intensities of the inconsistencies are represented by degrees of contradiction. Quantum mechanics is represented through mapping on the interlaced bilattices where this logical formalization allows annotation of two values in the format of degrees of evidence of probability. The Bernoulli probability distribution is used to establish probabilistic logical states that identify the superposition of states and quantum entanglement with the equations and determine the state vectors located inside the interlaced Bilattice. In the proposed logical probabilistic paraquantum logic model (pPQL Model), we introduce the operation of logical conflation into interlaced bilattice. We verify that in the pPQL Model, the operation of logical conflation is responsible for providing a suitable model for various phenomena of quantum mechanics, mainly the quantum entanglement. The results obtained from the entanglement equations demonstrate the formalization and completeness of paraquantum logic that allows for interpretations of similar phenomena of quantum mechanics, including EPR paradox and the wave-particle theory.

An Exploration on Logical Ideas of System Architecture Modeling

China’s space technology has gradually improved from the early stages’ introduction, absorption and re-innovation based on backward design to independent innovation based on forward design. It is necessary to develop a new approach of systems engineering to improve the quality and efficiency of space systems design considering the large number of original design problems expected in the future. Adopting Model-Based Systems Engineering(MBSE) and Digital Twin method are important development initiatives in the field of modern engineering design. In the initial phase of system design, it is necessary to generate firm system architecture models based on the needs of stakeholders. The quality of the system design in this phase has a great impact on the detailed design and implementation for the subsequent system, and also plays an important role in the performance, development progress and cost of the whole system. Through the collaboration of cross-professional teams, modeling and model execution, comparing the model execution with expected results, MBSE has enabled digital model-level verification and validation before test verification and validation based on physical products, thus improving the design exactness, completeness and greatly reducing design errors or defects. This paper explores the logical ideas behind modeling of system architectures in order to promote the adoption of MBSE in the field of space systems.

中国区域卫生规划监督与评价的Logic model(逻辑模型)研究

研究的目的是建立中国区域卫生规划的监督与评价体系,推动全国的区域卫生规划工作,采用LogicModel建立了中国区域卫生规划监督与评价的框架和指标体系并对有关实施问题进行了讨论。

Completeness of bounded model checking temporal logic of knowledge

In order to find the completeness threshold which offers a practical method of making bounded model checking complete, the over-approximation for the complete threshold is presented. First, a linear logic of knowledge is introduced into the past tense operator, and then a new temporal epistemic logic LTLKP is obtained, so that LTLKP can naturally and precisely describe the system＇s reliability. Secondly, a set of prior algorithms are designed to calculate the maximal reachable depth and the length of the longest of loop free paths in the structure based on the graph structure theory. Finally, some theorems are proposed to show how to approximate the complete threshold with the diameter and recurrence diameter. The proposed work resolves the completeness threshold problem so that the completeness of bounded model checking can be guaranteed.

Intrusion Detection Algorithm Based on Model Checking Interval Temporal Logic

Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is still a high rate of false negatives in detecting these complex attack patterns.To solve this problem,we use interval temporal logic formulae to describe concurrent attacks and piecewise attacks.On this basis,we formalize a novel algorithm for intrusion detection based on model checking interval temporal logic.Compared with the method based on model checking linear temporal logic,the new algorithm can find unknown succinct attacks.The simulation results show that the new method can effectively reduce the false negative rate of concurrent attacks and piecewise attacks.

Physics-based analysis and simulation model of electromagnetic interference induced soft logic upset in CMOS inverter

The instantaneous reversible soft logic upset induced by the electromagnetic interference（EMI） severely affects the performances and reliabilities of complementary metal–oxide–semiconductor（CMOS） inverters. This kind of soft logic upset is investigated in theory and simulation. Physics-based analysis is performed, and the result shows that the upset is caused by the non-equilibrium carrier accumulation in channels, which can ultimately lead to an abnormal turn-on of specific metal–oxide–semiconductor field-effect transistor（MOSFET） in CMOS inverter. Then a soft logic upset simulation model is introduced. Using this model, analysis of upset characteristic reveals an increasing susceptibility under higher injection powers, which accords well with experimental results, and the influences of EMI frequency and device size are studied respectively using the same model. The research indicates that in a range from L waveband to C waveband, lower interference frequency and smaller device size are more likely to be affected by the soft logic upset.

Three-dimensional fuzzy logic system for process modeling and control

The traditional fuzzy logic system （FLS） can only model and control the process in two-dimensional nature. Many of real-world systems are of multidimensional features, such as, thermal and fluid processes with spatiotemporal dynamics, biological systems, or decision-making processes that contain stochastic and imprecise uncertainties. These types of systems are difficult for the traditional FLS to model and control because they require a third dimension for spatial or probabilistic information. The type-2 fuzzy set provides the possibility to develop a three-dimensional fuzzy logic system for modeling and controlling these processes in three-dimensional nature.

Fault detection and identification based on combining logic and model in a wall-climbing robot

A combined logic- and model-based approach to fault detection and identification （FDI） in a suction foot control system of a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events （elementary causes）, which can lead to a root event （a particular fault）. Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot.

A Novel Design of Octal-Valued Logic Full Adder Using Light Color State Model

Due to the demand of high computational speed for processing big data that requires complex data manipulations in a timely manner,the need for extending classical logic to construct new multi-valued optical models becomes a challenging and promising research area.This paper establishes a novel octal-valued logic design model with new optical gates construction based on the hypothesis of Light Color State Model to provide an efficient solution to the limitations of computational processing inherent in the electronics computing.We provide new mathematical definitions for both of the binary OR function and the PLUS operation in multi valued logic that is used as the basis of novel construction for the optical full adder model.Four case studies were used to assure the validity of the proposed adder.These cases proved that the proposed optical 8-valued logic models provide significantly more information to be packed within a single bit and therefore the abilities of data representation and processing is increased.

A Non-Singleton Type-3 Fuzzy Modeling: Optimized by Square-Root Cubature Kalman Filter

In many problems,to analyze the process/metabolism behavior,a mod-el of the system is identified.The main gap is the weakness of current methods vs.noisy environments.The primary objective of this study is to present a more robust method against uncertainties.This paper proposes a new deep learning scheme for modeling and identification applications.The suggested approach is based on non-singleton type-3 fuzzy logic systems(NT3-FLSs)that can support measurement errors and high-level uncertainties.Besides the rule optimization,the antecedent parameters and the level of secondary memberships are also adjusted by the suggested square root cubature Kalmanfilter(SCKF).In the learn-ing algorithm,the presented NT3-FLSs are deeply learned,and their nonlinear structure is preserved.The designed scheme is applied for modeling carbon cap-ture and sequestration problem using real-world data sets.Through various ana-lyses and comparisons,the better efficiency of the proposed fuzzy modeling scheme is verified.The main advantages of the suggested approach include better resistance against uncertainties,deep learning,and good convergence.

Model Checking over Paraconsistent Temporal Logic

Classical logic cannot be used to effectively reason about concurrent systems with inconsistencies (inconsistencies often occur, especially in the early stage of the development, when large and complex concurrent systems are developed). In this paper, we propose the use of a guasi-classical temporal logic (QCTL) for supporting the verification of temporal properties of such systems even where the consistent model is not available. Our models are paraKripke structures (extended standard Kripke structures), in which both a formula and its negation are satisfied in a same state, and properties to be verified are expressed by QCTL with paraKripke structures semantics. We introduce a novel notion of paraKripke models, which grasps the paraconsistent character of the entailment relation of QCTL. Furthermore, we explore the methodology of model checking over QCTL, and describe the detailed algorithm of implementing QCTL model checker. In the sequel, a simple example is presented, showing how to exploit the proposed model checking technique to verify the temporal properties of inconsistent concurrent systems.

Logic Picture-Based Dynamic Power Estimation for Unit Gate-Delay Model CMOS Circuits

In this research, a fast methodology to calculate the exact value of the average dynamic power consumption for CMOS combinational logic circuits is developed. The delay model used is the unit-delay model where all gates have the same propagation delay. The main advantages of this method over other techniques are its accuracy, as it is deterministic and it requires less computational effort compared to exhaustive simulation approaches. The methodology uses the Logic Pictures concept for obtaining the nodes’ toggle rates. The proposed method is applied to well-known circuits and the results are compared to exhaustive simulation and Monte Carlosimulation methods.