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.

USING LOGIC COMPONENTS FOR CONCEPTUAL DIE DESIGN

Logic components are used to support the conceptual design Taking the stamping die structure as the research object,several logic components are defined for the conceptual die construction design A new method logic assembly modeling is presented to satisfy the characteristic of the top down die design process Representing shapes and spatial relations in logic can provide a natural,intuitive method of developing complete computer systems for reasoning about die construction design at the conceptual stage This method can reflect the designer's thought clearly and provide the designer with a test bed for generating alternatives and performing reasoning work at the conceptual die design stage

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.

MLD-MPC Approach for Three-Tank Hybrid Benchmark Problem

The present paper aims at validating a Model Predictive Control(MPC),based on the Mixed Logical Dynamical(MLD)model,for Hybrid Dynamic Systems(HDSs)that explicitly involve continuous dynamics and discrete events.The proposed benchmark system is a three-tank process,which is a typical case study of HDSs.The MLD-MPC controller is applied to the level control of the considered tank system.The study is initially focused on the MLD approach that allows consideration of the interacting continuous dynamics with discrete events and includes the operating constraints.This feature of MLD modeling is very advantageous when an MPC controller synthesis for the HDSs is designed.Once the MLD model of the system is well-posed,then the MPC law synthesis can be developed based on the Mixed Integer Programming(MIP)optimization problem.For solving this MIP problem,a Branch and Bound(B&B)algorithm is proposed to determine the optimal control inputs.Then,a comparative study is carried out to illustrate the effectiveness of the proposed hybrid controller for the HDSs compared to the standard MPC approach.Performances results show that the MLD-MPC approach outperforms the standardMPCone that doesn’t consider the hybrid aspect of the system.The paper also shows a behavioral test of the MLDMPC controller against disturbances deemed as liquid leaks from the system.The results are very satisfactory and show that the tracking error is minimal less than 0.1%in nominal conditions and less than 0.6%in the presence of disturbances.Such results confirm the success of the MLD-MPC approach for the control of the HDSs.

Research and practice of intelligent coal mine technology systems in China

This study considered the role of coal as China’s basic energy source and examines the development of the coal industry.We focused on the intelligent development of coal mines,and introduced the“Chinese mode”of intelligent mining in underground coal mines,which uses complete sets of technical equipment to propose classifcation and grading standards.In view of the basic characteristics and technical requirements of intelligent coal mine systems,we established a digital logic model and propose an information entity and knowledge map construction method.This involves an active information push strategy based on a knowledge demand model and an intelligent portfolio modeling and distribution method for collaborative control of coal mines.The top-level architecture of 5G+intelligent coal mine systems combines intelligent applications such as autonomous intelligent mining,human–machine collaborative rapid tunneling,unmanned auxiliary transportation,closed-loop safety control,lean collaborative operation,and intelligent ecology.Progress in intelligent mining technology was described in terms of a dynamic modifed geological model,underground 5G network and positioning technology,intelligent control of the mining height and straightness of the longwall working face,and intelligent mining equipment.The development of intelligent coal mines was analyzed in terms of its imbalances,bottlenecks,and the compatibility of large-scale systems.Implementation ideas for promoting the development of intelligent coal mines were proposed,such as establishing construction standards and technical specifcations,implementing classifcation and grading standards according to mining policy,accelerating key technology research,and building a new management and control model.

A Hybrid Approach to Modeling and Control of Vehicle Height for Electronically Controlled Air Suspension

The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.

Secure and Anonymous Three-Factor Authentication Scheme for Remote Healthcare Systems

Wireless medical sensor networks(WMSNs)play a significant role in increasing the availability of remote healthcare systems.The vital and physiological data of the patient can be collected using the WMSN via sensor nodes that are placed on his/her body and then transmitted remotely to a healthcare professional for proper diagnosis.The protection of the patient’s privacy and their data from unauthorized access is a major concern in such systems.Therefore,an authentication scheme with a high level of security is one of the most effective mechanisms by which to address these security concerns.Many authentication schemes for remote patient monitoring have been proposed recently.However,the majority of these schemes are extremely vulnerable to attacks and are unsuitable for practical use.This paper proposes a secure three-factor authentication scheme for a patient-monitoring healthcare system that operates remotely using a WMSN.The proposed authentication scheme is formally verified using the Burrows,Abadi and Needham’s(BAN)logic model and an automatic cryptographic protocol verifier(ProVerif)tool.We show that our authentication scheme can prevent relevant types of security breaches in a practical context according to the discussed possible attack scenarios.Comparisons of the security and performance are carried out with recently proposed authentication schemes.The results of the analysis show that the proposed authentication scheme is secure and practical for use,with reasonable storage space,computation,and communication efficiency.

Causal association rule mining methods based on fuzzy state description

Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.

FCS-MPC Strategy for PV Grid-Connected Inverter Based on MLD Model

In the process of grid-connected photovoltaic power generation,there are high requirements for the quality of the power that the inverter breaks into the grid.In this work,to improve the power quality of the grid-connected inverter into the grid,and the output of the system can meet the grid-connected requirements more quickly and accurately,we exhibit an approach toward establishing a mixed logical dynamical(MLD)model where logic variables were introduced to switch dynamics of the single-phase photovoltaic inverters.Besides,based on the model,our recent efforts in studying the finite control set model predictive control(FCS-MPC)and devising the output current full state observer are exciting for several advantages,including effectively avoiding the problem of the mixed-integer quadratic programming(MIQP),lowering the THD value of the output current of the inverter circuit,improving the quality of the power that the inverter breaks into the grid,and realizing the current output and the grid voltage same frequency and phase to meet grid connection requirements.Finally,the effectiveness of the mentioned methods is verified by MATLAB/Simulink simulation.

PRODUCT MODELING AND PROCESS PLANNING WITHIN CONCURRENT ENGINEERING ENVIRONMENT

A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.

Computational Mechanisms for Metaphor in Languages： A Survey

Metaphor computation has attracted more and more attention because metaphor, to some extent, is the focus of mind and language mechanism. However, it encounters problems not only due to the rich expressive power of natural language but also due to cognitive nature of human being. Therefore machine-understanding of metaphor is now becoming a bottle-neck in natural language processing and machine translation. This paper first suggests how a metaphor is understood and then presents a survey of current computational approaches, in terms of their linguistic historical roots, underlying foundations, methods and techniques currently used, advantages, limitations, and future trends. A comparison between metaphors in English and Chinese languages is also introduced because compared with development in English language Chinese metaphor computation is just at its starting stage. So a separate summarization of current progress made in Chinese metaphor computation is presented. As a conclusion, a few suggestions are proposed for further research on metaphor computation especially on Chinese metaphor computation.

Optimization of fused deposition modeling process parameters using a fuzzy inference system coupled with Taguchi philosophy

Fused deposition modeling （FDM） is an additive manufacturing technique used to fabricate intricate parts in 3D, within the shortest possible time without using tools, dies, fixtures, or human intervention. This article empiri- cally reports the effects of the process parameters, i.e., the layer thickness, raster angle, raster width, air gap, part orientation, and their interactions on the accuracy of the length, width, and thicknes, of acrylonitrile-butadiene- styrene （ABSP 400） parts fabricated using the FDM tech- nique. It was found that contraction prevailed along the directions of the length and width, whereas the thickness increased from the desired value of the fabricated part. Optimum parameter settings to minimize the responses, such as the change in length, width, and thickness of the test specimen, have been determined using Taguchi＇s parameter design. Because Taguchi＇s philosophy fails to obtain uniform optimal factor settings for each response, in this study, a fuzzy inference system combined with the Taguchi philosophy has been adopted to generate a single response from three responses, to reach the specific target values with the overall optimum factor level settings. Further, Taguchi and artificial neural network predictive models are also presented in this study for an accuracy evaluation within the dimensions of the FDM fabricated parts, subjected to various operating conditions. The pre- dicted values obtained from both models are in good agreement with the values from the experiment data, with mean absolute percentage errors of 3.16 and 0.15, respectively. Finally, the confirmatory test results showed an improvement in the multi-response performance index of 0.454 when using the optimal FDM parameters over the initial values.