A Novel Framework to Construct S-Box Quantum Circuits Using System Modeling: Application to 4-Bit S-Boxes

Quantum computers accelerate many algorithms based on the superposition principle of quantum mechanics.The Grover algorithm provides significant performance to malicious users attacking symmetric key systems.Since the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms,research research on the implementation of quantum circuits is essential.This paper presents a new framework to construct quantum circuits of substitution boxes(S-boxes)using system modeling.We model the quantum circuits of S-boxes using two layers:Toffoli and linear layers.We generate vector spaces based on the values of qubits used in the linear layers and apply them to find quantum circuits.The framework finds the circuit bymatching elements of vector spaces generated fromthe input and output of a given S-box,using the forward search or themeet-in-the-middle strategy.We developed a tool to apply this framework to 4-bit S-boxes.While the 4-bit S-box quantum circuit construction tool LIGHTER-R only finds circuits that can be implemented with four qubits,the proposed tool achieves the circuits with five qubits.The proposed tool can find quantum circuits of 4-bit odd permutations based on the controlled NOT,NOT,and Toffoli gates,whereas LIGHTER-R is unable to perform this task in the same environment.We expect this technique to become a critical step toward optimizing S-box quantum circuits.

System modeling and dynamic analysis of ISG hybrid power shafting

A system model is established to analyze the dynamic performance of an integrated starter and generator （ISG） hybrid power shafting. The model couples the electromechanical coupling shaft dynamics, the bearing hydrodynamic lubrication and the engine block stiffness. The model is com- pared with the model based on ADAMS or the model neglecting the bearing hydrodynamics. The bearing eccentricity and the oil film pressure have been calculated under different hybrid conditions or at the different motor power levels. It＇ s found that the bearing hydrodynamics decreases the cal- culation results of the bearing peak load. Changes of the hybrid conditions or the motor power have no significant effect on the main bearing, but have impact on the motor bearing. A hybrid power sys- tem composed of a 1.6 L engine and a 45 kW ISG motor can operate safely.

A systematic review of system modeling and control strategy of proton exchange membrane fuel cell

The proton exchange membrane fuel cell,as a novel energy device,exhibits a wide array of potential applications.This paper offers a comprehensive review and discussion of modeling and control strategies for fuel cell systems.It commences with a concise introduction to the structure and principles of fuel cells.Subsequently,it outlines modeling approaches for various fuel cell subsystems,encompassing the fuel cell stack,air supply system,hydrogen supply system,thermal management system,and water management system.Following this,it conducts a comparative analysis and discussion of prevalent control strategies for the aforementioned subsystems.Lastly,the paper outlines future research trends and directions in the modeling and control strategies of fuel cells.The aim of this paper is to provide ideas and inspirations for the design and management of membrane fuel cell systems from control aspects.

Refinement modeling and verification of secure operating systems for communication in digital twins

In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely correct.Formal verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented correctly.In this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly instructions.The verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.

Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Mass Balance Modeling for Electric Arc Furnace and Ladle Furnace System in Steelmaking Facility in Turkey

In the electric arc furnace （EAF） steel production processes, scrap steel is principally used as a raw material instead of iron ore. In the steelmaking process with EAF, scrap is first melted in the furnace and then the desired chemical composition of the steel can be obtained in a special furnace such as ladle furnace （LF）. This kind of furnace process is used for the secondary refining of alloy steel. LF furnace offers strong heating fluxes and enables precise temperature control, thereby allowing for the addition of desired amounts of various alloying elements. It also provides outstanding desulfurization at high-temperature treatment by reducing molten steel fluxes and removing deoxidation products. Elemental analysis with mass balance modeling is important to know the precise amount of required alloys for the LF input with respect to scrap composition. In present study, chemical reactions with mass conservation law in EAF and LF were modeled altogether as a whole system and chemical compositions of the final steel alloy output can be obtained precisely according to different scrap compositions, alloying elements ratios, and other input amounts. Besides, it was found that the mass efficiency for iron element in the system is 95.93%. These efficiencies are calculated for all input elements as 8. 45% for C, 30.31% for Si, 46.36% for Mn, 30.64% for P, 41.96% for S, and 69.79% for Cr, etc. These efficiencies provide valuable ideas about the amount of the input materials that are vanished or combusted for 100 kg of each of the input materials in the EAF and LF system.

THEMODELINGOFATCSYSTEMSBASEDONPETRINET

In this paper a modeling method of ATC system is developed by using object Petri net. The formalized definition of the senior Petri net is given and illustrated by a practical example.

Feature selection for energy system modeling: Identification of relevant time series information

Heuristic or clustering based time series aggregation methods are often used to reduce temporal complexity of energy system models by selecting representative days.However,these methods potentially neglect relevant information of time series(e.g.,distribution parameters).To identify relevant time series parameters,feature selection algorithms can be applied.The present research contributes by(a)developing a new feature selection approach based on clustering,nested modeling and regression(CNR)which is designed for applications requiring high selectivity and using different data sets,(b)comparing and evaluating CNR with feature selection methods available from the literature(e.g.,LASSO)and(c)identifying relevant information of the time series applied in energy system models,in particular those of demand,photovoltaic and wind.Results show that CNR achieves on average up to 101%lower mean absolute errors when methods are directly compared.Thus,CNR better identifies relevant information when the number of selected features is restricted.The disadvantage of CNR,however,is its high computational effort.A potential remedy to counter this is the combination with another method(e.g.,as pre-feature selection).In terms of relevant information,energy systems including photovoltaic are mainly characterized by the correlation between demand and photovoltaic time series as well as the range and the 35%quantile of demand.When energy systems include wind power,the minimum and mean of wind as well as the correlation between demand and wind time series are relevant characteristics.The implications of these findings are discussed.

Non-intrusive modeling for integrated energy system based on two-stage GAN

Generally,an accurate model can describe the operating states of a system more effectively and provide a more reliable theoretical basis for the system optimization and control.Different from the traditional intrusive modeling,a non-intrusive modeling method based on two-stage generative adversarial network(TS-GAN)is proposed for integrated energy system(IES).By using this method,non-intrusive modeling for the IES including photovoltaic,wind power,energy storage,and energy coupling equipment can be carried out.First,the characteristics of IES are analyzed and extracted based on the meteorological data,energy output,and energy price,and then the characteristic database is established.Meanwhile,the loads are classified as uncontrollable loads and schedulable loads based on frequency domain decomposition to facilitate energy management.Furthermore,TS-GAN algorithm based on the Stackelberg game is designed.In the TS-GAN,the first-stage GAN is used to generate the operating data of each equipment identified by non-invasive monitoring,and the second-stage GAN distinguishes the accumulated data generated by first-stage GAN and further modifies the generator models of the first-stage GAN.Finally,the effectiveness and accuracy of the proposed method are verified by the simulation of an energy region.

A Modeling Method Applied to Fault Diagnosis for Constant Linear System

The paper presents a new modeling method applied to fault diagnosis for constant linear closed-loop system by taking the impulse response series as the system model, and provides the calculation process of the method and output of model. The high frequency part of the pulse series, in the method, is reversed so as not to lose the frequency information of the pulse series in its transfer function. On the other hand, the method can also avoid the disadvantage that the learning results of neural network are uncertain every time. In the last part, the application with random disturbance of digital simulation and practical system shows that the modeling method is high accurate and suitable to be applied in fault diagnosis area.

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

The Fuzzy Modeling Algorithm for Complex Systems Based on Stochastic Neural Network

A fuzzy modeling method for complex systems is studied. The notation of general stochastic neural network (GSNN) is presented and a new modeling method is given based on the combination of the modified Takagi and Sugeno's (MTS) fuzzy model and one-order GSNN. Using expectation-maximization(EM) algorithm, parameter estimation and model selection procedures are given. It avoids the shortcomings brought by other methods such as BP algorithm, when the number of parameters is large, BP algorithm is still difficult to apply directly without fine tuning and subjective tinkering. Finally, the simulated example demonstrates the effectiveness.

Modeling and simulation of quadrotor UAV based on Simscape

In order to speed up and simplify the design of the quadrotor unmanned aerial vehicle(UAV)and carry out experimental simulation and verification of relevant control algorithms,this paper analyzed the system dynamics model of the mechanical structure and flight principle of the quadrotor aircraft,and used the Newton-Euler method to derive the non-linear dynamic equations.Aiming at improving the modeling accuracy and system integrity of the quadrotor,the physical system modeling was combined with the CAD software and the Matlab/Simscape toolbox.The three-dimensional quadrotor solid model built by CAD software was imported into the Simscape simulation platform to construct the body and power system model of the quadrotor.Based on this,the control algorithm designed by Simulink was added to the simulation platform to facilitate the experiment verification and parameter tuning.The simulation results show that the designed aircraft can achieve hover and tracking well and meet the control performance requirements of the system.

Research on a New Hybrid System of a Tyre Crane Using Supercapacitors

Research on a hybrid system of a crane is a focus which considers environmental protection and energy saving. A new environmental protection and energy saving hybrid system of tyre crane, which utilizes supercapacitors as the energy store device, is presented. Analyzing the principle of supercapacitors, the model of the crane＇s hybrid system is set up in this paper, and the model of main blocks are established. Through simulation analyzing, the energy saving result of the new hybrid system is obtained, and the good application value of the new hybrid system is explained.

A multi-input and multi-output design on automotive engine management system

Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.

Modeling of Multi-Freedom Ship Motions in Irregular Waves with Fuzzy Neural Networks

In this paper, the neural network technology is combined with the fuzzy set theory to model the wave-induced ship motions in irregular seas. This combination makes possible the handling of a non-linear dynamic system with insufficient input information. The numerical results from the strip theory are used to train the networks and to demonstrate the validity of the proposed procedure.

Nonlinear modeling of PEMFC based on neural networks identification

The proton exchange membrane generation technology is highly efficient and clean, and is considered as the most hopeful “green” power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model. This paper first simply analyzes the necessity of the PEMFC generation technology, then introduces the generating principle from four aspects: electrode, single cell, stack, system; and then uses the approach and self-study ability of artificial neural network to build the model of nonlinear system, and adapts the Leven- berg-Marquardt BP (LMBP) to build the electric characteristic model of PEMFC. The model uses experimental data as training specimens, on the condition the system is provided enough hydrogen. Considering the flow velocity of air (or oxygen) and the cell operational temperature as inputs, the cell voltage and current density as the outputs and establishing the electric characteristic model of PEMFC according to the different cell temperatures. The voltage-current output curves of model has some guidance effect for improving the cell performance, and provide basic data for optimizing cell performance that have practical significance.

MODEL AND PERFORMANCE ANALYSIS OF FMT SYSTEM AND ORTHOGONAL FILTERBANKS

An orthogonal multi-carrier modulation-Filtered Multi-Tone (FMT) modulation, is evaluated in this paper. The objective of this paper is to model the FMT system with polyphase fil- terbank network, design its synthesis/analysis orthogonal filterbanks and analyze their performance. Oversampled and critically sampled cases of FMT system are discussed in detail. Perfect Reconstruc- tion (PR) properties of M parallel orthogonal subchannels in the case of critically sampled is derived from filterbank polyphase decomposition. Diverse types of prototype filters which include Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) are designed and analyzed. Performance analysis of orthogonal filterbanks which are implemented by these prototype filters are proposed and compared respectively. Simulation results of FMT orthogonal filterbanks are presented. In the end, the application prospect of FMT is discussed.

Reliability Study on the Risk Precontrol Management System of Coal Mines Safety

Risk precontrol management system of coal mines safety( RPMSCS) provides a set of preventive safety management strategy for high-risk coal industries, which has captured extensive attentions. Fundamentally,there are several membership systems with subsystems in the management system, and the subsystem reliability has an important influence on the management system performance. Through analyzing the structure characteristics of the management system,the phase type distribution was employed to analyze its subsystem reliability by considering repair process and three states including working,fail-abnormal,and fail-emergency states. The reliability indices of the subsystem were derived respectively,including the probabilities that the subsystem in three states,mean time to the first failure, mean time to first failemergency,mean working time to first fail-emergency,and mean maintenance time to the first fail-emergency, are derived respectively. The probabilities of the membership systems and the management system in three states were also derived. Some numerical examples were used to show the procedures. The result is important for better understanding the management system operation and improving its operational performance from the respect of system reliability.

MODEL-BASED PERFORMANCE EVALUATION APPROACH FOR MOBILE AGENT SYSTEMS

Claimed as the next generation programming paradigm, mobile agent technology has attracted extensive interests in recent years. However, up to now, limited research efforts have been devoted to the performance study of mobile agent system and most of these researches focus on agent behavior analysis resulting in that models are hard to apply to mobile agent systems. To bridge the gap, a new performance evaluation model derived from operation mechanisms of mobile agent platforms is proposed. Details are discussed for the design of companion simulation software, which can provide the system performance such as response time of platform to mobile agent. Further investigation is followed on the determination of model parameters. Finally comparison is made between the model-based simulation results and measurement-based real performance of mobile agent systems. The results show that the proposed model and designed software are effective in evaluating performance characteristics of mobile agent systems. The proposed approach can also be considered as the basis of performance analysis for large systems composed of multiple mobile agent platforms.