An intelligent control method based on artificial neural network for numerical flight simulation of the basic finner projectile with pitching maneuver

In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Vision based intelligent traffic light management system using Faster R‐CNN

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

Car-following strategy of intelligent connected vehicle using extended disturbance observer adjusted by reinforcement learning

Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions,thus declining the car-following performance.To solve this problem,a car-following strategy of ICV using EDO adjusted by reinforcement learning is proposed.Different from the conventional method,the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy.Since the“equivalent disturbance”can be compensated by EDO to a great extent,the disturbance rejection ability of the carfollowing method will be improved significantly.Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.

Design and Application of Intelligent Control System for Molten Iron Transportation Based on 5G Technology

Molten transport is an important link in the iron and steel enterprise production,involves many complex factors,artificial management is difficult.Therefore,puts forward a kind of molten iron transport wisdom control system based on 5G technology,which mainly contains the intelligent identification tracking system,equipment status collection information acquisition system,locomotive vehicle terminal system,etc.Combined with the analysis of the actual application situation,the system could integrate all the processes and elements of molten iron produc-tion and transportation,realize the integration of operation and management,and also promote the improvement of the turnover efficiency of molten iron tank,reduce the demand for personnel,and reduce the labor cost.

RESEARCH ON MECHANICAL MEASUREMENT-ORIENTED INTELLIGENT VIRTUAL CONTROLS

Intelligent virtual control (IVC) is an intelligent measurement instrumentunit with the function of actual measurement instruments, and the unit can be used as basic buildingblock for a variety of more complex virtual measurement instruments on a PC. IVC is a furtheradvancement from virtual instrument (VI), and it fuses the function modules and the controls modulesso that the relationship between the functions and controls of an instrument is imbedded in one ormore units. The design, implementation and optimization methods of IVCs are introduced. The computersoftware representation of IVCs is discussed. An example of an actual VI constructed with thebuilding blocks of IVCs is given.

Mechanoluminescent-Triboelectric Bimodal Sensors for Self-Powered Sensing and Intelligent Control

Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Key technologies and applications of intelligent dispatching command for high-speed railway in China

Purpose–The intelligent Central Traffic Control(CTC)system plays a vital role in establishing an intelligent high-speed railway(HSR)system.As the core of HSR transportation command,the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching.This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.Design/methodology/approach–This paper first briefly introduces the functions and configuration of the intelligent CTC system.Some new servers,terminals and interfaces are introduced,which are plan adjustment server/terminal,interface for automatic train operation(ATO),interface for Dynamic Monitoring System of Train Control Equipment(DMS),interface for Power Supervisory Control and Data Acquisition(PSCADA),interface for Disaster Monitoring,etc.Findings–The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans,safety control of train routes and commands,traffic information data platform,integrated simulation of traffic dispatching and ATO function.These technologies have been applied in the Beijing-Zhangjiakou HSR,which commenced operations at the end of 2019.Implementing these key intelligent functions has improved the train dispatching command capacity,ensured the safe operation of intelligent HSR,reduced the labor intensity of dispatching operators and enhanced the intelligence level of China’s dispatching system.Originality/value–This paper provides further challenges and research directions for the intelligent dispatching command of HSR.To achieve the objectives,new measures need to be conducted,including the development of advanced technologies for intelligent dispatching command,coping with new requirements with the development of China’s railway signaling system,the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Design of Diversified Intelligent Control System for Energy-saving Optimization of Solar Greenhouse in North China

Intelligent greenhouse can promote the development of modern agriculture, realize the high quality and high yield of crops, and also bring greater economic benefits. In accordance with the climate conditions in northwest China, a set of intelligent control system for diversified environment of solar greenhouse was designed. The system divides the annual greenhouse control into six stages according to the optimal energy saving. It uses modern detection technology to collect the greenhouse environmental temperature, environmental humidity, soil humidity, CO_(2) concentration and illumination parameters under different working modes. It uses programmable logic control technology to realize the data processing of various parameters and the action control of rolling film, wet curtain fan and other actuators. It uses KingView monitoring software to realize the monitoring and manual control of greenhouse environment parameters. The operation results indicate that the control system runs stably and basically meets the control requirements.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

堆石混凝土坝概述及下一代混凝土坝施工技术展望

Over the past few decades,one of the most significant advances in dam construction has been the inven-tion of the rock-filled concrete(RFC)dam,which is constructed by pouring high-performance self-compacting concrete(HSCC)to fill the voids in preplaced large rocks.The innovative use of large rocks in dam construction provides engineers with a material that requires less cement consumption and hydration heat while enhancing construction efficiency and environmental friendliness.However,two fundamental scientific issues related to RFC need to be addressed:namely,the pouring compactness and the effect of large rocks on the mechanical and physical properties of RFC.This article provides a timely review of fundamental research and innovations in the design,construction,and quality control of RFCdams.Prospects for next-generation concrete dams are discussed from the perspectives of envi-ronmental friendliness,intrinsic safety,and labor savings.

Current status and construction scheme of smart geothermal field technology

To address the key problems in the application of intelligent technology in geothermal development,smart application scenarios for geothermal development are constructed.The research status and existing challenges of intelligent technology in each scenario are analyzed,and the construction scheme of smart geothermal field system is proposed.The smart geothermal field is an organic integration of geothermal development engineering and advanced technologies such as the artificial intelligence.At present,the technology of smart geothermal field is still in the exploratory stage.It has been tested for application in scenarios such as intelligent characterization of geothermal reservoirs,dynamic intelligent simulation of geothermal reservoirs,intelligent optimization of development schemes and smart management of geothermal development.However,it still faces many problems,including the high computational cost,difficult real-time response,multiple solutions and strong model dependence,difficult real-time optimization of dynamic multi-constraints,and deep integration of multi-source data.The construction scheme of smart geothermal field system is proposed,which consists of modules including the full database,intelligent characterization,intelligent simulation and intelligent optimization control.The connection between modules is established through the data transmission and the model interaction.In the next stage,it is necessary to focus on the basic theories and key technologies in each module of the smart geothermal field system,to accelerate the lifecycle intelligent transformation of the geothermal development and utilization,and to promote the intelligent,stable,long-term,optimal and safe production of geothermal resources.

INTELLIGENT PRECISION CONTROL IN CNC GRINDING

The development of intelligent control techniques provides powerful means for the control of machine tools. In this paper, a intelligent control technique and an algorithm for precision control of CNC grinding of ceramic chips are introduced. In the process of ceramic chip CNC grinding, the dimension of the chips tends to get larger and the dimensional error to exceed the tolerance as the number of the chips increases which are machined on the same part program. There are many factors leading to the occurrence of the error and the law of error variation is very complicated. With the introduced intelligent self learning error compensation technique, the CNC system can improve the control strategy to compensate the error automatically. The simulational result is also given.

A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

Open multilevel hierarchic intelligent control system for eco-industrial system

In allusion to the characteristics of the open complex giant system, an open multilevel hierarchic intelligent control system is established for the eco-industrial system. With the idea of the open engineering system, using the hall for workshop of metasynthetic engineering （HWME）, intelligent control techniques, the expert system and the design of experiments are integrated within the framework of the nonlinear multiobjective decision support system to develop a robust, top-level design specification so as to make the system have the quality of adaptive control, self-organizing, self-learning and robustness. Finally, an illustrative example is given to clarify the effectiveness of the method.

Analysis of Current Research and Future Development Trends of Applying Solar Energy in Street Lighting

In the context of promoting green energy transition and addressing climate change globally,solar energy,as a clean and renewable energy source,has gradually become a hot topic for research.Solar streetlight systems realize energy self-sufficiency and environment-friendly lighting by integrating photovoltaic power generation technology and efficient LED lighting technology.By comprehensively analyzing the current status of the application of solar streetlights at home and abroad,this paper discusses its technical advantages,market penetration,and challenges in its development.In terms of technical characteristics,this paper focuses on analyzing the key technologies such as energy conversion efficiency and intelligent control systems of solar streetlights.

Neural Network-Powered License Plate Recognition System Design

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

INTELLIGENT VIRTUAL CONTROL:MEASURING INSTRUMENT FROM WHOLE TO PART

A new concept called intelligent virtual control (IVC), which can be drivenby measuring functions, is put forward. This small 'intelligent measurement instrument unit (IMIU)',carrying with functions of instrument, consists of different types of intelligent virtualinstrument (IVI) through individual components together as building blocks and can be displayeddirectly on the computer screen. This is a new concept of measuring instrument, and also animportant breakthrough after virtual instrument (VI). Virtual control makes instrument resourcesobtain further exploitation. It brings about a fundamental change to the design and manufacturingmode. The instrument therefore, can not only be produced directly inside a PC, but the product isinvolved in the 'green product' system. So far, all the present digital instruments will grow to bereplaced by intelligent control with green characteristics.

Study on Intelligent Control and 3D Real-time Distributed Animation Simulation for Super-maneuver Attack of the New Generation Fighter

The super-maneuver flight performance has a very high tactical value, and the development of this tactical value has great significance. A discussion is devoted to the study of intelligent control methods and technologies of real-time distributed 3-dimensional animation simulation for the super-maneuverable attack of new generational fighter in this paper. A flight control system of super-maneuver is reconstructed by adopting three layers BP neural networks of number 3, and the fire/flight coupler is designed by introducing a fuzzy control rule whose universe of discourse and gain are regulated adaptively on the line. Furthermore, a new method of real-time distributed 3-dimensional animation simulation is put forward, and a real-time distributed 3-dimensional animation simulation tool platform is constructed in this paper. The simulation result is lifelike, perceivable directly and useful.