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control solutions for vehicles with continuously variable transmission

Control solutions for vehicles with continuously variable tr...

引用

International symposium on computational intelligence and Informatics

作者： C.-A. Dragos S. Preitl R.-E. Precup C.-S. Nes D. Pirlea A. S. Paul Department of Automation and Applied Informatics Polytechnic University of Timisoara Timisoara Romania Department of Strength of Materials Polytechnic University of Timisoara Timisoara Romania

The paper presents aspects concerning the modeling, driving scenarios and control structures of two classes of vehicular power train systems with continuously variable transmission (CVT). The modeling includes an analysis of the systems' components which include the spark-ignition internal combustion engine, the torque converter, the continuously variable transmission and the wheels. The CVT offers a continuum of infinitely variable gear ratios between established minimum and maximum limits compared to the automatic transmission which has only five gear ratios. Five driving scenarios are illustrated by digital simulation results: acceleration, overtaking maneuver, ramp encounter, engine brake, and cruise. Digital simulations are presented to test and validate the developed control solutions for one driving scenario.

关键词： Vehicles Engines Torque Mathematical model Gears Acceleration Mechanical power transmission

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An intelligent, integrated control system for a pressure filter

An intelligent, integrated control system for a pressure fil...

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International ieee Conference on Intelligent Systems, IS

作者： S.-L. Jamsa-Jounela A. Kesti M. Vermasvuori T. Ryynanen P. Enden J. Kampe Department of Process Control and Automation Department of Chemical Technology Helsinki University of Technology Espoo Finland

Artificial intelligence methods like expert systems and self-organizing maps have proved to be excellent tools for the control of mineral processes. This technology is currently being embedded directly into process equipment like flotation cells and dewatering filters. In this paper an intelligent, integrated control system for a pressure filter is described and the testing results presented and discussed.

关键词： Intelligent systems Intelligent control Centralized control Artificial intelligence Filters Expert systems Self organizing feature maps Process control control systems Minerals

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Research on Node Location Technology Based on Improved Particle Swarm Optimization

Research on Node Location Technology Based on Improved Parti...

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ieee symposium Series on computational intelligence (SSCI)

作者： Xiumei Cai Kexin Hu Fangjuan Zhang Wei Li Yiran Li Zichao Zhang School of Automation Xi’an University of Posts and Telecommunications Xi’an China School of Science Xi’an University of Posts and Telecommunications Xi’an China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

To solve the problems that the position error of the classcial DV-Hop localization algorithm is too large to satisfy the precision requirements of node positioning ,this paper put forward an imporved algorithm. Firstly, the algorithm introduces the dual communication radius method. Through the method of two broadcasts, the calculation method of the minimum hops is improved, and the minimum hops between nodes is further refined. Secondly, the usage of the particle swarm optimization algorithm can reduce the error when using the least squares method to compute the coordinate of unknown node. By using the improved particle swarm optimization algorithm, the large error of the least squares method for solving the unknown node coordinates is optimized, and then, make some improvements to avoid the standard particle swarm optimization algorithm fall into the local optimum in the process of iterative optimization . The simulation results show that the improved DV-Hop algorithm can effectively decrease the location errors and increase the precision of node positioning.

关键词： Handheld computers computational intelligence

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A Fog Level Detection Method Based on Grayscale Features

A Fog Level Detection Method Based on Grayscale Features

引用

International symposium on computational intelligence and Design, ISCID

作者： Cong Li Xiaobo Lu Chen Tong Weili Zeng School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9781479970063

With the rapid development of highway, the distribution of surveillance cameras has become increasingly intensive, which brings important significance to traffic safety by detecting visibility of fog using surveillance video. In this paper, a fog level detection method based on grayscale features is proposed. Sometimes there is no proper calibration template in highway. In order to meet the requirement of transport regulation on visibility, we classify fog level qualitatively into big fog, little fog and no fog by analyzing the change of average gray value with the ordinate in different weather conditions. The experiment results show that this method classifies accurately, quickly and is widely applicable.

关键词： Meteorology Roads Accuracy Gray-scale Feature extraction Statistical analysis Cameras

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What is robot intelligence

What is robot intelligence

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： H. Miura Department of Mechano-Informatics University of Tokyo Bunkyo Tokyo Japan

It should be understood that the robot is not a simple automatic machine and has certain intelligence. Several intelligent robots which have been developed in the author's laboratory for the past 15 years are introduced in this paper. These robots perform many kinds of play like cup and ball game, top-spinning, stilts, etc. When a human plays these games, one needs some special intelligence or skill. If we can put these human-like intelligence into a robot in the form of computer control program, the robot will be able to play the same games. The most important problem is to find out what sort of intelligence a human needs for playing each game. This problem should be solved by observation and analysis of the human play. These intelligences will be useful not only for playing that game but also for other jobs of robots. By the way, these robots look intelligent apparently. But, are they really and truly intelligent? There is an opinion that these robots are no more than simple automatic machines which are controlled by a computer with sophisticated programs. Then, what is actual robot intelligence? The author is trying to construct a new robotics-insect-model based microrobotics -in order to get a new concept of robot intelligence.< >

关键词： Intelligent robots Microelectromechanical devices

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RIS-Aided Localization Method Based on DNN-SSA Fusion in NLOS Scenarios 5

RIS-Aided Localization Method Based on DNN-SSA Fusion in NLO...

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5th International Conference on Computer, Big Data and Artificial intelligence, ICCBD+AI 2024

作者： Luo, Yujia Hu, Qingsong Cheng, Yuanxun Yuan, Shuya Zhang, Yuansheng China University of Mining and Technology School of Information and Control Engineering Xuzhou China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process Beijing China Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

ISBN: (纸本)9798331533991

With the advent of the 6G era, precise positioning and reliable, energy-efficient data transmission have become critical for the Internet of Things. However, high-frequency signals like millimeter-wave and terahertz are easily obstructed, making traditional LOS-based methods ineffective in complex environments. To overcome this, NLOS localization methods and Reconfigurable Intelligent Surfaces offer promising solutions by dynamically modifying the wireless environment. This paper introduces a Direct Position Determination method that integrates Deep Neural Networks (DNN) with the Sparrow Search Algorithm (SSA) to tackle the challenges of high computational complexity and low localization accuracy in RIS-aided systems. An NLOS scenario with RIS is established, and a far-field channel model is derived. The method uses DNN to model the nonlinear relationship between the likelihood function and user position, and then employs SSA to optimize the DNN-based fitness function, efficiently solving the objective function. Experimental results show that the DNN-SSA method consistently achieves high localization accuracy across different scenarios, even at low SNR levels, demonstrating its effectiveness and potential for 6G high-precision localization. © 2024 ieee.

关键词： Deep neural networks

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Time-suboptimal predictive control of four-in-wheel driven electric vehicles

Time-suboptimal predictive control of four-in-wheel driven e...

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International symposium on Applied computational intelligence and Informatics ( SACI)

作者： György Max Béla Lantos Department of Control Engineering and Information Technology Budapest University of Technology and Economics Budapest Hungary

The paper deals with the approximately time optimal control of four in-wheel-driven (4WD) electric cars in a test path under state and input constraints with initial perturbations. The path is divided into sections allowing that path information for the actual section appears in real time based on sensor fusion. For each section a separate optimum control problem is solved in a receding horizon predictive control (RHPC) fashion using the single-track model (2WD) of the vehicle. The problem is given as a dynamic nonlinear optimal control problem (DNOCP) and solved by reformulating it to a static nonlinear program (NLP) using discretization and direct multiple shooting methods. A novel method is presented to convert the RHPC optimal solution to the optimal control of 4WD cars. The conversion assures similar motion of the CoG points of both models and optimal distribution of the longitudinal wheel forces. For closed loop control of 4WD vehicle a discrete time model predictive control (MPC) is proposed which uses the optimal reference signals and the distributed wheel forces and optimizes the perturbations with analytically solvable end constraints.

关键词： Vehicles Wheels Optimal control Optimization Predictive control Force Vehicle dynamics

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Hierarchical Cooperative Swarm Policy Learning with Role Emergence

Hierarchical Cooperative Swarm Policy Learning with Role Eme...

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ieee symposium Series on computational intelligence (SSCI)

作者： Tianle Zhang Zhen Liu Zhiqiang Pu Tenghai Qiu Jianqiang Yi Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728190495

Swarm systems can cooperatively and efficiently accomplish specified complex tasks. Recent works have shown the potential of multi-agent reinforcement learning methods to study behavior policies of swarm systems. However, it is difficult for them to complete complex swarm tasks efficiently. In human society, role assignment can effectively help humans understand complex tasks and decompose them into simple certain subtasks. Inspired by this, we propose a two-level hierarchical cooperative swarm policy learning framework with role emergence based on hierarchical deep reinforcement learning for distributed swarm systems. In this framework, roles are dynamic and emergent. Agents with the same role tend to collectively complete a certain subtask. Specifically, each agent uses a higher-level swarm policy to dynamically select a role for itself in a role space and at a higher temporal scale, while it uses a lower-level swarm policy to perform the responsibilities of the selected role in a primitive action space. Meanwhile, hierarchical swarm policies with partial observation are centrally trained and decentrally executed, where agents' local interaction modules and extrinsic team rewards are designed to promote cooperation among agents. In addition, an intrinsic reward is defined to enable different roles to be identified by agents' longer-term behaviors, which implicitly associates the roles with responsibilities. Simulation results show that our method can learn and generate emergent, dynamic and identifiable roles, which helps swarm systems to reliably and efficiently accomplish complex tasks in a shorter time.

关键词： Simulation Reinforcement learning Reliability Task analysis computational intelligence

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The Visibility and Usability Research of Navigation Satellites for HEO

The Visibility and Usability Research of Navigation Satellit...

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International symposium on computational intelligence and Design, ISCID

作者： Yuzhen Gong Lingjuan Miao Xi Zhang Yanbing Guo School of automation Beijing institute of technology Beijing China

ISBN: (纸本)9781479970063

The application of global satellite navigation system to the user satellite at high elliptical orbit can overcome the disadvantage that the equipment of the ground control system is complex and high cost. But with the increasing of the altitude of user satellite, the number of usable satellites reduces, even less than four. In order to achieve navigating and positioning using the global satellite navigation system, this paper puts forward the concept of the transmission time demodulation threshold and the concept of ephemeris data demodulation threshold. We make full use of the navigation message information and analyze these new concepts to discuss a new method. The simulation result demonstrates that the new method improves the number of navigation satellites and period of navigating autonomously.

关键词： Satellites Global Positioning System Demodulation Satellite broadcasting Orbits Receivers

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Computer system for process control based on data-driven

Computer system for process control based on data-driven

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ieee symposium on Electrical & Electronics Engineering (EEESYM)

作者： Jiangyun Li Yan Liu Chaonan Tong School of Automation & Electrical Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China

ISBN: (纸本)9781467323635

It presents a computer control system for process control based on data-driven. The system focuses on process data and is able to deal with the complex problems such as nonlinearity, significant delay, strong coupling and stochastic uncertainty, which are ubiquitous in process control. It adopts both modeling method based on data and learning control theory. The computer control system is composed of PC servers and high performance embedded special controllers. control network adopts fully-distributed automation islands based on industrial Ethernet. So the powerful ability of data process is provided for the system and can satisfy the requirement of modeling and controlling based on data-driven.

关键词： computational modeling Adaptation models Predictive models Analytical models

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