Article
Automation & Control Systems
Fang Xu, Zhongyi Guo, Hong Chen, Dongdong Ji, Ting Qu
Summary: This article presents the FPGA implementation of particle swarm optimization-based nonlinear model-predictive control for resource-constrained embedded systems with millisecond timescales. The implementation utilizes parallelism, pipelining, and specialized numerical formats to enhance the online computation performance of NMPC and finds a trade-off between computational performance and resource usage.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Hardware & Architecture
Mohammad A. Al-Jarrah, Amin Jarrah, Amal Alawaisah
Summary: This paper presents the development of an automotive engine idle speed controller using nonlinear model predictive control and the Firefly Algorithm (NMPC-FA-ISE). The NMPC-FA is implemented on a FPGA platform using the Vivado HLS tool. The FA algorithm is employed to handle the nonlinearity of NMPC. Experimental results demonstrate satisfactory control performance with fast response time and acceptable power consumption.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Automation & Control Systems
Xiao-Wei Zhang, Lei Zuo, Ming Li, Jian-Xin Guo
Summary: This article presents an efficient and robust method for FPGA calculation of matrix inversion, which reduces computation load and improves numerical stability. The proposed computation procedures include matrix decomposition, triangular matrix inversion, and matrices multiplication.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Computer Science, Information Systems
Pervesh Kumar, Imran Ali, Dong-Gyun Kim, Sung-June Byun, Dong-Gyu Kim, Young-Gun Pu, Kang-Yoon Lee
Summary: In this paper, a re-configurable CNN engine design method is proposed. The modeling is done using TensorFlow and Keras libraries in Python, and the register-transfer-level design is performed using Verilog. The proposed design achieves a competitive accuracy of approximately 96% on the MNIST and CIFAR-10 datasets.
Article
Computer Science, Artificial Intelligence
Alexandro Ortiz, Efrain Mendez, David Balderas, Pedro Ponce, Israel Macias, Arturo Molina
Summary: This study describes the implementation of metaheuristic optimization algorithms in hardware and compares five important algorithms. The results demonstrate the feasibility of NI FPGA hardware and reveal differences in device utilization and execution time among the algorithms.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Hao Wu
Summary: This study focuses on classifying Indian classical dance using FPGA, with data collection on various themes and postures for offline reference in dance education.
MICROPROCESSORS AND MICROSYSTEMS
(2021)
Article
Environmental Sciences
Hushan Lv, Yongrui Li, Yizhuang Xie, Tingting Qiao
Summary: This study introduces a three-dimensional cross-mapping approach and an on-chip data transfer approach based on a superscalar pipeline to improve the data storage and transfer efficiency of SAR imaging systems. The hardware architecture designed and the experimental results obtained demonstrate that the proposed methods can significantly increase the storage access bandwidth and enhance the data transfer efficiency, making them suitable for real-time processing systems in spaceborne SAR.
Article
Computer Science, Hardware & Architecture
Xiaoyan Wang, Xiaoyan Liu
Summary: The study highlights the importance of crisis management models such as the information layer, control layer, utilitarian layer, and human cooperation layer, as well as technical improvements and implementations for crisis response. Additionally, utilizing Web Geographic Information System and sensor data to generate logistics intelligent decision procedures can enhance the efficiency of emergency logistics response.
MICROPROCESSORS AND MICROSYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Limin Yu, Shen Xu, Lingyun Li, Yugeng Wu, Chenxi Yang, Longxing Shi, Weifeng Sun
Summary: This article proposes using a sigma converter in the voltage regulator module of a 48V bus to improve system efficiency and reduce costs. A small-signal model is constructed using a decoupling method, and a control design and simplified transfer function are provided to achieve voltage regulation under different loads.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2022)
Article
Geochemistry & Geophysics
Daniel Bascones, Carlos Gonzalez, Daniel Mozos
Summary: This article presents a real-time implementation of a hyperspectral image compression algorithm based on FPGA, which is able to process large images at a fast speed. The algorithm avoids new dependencies by using a new sample ordering method and encoder.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Mauricio Feo, Federico Alessio, Paolo Durante, Luis Granado Cardoso, Guillaume Vouters
Summary: The LHCb experiment at CERN has been upgraded for LHC Run 3, replacing the entire readout system with new electronics. Clock and control commands are distributed through an optical network, ensuring synchronicity. A firmware core called LHCb-PON provides stable communication and timing, while also monitoring the system. This article presents the implementation and results of this upgraded system during the startup of LHC Run 3.
IEEE TRANSACTIONS ON NUCLEAR SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Riccardo Della Sala, Davide Bellizia, Giuseppe Scotti
Summary: This paper presents a True Random Number Generator (TRNG) implemented using latched-XOR (LX) gates. The proposed TRNG improves the throughput of conventional TRNGs by combining latches metastability and ring oscillators jitter. Experimental results show that the generated bitstreams exhibit good randomness and the TRNG is robust to voltage and temperature variations. The FPGA implementation is compact and efficient, achieving high throughput.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2022)
Article
Computer Science, Information Systems
Sumit Kumar Chatterjee, Sravan Kumar Vittapu
Summary: This study proposes an enhanced FSME (EFSME) method based on particle swarm optimization for motion estimation in HEVC video compression. The experimental results demonstrate that the proposed method outperforms existing approaches in terms of power consumption, area, and operational frequency.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Sumit Kumar Chatterjee, Sravan Kumar Vittapu
Summary: This paper proposes an Enhanced FSME (EFSME) method based on Particle Swarm Optimization for optimizing the motion estimation process in HEVC video compression. Experimental results show that EFSME significantly improves power consumption, area, and operating frequency compared to existing methods.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Charles Coquet, Andreas Arnold, Pierre-Jean Bouvet
Summary: The study describes and analyzes the Local Charged Particle Swarm Optimization (LCPSO) algorithm designed to track a moving target in a constrained environment with a swarm of agents. The algorithm is inspired by flocking algorithms and Particle Swarm Optimization (PSO) for function optimization, and its resilience to communication constraints and target behavior is supported by mathematical analysis and simulation results.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Lin Chen, Yilin Wang, Jing Zhao, Shihong Ding, Jinwu Gao, Hong Chen
Summary: An adaptive control scheme is proposed based on extremum seeking (ES) for rapid and high-precision servo control of an electronic throttle. It consists of an ES-variable-gain adaptive proportional-integral (ES-API) controller and an adaptive compensator (ES-ACP). The ES-API controller uses maps for the gains designed with respect to the tracking error and the ES-ACP compensates for the nonlinearity inherent in the electronic throttle control (ETC) system. Experimental results demonstrate that the control scheme is capable of accurately and quickly tracking multiple reference trajectories.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Engineering, Civil
Lin Zhang, Lianbo Jiang, Hanghang Liu, Yunfeng Hu, Ping Wang, Hong Chen
Summary: This study proposes a hierarchical control strategy to improve vehicle stability under extreme conditions. In the upper layer controller, a combined-slip tire model is adopted to improve model accuracy. A nonlinear model predictive control based controller is designed to track desired yaw rate and suppress lateral velocity and tire slip ratios. In the lower layer controller, the disturbance on the driver's torque requirement is taken into account and a linear predictive controller is designed to adjust motor torques to track desired tire slip ratios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Mechanical
Hongyan Guo, Xu Zhao, Jun Liu, Qikun Dai, Hui Liu, Hong Chen
Summary: An estimation framework that combines vision and vehicle dynamic information is established to accurately obtain the peak tire-road friction coefficient. The framework collects information for the road ahead from an image captured by a camera and uses a lightweight convolutional neural network to identify the road type and its corresponding range of tire-road friction coefficients. An unscented Kalman filter (UKF) method is then used to estimate the tire-road friction coefficient value directly based on the dynamic vehicle states. The results from the road-type recognition and dynamic estimation methods are synchronized, and a confidence-based fusion strategy is proposed to obtain an accurate peak tire-road friction coefficient. Virtual and real vehicle tests confirm the effectiveness of the proposed fusion estimation strategy, which outperforms both general vision-based estimation methods and dynamic-based estimation methods.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Artificial Intelligence
Haiping Du, Siyu Teng, Hong Chen, Jiaqi Ma, Xiao Wang, Chao Gou, Bai Li, Siji Ma, Qinghai Miao, Xiaoxiang Na, Peijun Ye, Hui Zhang, Guiyang Luo, Fei-Yue Wang
Summary: This letter presents a decentralized and hybrid workshop on the potential influence of ChatGPT on research and development in intelligent vehicles. The tests conducted showed that while ChatGPT's information can be updated and corrected, it may not always possess the latest knowledge regarding specific topics. The letter also discusses possible applications of ChatGPT in areas like autonomous driving, human-vehicle interaction, and intelligent transportation systems, highlighting challenges and opportunities associated with these applications.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Artificial Intelligence
Yao Sun, Yunfeng Hu, Hui Zhang, Hong Chen, Fei-Yue Wang
Summary: This letter presents the latest research findings from IEEE TIV's Decentralized and Hybrid Workshops (DHW) on Ethics, Responsibility, and Sustainability (ERS). The research focuses on a novel emission regulatory framework for intelligent transportation systems (ITS) and smart cities (SCs) in ERS. The framework proposes a parallel transportation level and a parallel vehicle level to achieve accurate estimation and emission-aware optimal planning. The letter also highlights the importance of considering modern aftertreatment systems (ATS) as a core module in the emission model.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Artificial Intelligence
Yao Sun, Yunfeng Hu, Hui Zhang, Feiyue Wang, Hong Chen
Summary: A parallel supervision system is developed to accurately estimate vehicle CO2 emissions by using only onboard diagnostics (OBD)-independent information. The system can predict future road gradients and planned speed trajectories. The combined CO2 model, consisting of physical and data-driven models, is considered the core part of the artificial world, while the actual traffic environment is regarded as the physical world. Two real-world experimental case studies validate the accuracy of both the physical and data-driven models, with the physical model showing more robustness. The system effectively bridges the gap between regulatory test cycles and real-world carbon emissions.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Artificial Intelligence
Lulu Guo, Hongqing Chu, Jin Ye, Bingzhao Gao, Hong Chen
Summary: This paper proposes a hierarchical velocity control system considering different drive preferences for connected and automated vehicles to improve overall efficiency under the vehicle-to-X (V2X) environment. Simulation results indicate that energy-saving and computational efficiency are improved using the proposed control system. The solution algorithm is further demonstrated under a hardware-in-the-loop simulation.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Engineering, Civil
Hongyan Guo, Jingzheng Guo, Xu Zhao, Dongpu Cao, Hong Chen, Shuyou Yu
Summary: This paper proposes a data-mechanism adaptive switched predictive (DASP) control strategy for intelligent connected vehicles. The strategy addresses the challenges of heterogeneous vehicles with disturbances and uncertain dynamics in platoon scenarios, as well as the multimodel switching caused by interruptions in communication. The use of Givens rotations and switching criteria enables online adaptive switching of the controller. Robustness analysis and simulations demonstrate the effectiveness of DASP algorithm for heterogeneous multivehicle regulation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Xinghao Lu, Haiyan Zhao, Cheng Li, Bingzhao Gao, Hong Chen
Summary: In this paper, a new decision-making method based on game theory is proposed to resolve the driving conflict and improve the safety and efficiency of autonomous vehicles at unsignalized intersections. The proposed method constructs an alterable game mode by combining a designed game entrying mechanism and replanning of game sequential order under different intersection conditions to ensure adaptiveness and effectiveness. Four payoff indicators and personalized payoff function are designed considering driving efficiency, safety, and comfort requirements. The advantage of the proposed method is its ability to reduce complexity, improve effectiveness, and consider personalized driving preferences. Five different typical scenarios at unsignalized intersections are simulated, and the results demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Kunyang Cai, Ting Qu, Bingzhao Gao, Hong Chen
Summary: This paper proposes a novel cooperative perception solution based on consensus theory to improve the accuracy and consistency for the detection and tracking of non-connected targets by combining V2X information.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yongjun Yan, Nan Li, Jinlong Hong, Bingzhao Gao, Jia Zhang, Hong Chen, Jing Sun, Ziyou Song
Summary: This study proposes an eco-coasting strategy that calculates the optimal timing and duration of coasting maneuvers using road information preview. By evaluating different coasting mechanisms, it is found that the engine start/stop method performs better in terms of fuel consumption and travel time. The online performance of the eco-coasting strategy is evaluated using Mixed Integer Model Predictive Control (MIMPC), and simulation results show that it achieves near-optimal performance and outperforms the rule-based method.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Ping Wang, Xiyue Zhang, Jianpeng Shi, Bin Gou, Lin Zhang, Hong Chen, Yunfeng Hu
Summary: This paper proposes an MPC-based control strategy to prevent vehicle rollover during high-speed driving. By considering tire force saturation and real-time rollover index, the control region is divided into different stability regions. State constraints are set based on driver behavior and road conditions to improve overall vehicle performance.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Automation & Control Systems
Xiao Hu, Hong Chen, Qiao Ren, Xun Gong, Ping Wang, Yunfeng Hu
Summary: This article proposes a well-developed method for the estimation and expansion of the vehicle stability region by improving the region of attraction (RoA) based on sums of squares (SOS) programming. The method reduces conservatism by formulating an improved SOS program with an optimization objective and a customized algorithm. The computational burden is reduced by using a feasibility prejudgment strategy and a dynamic search range. Simulations and hardware-in-the-loop experiments verify the effectiveness of the method.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Engineering, Civil
Yanjun Huang, Shuo Yang, Liwen Wang, Kang Yuan, Hongyu Zheng, Hong Chen
Summary: This paper proposes an efficient self-evolution method for reinforcement learning algorithms using a combination of SAC and BC. The method improves convergence efficiency without sacrificing the exploration advantage of reinforcement learning.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Yangyang Feng, Shuyou Yu, Encong Sheng, Yongfu Li, Shuming Shi, Jianhua Yu, Hong Chen
Summary: This paper proposes a hierarchical control strategy that considers the longitudinal and lateral coupling property of vehicle platoons. By using a predictive control scheme, the strategy predicts and maintains the vehicles on the designated lanes, avoiding the need to solve nonlinear optimization problems and reducing the computational burden. The joint simulation results demonstrate the effectiveness of the proposed strategy in terms of maintaining the velocity and safety distance of vehicles in both straight and curved road scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)