Article
Automation & Control Systems
Yu Zhang, Mingfan Xu, Yechen Qin, Mingming Dong, Li Gao, Ehsan Hashemi
Summary: The multiobjective adaptive cruise control proposed in this article is based on a novel integrated structure, which consists of an adaptive controller and switching mechanism. The controller combines upper and lower layers for switching modes to avoid collisions and maintain tracking capability in complex driving scenarios. The effectiveness, real-time performance, and robustness of the integrated structure are validated through complex scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Mitsuhiro Hattori, Osamu Shimizu, Sakahisa Nagai, Hiroshi Fujimoto, Koji Sato, Yusuke Takeda, Takuma Nagashio
Summary: In this study, a novel optimization method called quadrant DP (QDP) is proposed for ecological adaptive cruise control (ACC). QDP divides the DP table into four quadrants and performs most computations offline, reducing the computation cost while achieving globally optimal results.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Energy & Fuels
Dongmei Wu, Quan Yuan, Changqing Du, Fuwu Yan, Yang Li
Summary: This paper proposes a novel optimization method with dynamic weight factors based on road classification for the predictive cruise control system of 4WD electric vehicles. The simulation results show that this method can improve the adaptability and energy-saving performance of PCC on different types of roads.
Article
Energy & Fuels
Ronghui Zhang, Na Wu, Zihan Wang, Kening Li, Zhumei Song, Zhenting Chang, Xia Chen, Fan Yu
Summary: This paper presents a constrained hybrid optimal model predictive control method for the mobile energy storage system of Intelligent Electric Vehicle (IEV). The proposed method includes an adaptive cruise control system, hierarchical control structure for active safety control and energy flow management, and an electronic longitudinal control system. Simulation results show that the IEV with the designed hybrid controller can adaptively track following vehicles and reduce the possibility of collision with optimal energy flow management.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Leopoldo Vite, Luis Juarez, Marco A. Gomez, Sabine Mondie
Summary: We investigate the stabilization problem of an Adaptive Cruise Control (ACC) vehicle platoon with input-delay, proposing a dynamic predictor for input-delay compensation and addressing robustness issues. Each vehicle achieves velocity matching and safe inter-vehicular distance using a proportional-integral controller combined with a dynamic predictor. String stability of the closed-loop system, i.e., the ability to attenuate fluctuations, is analyzed in the frequency domain. Simulations of a platoon of five vehicles demonstrate the effectiveness of the proposed control scheme.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Energy & Fuels
Aaron Rabinowitz, Farhang Motallebi Araghi, Tushar Gaikwad, Zachary D. Asher, Thomas H. Bradley
Summary: This study thoroughly evaluates the application of Predictive Optimal Energy Management Strategy (POEMS) in connected vehicles using 10 to 20 s predicted velocity, comparing different signal categories and models to analyze their effects on prediction fidelity. Results show that high-fidelity ego future speed prediction can significantly improve fuel economy, approaching the upper limit achievable with POEMS.
Article
Computer Science, Artificial Intelligence
Bolin Gao, Qien Chen, Yanwei Liu, Keke Wan, Keqiang Li
Summary: Based on a vehicle-cloud hierarchical architecture, this paper proposes a predictive cruise control for urban buses, which estimates the dissipation time of the intersection queue to predict changes in traffic state. The proposed method saves 44.94%-56.74% of energy consumption and at least 26.8s of waiting time compared to human drivers, and 22.72%-41.27% of energy consumption compared to vehicle with the Intelligent Vehicle Infrastructure Cooperative Systems.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Automation & Control Systems
Saleh Albeaik, Trevor Wu, Ganeshnikhil Vurimi, Fang-Chieh Chou, Xiao-Yun Lu, Alexandre M. Bayen
Summary: This article investigates an alternative strategy for developing control systems for heavy duty trucks, which is configuration agnostic and relies on model-free deep reinforcement learning. The study validates the performance and robustness of the control systems through simulation and field experiments on two differently configured trucks.
CONTROL ENGINEERING PRACTICE
(2022)
Article
Automation & Control Systems
Hong Mo, Yinghui Meng, Fei-Yue Wang, Dongrui Wu
Summary: This paper proposes a new vehicle-following control strategy, which effectively addresses traffic congestion and improves road traffic safety by integrating different control models and methods.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Engineering, Electrical & Electronic
Hakan Basargan, Andras Mihaly, Peter Gaspar, Olivier Sename
Summary: This paper proposes an integration method for an intelligent, road-adaptive, semi-active suspension control and cruise control system. The road-adaptive, semi-active suspension controller is designed through the linear parameter-varying (LPV) method, and road adaptation is performed with a road adaptivity algorithm that considers road irregularities and vehicle velocity. The designed controllers are integrated, and the operation of the integrated method is validated in a TruckSim simulation environment.
Article
Chemistry, Analytical
Ivana Shopovska, Ana Stojkovic, Jan Aelterman, David Van Hamme, Wilfried Philips
Summary: Intelligent driver assistance systems are increasingly popular and have the ability to detect vulnerable road users. However, standard imaging sensors perform poorly in strong illumination contrast conditions. This study focuses on the use of HDR imaging sensors and the need for tone mapping in vehicle perception systems. The proposed DI-TM method achieves the best performance in terms of detection metrics in challenging dynamic range conditions, with a 13% improvement compared to existing methods.
Article
Engineering, Electrical & Electronic
Zhuwei Wang, Senfan Jin, Lihan Liu, Chao Fang, Meng Li, Song Guo
Summary: Connected cruise control (CCC) is an advanced driver assistance system that uses wireless vehicle-to-vehicle (V2V) communication technology to improve control stability and driving safety. This study investigates the design of a deep reinforcement learning (DRL) controller for CCC in high-dynamic traffic scenarios, considering time-varying leading velocity and communication delays. The proposed algorithm, based on deep deterministic policy gradient (DDPG), trains actor and critic networks to generate intelligent control strategies by maximizing a quadratic reward function. The effectiveness and convergence of the algorithm are verified through numerical simulations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Kaixiang Zhang, Kaian Chen, Zhaojian Li, Jun Chen, Yang Zheng
Summary: In this paper, a privacy-preserving data-enabled predictive control scheme is proposed for CAVs in a mixed traffic environment. The scheme addresses the issue of eavesdroppers trying to infer the vehicles' state and input information, and utilizes affine masking to conceal the true signals. Numerical simulations demonstrate the effectiveness of the proposed scheme.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Thermodynamics
Chaofeng Pan, Aibao Huang, Jian Wang, Liao Chen, Jun Liang, Weiqi Zhou, Limei Wang, Jufeng Yang
Summary: Adaptive cruise control (ACC) is in line with the current emphasis on safety, energy saving and environmental protection. The Energy-Optimal Adaptive Cruise Control (EACC) strategy based on Model Predictive Control (MPC) algorithm achieves energy optimization for pure electric vehicles, balancing tracking performance and economy under various working conditions.
Article
Thermodynamics
Haoming Gao, Xuanming Zhang, Xiaohua Zeng, Dongpo Yang, Dafeng Song, Lanqi Zhou
Summary: This paper proposes a hierarchical control architecture for HEV-PCC based on convex optimization, which incorporates road gradient information from high-precision maps to further enhance fuel economy for hybrid electric vehicles. Simulation analysis and hardware-in-loop testing validate that this method achieves an average fuel economy improvement of 9.45% compared to the equivalent consumption minimization strategy with constant speed cruising.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Energy & Fuels
Xiaosong Hu, Lars Johannesson, Nikolce Murgovski, Bo Egardt
Article
Automation & Control Systems
Xiaosong Hu, Jiuchun Jiang, Bo Egardt, Dongpu Cao
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2015)
Article
Engineering, Electrical & Electronic
Viktor Larsson, Lars Johannesson, Bo Egardt
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2015)
Article
Automation & Control Systems
Xiaosong Hu, Nikolce Murgovski, Lars Mardh Johannesson, Bo Egardt
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2015)
Article
Automation & Control Systems
Mikael Thor, Bo Egardt, Tomas McKelvey, Ingemar Andersson
CONTROL ENGINEERING PRACTICE
(2014)
Article
Automation & Control Systems
Mikael Thor, Bo Egardt, Tomas McKelvey, Ingemar Andersson
CONTROL ENGINEERING PRACTICE
(2014)
Article
Thermodynamics
Xiaosong Hu, Shengbo Eben Li, Zhenzhong Jia, Bo Egardt
Article
Automation & Control Systems
Bo Egardt, Nikolce Murgovski, Mitra Pourabdollah, Lars Johanne Sson Mardh
IEEE CONTROL SYSTEMS MAGAZINE
(2014)
Article
Automation & Control Systems
Xiaosong Hu, Rui Xiong, Bo Egardt
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2014)
Article
Engineering, Civil
Viktor Larsson, Lars Johannesson Mardh, Bo Egardt, Sten Karlsson
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2014)
Article
Engineering, Civil
Xiaosong Hu, Nikolce Murgovski, Lars Mardh Johannesson, Bo Egardt
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2014)
Article
Engineering, Electrical & Electronic
Mitra Pourabdollah, Nikolce Murgovski, Anders Grauers, Bo Egardt
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2013)
Article
Engineering, Electrical & Electronic
Nikolce Murgovski, Lars Mardh Johannesson, Bo Egardt
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2014)
Proceedings Paper
Automation & Control Systems
Viktor Larsson, Lars Johannesson, Bo Egardt
2014 EUROPEAN CONTROL CONFERENCE (ECC)
(2014)
Article
Automation & Control Systems
Subhashis Nandy
Summary: This research focuses on the design and stability analysis of nonlinear controllers for an electrically driven marine cycloidal propeller, along with estimating various parameters using the Extended Kalman Filter. The controller is defined using an efficient physics-based model and is able to accurately process multiple control signals. The robustness of the controller is assessed using Monte Carlo simulation, and its performance is evaluated through validation investigations.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Lucas C. Borin, Guilherme Hollweg, Caio R. D. Osorio, Fernanda M. Carnielutti, Ricardo C. L. F. Oliveira, Vinicius F. Montagner
Summary: This work presents a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of control gains is guided by high-fidelity simulations and particle swarm optimization algorithm, considering various normal and abnormal operating conditions. The proposed design ensures superior performance compared with other current control designs.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Wei He, Xiang Wang, Mohammad Masoud Namazi, Wangping Zhou, Josep M. Guerrero
Summary: The main objective of this paper is to develop a reduced-order adaptive state observer for a large class of DC-DC converters with constant power load, in order to estimate their unavailable states and unknown parameter and achieve an output feedback control scheme. The observer is designed using a generalized parameter estimation based observer technique and dynamic regressor extension and mixing method. The comparison study shows that the observer has the advantage of verifying the observability of the systems for exponential convergence without any extra excitation condition.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Te Zhang, Bo Zhu, Lei Zhang, Qingrui Zhang, Tianjiang Hu
Summary: This paper introduces a control technique called time-varying uncertainty and disturbance estimator (TV-UDE) which extends the classic UDE approach to handle more complicated issues. By combining TV-UDE with a nominal dynamic output-feedback controller, robust control for uncertain second-order attitude control systems without velocity measurements is achieved. Numerical simulations and physical experiments on a 2-DOF AERO attitude helicopter platform demonstrate the effectiveness of the proposed design in reducing steady-state errors and avoiding issues caused by high-gain estimation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kanishke Gamagedara, Taeyoung Lee, Murray Snyder
Summary: This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle capable of autonomously taking off and landing on a moving vessel in ocean environments. The flight hardware consists of a general-purpose computing module connected to a low-cost inertial measurement unit, real-time kinematics GPS, motor speed controller, and a camera through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading to execute control, estimation, and communication tasks simultaneously. The proposed flight system is verified through autonomous flight experiments on a research vessel in Chesapeake Bay, utilizing real-time kinematics GPS for relative positioning and vision-based autonomous flight for shipboard launch and landing.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yun Zhu, Kangkang Zhang, Yucai Zhu, Pengfei Jiang, Jinming Zhou
Summary: In this study, a three-term Dynamic Matrix Control (DMC) algorithm using quadratic programming is developed and compared with the traditional two-term DMC algorithm. Simulation studies and real-life tests show that the three-term DMC algorithm outperforms the two-term DMC algorithm in control effectiveness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Jayu Kim, Taehoon Lee, Cheol-Joong Kim, Kyongsu Yi
Summary: This paper presents a data-based model predictive control method for a semi-active suspension system. The method utilizes a continuous damping controller and a stiffness controller to improve ride comfort and reduce vehicle pitch motion. Gaussian process regression is also used to compensate for model parameter uncertainties. The algorithm has been verified through computer simulations and vehicle tests, demonstrating its effectiveness and robustness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kunpeng Zhang, Jikang Gao, Zongqi Xu, Hui Yang, Ming Jiang, Rui Liu
Summary: A improved dynamic programming model is proposed in this paper for joint operation optimization of virtual coupling of heavy-haul trains. By simultaneously optimizing the headway and energy savings, as well as performing locomotive engineering advisory analysis, significant improvements in train performance can be achieved.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Demian Garcia-Violini, Yerai Pena-Sanchez, Nicolas Faedo, Fernando Bianchi, John V. Ringwood
Summary: This study presents a model invalidation methodology for wave energy converters (WECs) that can effectively handle dynamic uncertainty and external noise. The results indicate that neglecting dynamic uncertainty can lead to overestimation of performance, highlighting the importance of accurate dynamic description for estimating control performance.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Shengyang Lu, Yue Jiang, Xiaojun Xu, Hanxiang Qian, Weijie Zhang
Summary: This paper proposes an adaptive heading tracking control strategy based on wheelbase changes for unmanned ground vehicles (UGVs) with variable configuration. The strategy adjusts the wheelbase according to different working conditions to optimize driving performance. The impact of changing wheelbase on sideslip angle and heading angle is analyzed, and a robust-active disturbance rejection control method is developed to achieve desired front-wheel steering angle. A torque distribution method based on tire load rate and real-time load is applied to enhance longitudinal stability.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Domenico Dona, Basilio Lenzo, Paolo Boscariol, Giulio Rosati
Summary: This paper proposes a new method for designing minimum energy trajectories for servo-actuated systems and demonstrates its accuracy and effectiveness through numerical comparisons and experimental validation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Haolin Wang, Luyao Zhang, Yao Mao, Qiliang Bao
Summary: This paper proposes a method of transforming the core element of ADRC, ESO, into a novel fuzzy self-tuning observer structure to improve the stability of LOS in the electro-optical tracking system. It effectively solves the conflict between disturbance rejection ability and noise attenuation ability in traditional ESO.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Alejandro Toro-Ossaba, Juan C. Tejada, Santiago Rua, Juan David Nunez, Alejandro Pena
Summary: This work presents the development of a myoelectric Model Reference Adaptive Controller (MRAC) with an Adaptive Kalman Filter for controlling a cable driven soft elbow exoskeleton. The proposed MRAC controller is effective in both passive and active control modes, showing good adaptability and control capabilities.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Mehrad Jaloli, Marzia Cescon
Summary: This study presents an advanced multi-agent reinforcement learning (RL) strategy for personalized glucose regulation, which is shown to improve glucose regulation and reduce the risk of severe hyperglycemia compared to traditional therapy.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yingming Tian, Kenan Du, Jianfeng Qu, Li Feng, Yi Chai
Summary: This paper investigates the control strategy for PMSM with position sensor fault in railway. A learning observer-based control strategy is proposed, which achieves high-precision estimation of electromotive force and accelerates speed response.
CONTROL ENGINEERING PRACTICE
(2024)