Article
Engineering, Civil
Xiao Pan, Boli Chen, Stelios Timotheou, Simos A. Evangelou
Summary: This paper addresses the speed planning problem for connected and autonomous vehicles (CAVs) at an unsignalized intersection with consideration of turning maneuvers. It is shown that the underlying optimization problem, subject to safety constraints, can be formulated as two second-order cone programs with convexification and relaxation. The investigation of Pareto optimal solutions highlights the importance of optimizing the trade-off between travel time and energy consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Aerospace
Nicholas Ortolano, David K. Geller, Aaron Avery
Summary: Convex optimization techniques are used for trajectory planning in orbital rendezvous and proximity operations. Two linear dynamics models are studied to develop an algorithm based on a second-order cone program for generating optimal trajectories. Results are presented for various scenarios in a nonlinear orbital simulation.
JOURNAL OF THE ASTRONAUTICAL SCIENCES
(2021)
Review
Engineering, Aerospace
Yanquan Zhang, Baolong Zhu, Min Cheng, Shunli Li
Summary: This paper presents a guidance algorithm based on successive convexification for generating fuel-optimal trajectories of spacecraft with 6 degrees of freedom subject to multiple path constraints. The algorithm divides the maneuver process into fly-around and docking phases and incorporates collision avoidance and plume impingement constraints. The original guidance problem is converted into a series of convex subproblems and solved iteratively using convex programming. The algorithm is demonstrated to be effective through numerical simulations.
AEROSPACE SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Civil
Qing Gu, Guoxing Bai, Guodong Wang, Yu Meng, Li Liu
Summary: This paper proposes an optimal trajectory planning method for turning maneuvers of LHD vehicles. By using a 3D key factors search strategy and optimization method, the algorithm's online execution ability is improved and the driving time of LHD is reduced.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Sean Kragelund, Claire Walton, Isaac Kaminer, Vladimir Dobrokhodov
Summary: This article presents a computational framework for planning mine countermeasures (MCM) search missions by autonomous vehicles, utilizing generalized optimal control (GenOC) to optimize search performance, developing tunable sensor models, and incorporating sonar detection models for optimization.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2021)
Article
Engineering, Civil
Shian Wang, Raphael Stern, Michael W. Levin
Summary: This article focuses on smoothing unstable traffic flow by controlling autonomous vehicles (AVs), aiming to minimize vehicle speed perturbation. A dynamic model for mixed traffic flow with both human-driven vehicles (HVs) and AVs is developed, and an optimal control problem is formulated based on Pontryagin's minimum principle to determine the optimal AV control policy. Numerical results demonstrate the effectiveness of the proposed approach in traffic smoothing and improvement on vehicle fuel economy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Runqi Chai, Antonios Tsourdos, Senchun Chai, Yuanqing Xia, Al Savvaris, C. L. Philip Chen
Summary: This article studies the problem of trajectory optimization for autonomous ground vehicles with the consideration of irregularly placed on-road obstacles and multiple maneuver phases. It proposes a novel desensitized trajectory optimization method to provide an effective alternative for addressing the complexity of the mission formulation.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Wenbo Sun, Fangni Zhang, Wei Liu, Qingying He
Summary: This paper investigates the potential of improving overall traffic and energy efficiency by controlling a proportion of connected and autonomous vehicles (CAVs) in a mixed traffic corridor. The proposed control framework shows promising results in numerical studies, demonstrating its effectiveness in improving road throughput.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Yixiao Zhang, Rui Hao, Tingting Zhang, Xiaohan Chang, Zepeng Xie, Qinyu Zhang
Summary: This paper presents a general dedicated intersection coordination framework for autonomous vehicles, which aims to improve vehicle coordination and motion planning at road intersections. The framework consists of a high-level planner and a low-level planner, which work together to generate reference trajectories, feasible tunnels, and practical trajectories. Simulations and experiments show that the proposed framework achieves significant performance advantages in various traffic metrics. Furthermore, the high-level planner effectively eliminates possible deadlocks among autonomous vehicles, which is rarely discussed in existing investigations.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yu-Hsin Hsu, Rung-Hung Gau
Summary: In this paper, a reinforcement learning approach combined with optimization theory is proposed for collision avoidance and trajectory planning in UAV communication networks. Simulation results demonstrate the superiority of the proposed approach over other methods.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Aerospace
Mohammadreza Radmanesh, Balaji Sharma, Manish Kumar, Donald French
Summary: This paper focuses on the cooperative path planning application of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in wildfires, utilizing simulation to model wildfire growth and employing space-time Kalman Filtering for wildfire estimation. The research aims to establish safe path planning strategies for UGVs traveling in wildfire-affected areas based on UAV data gathering.
CHINESE JOURNAL OF AERONAUTICS
(2021)
Article
Engineering, Aerospace
Youngkwang Kim, Sang-Young Park, Pureum Kim
Summary: This study presents a novel impulsive trajectory optimization algorithm called AIRTOP for near-fuel-optimal rendezvous under perturbations. AIRTOP is designed to improve the accuracy of rendezvous constraints while retaining first-order optimality, considering various orbital perturbations. To eliminate constraint errors, AIRTOP solves the linearized impulsive rendezvous problem recursively using the dual-primal optimization algorithm. Three numerical simulations near circular and elliptical orbits demonstrate the effectiveness and computational efficiency of AIRTOP compared to other methods.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Computer Science, Information Systems
Edoardo Pagot, Mattia Piccinini, Enrico Bertolazzi, Francesco Biral
Summary: This paper presents a framework for planning and executing autonomous parking maneuvers in complex parking scenarios. It formulates a minimum-time optimal control problem for trajectory planning using an indirect optimal control approach. A smooth penalty function is devised for collision avoidance with optimal control, and an effective technique is adopted for computing an initial solution guess. The planned parking maneuvers are tracked with an original pseudo-neural feedforward-feedback steering controller, outperforming other techniques. The framework is validated in challenging narrow parking scenarios with different conditions.
Article
Telecommunications
Chengcai Wang, Ao Wu, Yueqi Hou, Xiaolong Liang, Luo Xu, Xiaomo Wang
Summary: To prevent attackers from breaking through the interception blockade, deploying multiple UAV swarms on the interception line is a new combat style. An optimal deployment optimization model is proposed and the analytical expression of the optimal deployment positions is derived to solve the optimal deployment of swarm positions in cooperative interception. The proposed optimal deployment is compared with uniform deployment and random deployment to validate the theoretical analysis.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Engineering, Aerospace
Mi Wang, Huai-Ning Wu
Summary: This article studies the autonomous game control problem for spacecraft rendezvous by using the adaptive perception and interaction. It proposes an autonomous game control method for spacecraft a by formulating the rendezvous system as a two-player linear quadratic differential game with unknown intent of spacecraft o, and using the adaptive perception and interaction. The method removes the requirement for knowing the intent of spacecraft o, relaxes the persistent excitation condition in traditional adaptive estimation methods, and guarantees the asymptotic stability of the rendezvous system.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Physics, Multidisciplinary
Lin Cheng, ZhenBo Wang, FangHua Jiang, JunFeng Li
SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY
(2020)
Article
Engineering, Aerospace
Lin Cheng, Zhenbo Wang, Fanghua Jiang, Junfeng Li
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2020)
Article
Engineering, Aerospace
Lin Cheng, Zhenbo Wang, Fanghua Jiang, Junfeng Li
Summary: An adaptive neural network control approach is proposed in this study to achieve accurate and robust control of nonlinear systems with unknown dynamics. The study focuses on system transformation, control learning algorithm, and development of an adaptive neural network controller. Simulation results substantiate the effectiveness of the proposed techniques and controller's robustness.
ADVANCES IN SPACE RESEARCH
(2021)
Article
Engineering, Aerospace
Lin Cheng, Fanghua Jiang, Zhenbo Wang, Junfeng Li
Summary: This article proposes an intelligent predictor-corrector entry guidance approach for lifting hypersonic vehicles, which achieves real-time and safe control of entry flights using deep neural networks and constraint management techniques. The experiments verify high approximation accuracy of the DNN and demonstrate the capability of trajectory correction with a 20Hz update frequency. The proposed method provides high-precision, safe, and robust entry guidance for hypersonic vehicles.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Food Science & Technology
Ran Yang, Zhenbo Wang, Jiajia Chen
Summary: The study developed and validated an integrated approach combining mechanistic-modeling and machine-learning for efficient food product design with better heating uniformity. The integrated approach showed higher efficiency in optimizing product thickness of different shapes compared to the parametric sweep approach based solely on mechanistic modeling, with improvements ranging from 45.9% to 62.1%.
Article
Engineering, Aerospace
Lin Cheng, Peng Shi, Shengping Gong, Zhenbo Wang
Summary: In this study, an improved indirect method is proposed to achieve real-time trajectory optimization of fuel-optimal powered planetary landings. By deriving analytical shooting equation expressions and using a practical homotopy technique, the computational efficiency is significantly improved. The results show that the developed method can obtain a fuel-optimal landing trajectory in a short period of time.
CHINESE JOURNAL OF AERONAUTICS
(2022)
Article
Engineering, Multidisciplinary
XuXing Huang, Bin Yang, Shuang Li, ZhenBo Wang
Summary: This study proposes an efficient high-accuracy north-south station-keeping (NS-SK) strategy, which reduces the accumulation of secular drift through an averaging method, dampens long-period oscillation using impulse and finite-thrust propulsions, and introduces a fuel-optimal cycle and fixed-interval cycle to enhance the NS-SK strategy. Numerical simulations show that the improved strategy achieves high-accuracy NS-SK with minimal fuel consumption, and the fixed-interval cycle can achieve higher NS-SK accuracy while consuming less fuel.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2021)
Article
Engineering, Aerospace
Lin Cheng, Zhenbo Wang, Shengping Gong
Summary: This research proposes an adaptive control approach using two neural networks to achieve precise and robust control for hypersonic flight. The algorithms train the neural networks to learn flight dynamics and improve the dynamic performance of the controller, addressing the difficulty of obtaining accurate dynamical models.
Article
Engineering, Aerospace
Boris Benedikter, Alessandro Zavoli, Zhenbo Wang, Simone Pizzurro, Enrico Cavallini
Summary: This paper outlines a novel approach for designing optimal space trajectories under significant uncertainty. It employs finite-horizon covariance control and a robust feedback controller to plan an optimal path and compensate for disturbances during flight. A mindful convexification strategy is used to convert the nonlinear control problem into a convex optimization problem. The relaxation of the problem is proven to be lossless through optimal control theory and numerical experiments.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2022)
Article
Engineering, Aerospace
Jingji Wang, Shuang Li, Chunyang Liu, Zhenbo Wang
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Automation & Control Systems
Yang Shi, Zhenbo Wang, Tim J. LaClair, Chieh (Ross) Wang, Yunli Shao
Summary: Recent advances in Connected and Automated Vehicle (CAV) technologies have provided new opportunities for safe, efficient, and sustainable transportation systems. This paper proposes a novel speed control method for CAVs that minimizes fuel consumption and reduces idling time at signalized intersections. The method uses an optimal control problem formulation based on upcoming traffic signal information and utilizes pseudospectral discretization and sequential convex programming to improve computational efficiency.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Robotics
Chapel Reid Rice, Spencer Thomas McDonald, Yang Shi, Hao Gan, Won Suk Lee, Yang Chen, Zhenbo Wang
Summary: This paper presents a drone-enabled autonomous pollination system (APS) that utilizes modules such as environment sensing, flower perception, path planning, flight control, and pollination mechanisms. The authors focus on approaches to flower perception, path planning, and flight control modules. The proposed system is tested within a model predictive control (MPC) framework, demonstrating computational savings and embedded adjustments to uncertainty.
Article
Engineering, Aerospace
Brian G. Coulter, Daning Huang, Zhenbo Wang
Summary: This paper discusses the importance of integrated design frameworks covering high-fidelity disciplinary models such as aerodynamics and trajectory modeling, and introduces an energy-based problem formulation and optimization method for hypersonic vehicle design. Finally, a novel, iterative, data-driven framework is established using Bayesian optimization and machine learning to integrate these disciplinary models and successively search for the geometry that enables optimal mission performance.
JOURNAL OF AIRCRAFT
(2022)
Editorial Material
Engineering, Aerospace
Boris Benedikter, Alessandro Zavoli, Zhenbo Wang, Simone Pizzurro, Enrico Cavallini
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Chemistry, Multidisciplinary
Yang Shi, Zhenbo Wang, Tim J. LaClair, Chieh (Ross) Wang, Yunli Shao, Jinghui Yuan
Summary: The advent of connected vehicle technology brings new possibilities for revolutionizing future transportation systems. This paper proposes a novel data-driven traffic signal control method that combines deep learning and reinforcement learning techniques. By incorporating a compressed representation of the traffic states, the proposed method overcomes limitations in defining the action space, offering more practical and flexible signal phases. Simulation results demonstrate the convergence and robust performance of the proposed method compared to existing benchmark methods.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Aerospace
Andre F. P. Ribeiro, Carlos Ferreira, Damiano Casalino
Summary: This study compares a filament-based free wake panel method to experimental and validated numerical data in order to simulate propeller slipstreams and their interaction with aircraft components. The results show that the free wake panel method is able to successfully capture the slipstream deformation and shearing, making it a useful tool for propeller-wing interaction in preliminary aircraft design.
AEROSPACE SCIENCE AND TECHNOLOGY
(2024)
