Article
Automation & Control Systems
Florian Dorfler, Jeremy Coulson, Ivan Markovsky
Summary: In this article, the connections between sequential system identification and control for linear time-invariant systems, known as indirect data-driven control, and a direct data-driven control approach are discussed. The direct approach seeks an optimal decision that is compatible with recorded data assembled in a Hankel matrix and robustified through appropriate regularizations. Two methods from subspace identification and control, subspace predictive control and low-rank approximation, are used to illustrate the results. It is concluded that direct and regularized data-driven control can be derived as convex relaxation of the indirect approach.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Aerospace
Mingying Huo, Lie Yang, Na Peng, Ce Zhao, Wenyu Feng, Ze Yu, Naiming Qi
Summary: This study proposes a fast costate estimation method derived from the Bezier-curve-based shaping approach for indirect low-thrust transfer trajectory optimization. The trajectory is rapidly designed using a shape-based method, and the estimated costate is used to solve the optimal control problem. Comparisons of costate estimation performance for different missions show that the proposed method is more efficient than random initialization.
AEROSPACE SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Giovanni Iacovelli, Luigi Alfredo Grieco
Summary: This study explores the use of drones for data relay and formulates a Mixed-Integer Non-Linear Programming problem to maximize data transmission. By combining convex optimization and Ant Colony Optimization algorithm, a quasi-optimal solution is obtained. The numerical results illustrate the effectiveness of the proposed solution in various parameter configurations compared to a benchmark algorithm.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Mingqiang Wang, Lei Zhang, Zhiqiang Zhang, Zhenpo Wang
Summary: Efficient trajectory planning for intelligent vehicles in dynamic environments is achieved through a hybrid approach combining sampling-based and numerical optimization-based methods. A risk field model is used to evaluate risks with static and moving obstacles. The sampling-based approach generates collision-free trajectory candidates, considering curve smoothness, collision risk, and travel time. The optimization-based method optimizes the behavior trajectory for safety, vehicle dynamics stability, and driving comfort. Simulation results demonstrate the competency of the proposed framework in generating high-quality trajectories in real-time.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Weitian Sheng, Bai Li, Xiang Zhong
Summary: This paper presents an autonomous parking trajectory planning method in unstructured environments with narrow passages using a hierarchical trajectory planner with a graph search layer and a numerical optimal control layer, which runs much faster than prevalent methods.
Article
Chemistry, Multidisciplinary
Fredy Juarez-Perez, Marco Antonio Cruz-Chavez, Rafael Rivera-Lopez, Erika Yesenia Avila-Melgar, Marta Lilia Erana-Diaz, Martin H. Cruz-Rosales
Summary: This paper introduces a hybrid genetic algorithm implemented in a grid environment to solve difficult instances of the flexible flow shop scheduling problem. The algorithm takes advantage of distributed computing power to perform local searches, resulting in near optimal solutions in fewer generations. Experimental results demonstrate that the proposed scheme achieves the upper bound in a wide range of test instances, and efficiently utilizes computational resources.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Aerospace
Maria Cerezo-Magana, Alberto Olivares, Ernesto Staffetti
Summary: This article studies the formation mission design problem for commercial aircraft in the presence of uncertainties. The research demonstrates that benefits can be achieved even in the presence of uncertainties.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Robotics
Jesus Tordesillas, Brett T. Lopez, Michael Everett, Jonathan P. How
Summary: This paper introduces FASTER (Fast and Safe Trajectory Planner), which enables UAVs to fly at high speeds in unknown environments while ensuring safety. The algorithm optimizes the local planner in both the free-known and unknown spaces to achieve high-speed trajectories, with a safe back-up trajectory always available in the free-known space.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Robotics
Jesus Tordesillas, Jonathan P. How
Summary: MADER is a 3-D decentralized and asynchronous trajectory planner for UAVs that generates collision-free trajectories in complex environments. It uses the MINVO basis to obtain smaller outer polyhedral representations, and guarantees safety with respect to other agents through a collision check-recheck scheme.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Automation & Control Systems
Lili Li, Linyang Song, Tieshan Li, Jun Fu
Summary: This article investigates the event-triggered output regulation problem for a networked flight control system with a switched system approach. An alternate event-triggered mechanism based on the subsystem model is proposed to address asynchronous switching and sufficient conditions for event-triggered asynchronous output regulation problem are solved. The proposed methods are proven to be effective with the F-18 aircraft model.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Aerospace
Yang Wang, Francesco Topputo
Summary: An efficient indirect method is proposed to determine fuel-optimal many-revolution low-thrust transfers in the presence of Earth-shadow eclipses. The shadow entrance and exit events are modeled as interior-point constraints. A two-level continuation scheme is introduced to generate many-revolution trajectories, taking into account the possibility of ill-conditioned state transition matrices when crossing the shadow edge. The computational framework integrates analytic derivatives, switching detection, and continuation, providing discontinuous bang-bang solutions and their gradients. Simulations of transfers from a geostationary transfer orbit to a geostationary orbit are conducted to showcase the effectiveness and efficiency of the developed method.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Computer Science, Software Engineering
Amin Babadi, Michiel van de Panne, C. Karen Liu, Perttu Hamalainen
Summary: This article proposes a novel method for exploring the dynamics of physically based animated characters and learning a task-agnostic action space to facilitate movement optimization. The method parameterizes actions as target states and learns a low-level control policy that drives the agent's state towards the targets. The approach improves trajectory and high-level policy optimization efficiency across multiple tasks and algorithms and provides visualizations demonstrating the benefits of using target states as actions.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Hardware & Architecture
Yang Wang, Yawen Chen, Zhaoming Lu, Xiangming Wen
Summary: This paper investigates the 3D trajectory design, beamwidth, and power allocation problems for mmWave UAV communication systems. A deep reinforcement learning (DRL) based framework, called intelligent flying-beamformer, is proposed to solve the non-convex optimization problem. Simulation results demonstrate the effectiveness of the proposed intelligent flying-beamformer in improving system capacity, especially through the optimization of beamwidth.
Article
Mechanics
Zheming Tong, Zhongqin Yang, Shuiguang Tong, Zekui Shu, Xiangkun Elvis Cao
Summary: An enstrophy dissipation-based hybrid optimization (EDHO) approach, combining the advantages of sparrow search algorithm and Non-dominated Sorting Genetic Algorithm III (NSGA-III), was proposed to enlarge the Preferred Operating Range (POR) of a slanted axial flow pump (SAFP). The overall hydraulic performance was optimized with a special focus on energy loss mechanism. The results showed that eddy dissipation contributed the most energy loss under partial loads, while shear dissipation also played a significant role under overload conditions.
Article
Engineering, Civil
Wonteak Lim, Seongjin Lee, Myoungho Sunwoo, Kichun Jo
Summary: This paper proposes a hybrid trajectory planning scheme that integrates the strength of sampling and optimization methods to solve the problem of safe trajectory planning in dynamic driving environments. The sampling method is used for lateral movement while the numerical optimization method is used for longitudinal movement, helping the planner generate adaptive trajectories in various situations.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)