Article
Engineering, Aerospace
Qingyu Qu, Kexin Liu, Wei Wang, Jinhu Lu
Summary: This article focuses on the relative position tracking problem of autonomous spacecraft rendezvous with collision avoidance requirement. It proposes an exploration-adaptive deep deterministic policy gradient (DDPG) algorithm for training a definite control strategy. By introducing adaptive noise and a metalearning-based idea, it reduces energy consumption and adapts to other similar scenarios effectively.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Engineering, Aerospace
Kosuke Ikeya, Kaiwen Liu, Anouck Girard, Ilya Kolmanovsky
Summary: This paper presents a learning-based reference governor (LRG) method for spacecraft automated rendezvous, proximity maneuvering, and docking (ARPOD) operations, to enforce safety constraints. The LRG method replaces the spacecraft dynamics model with learning and guarantees constraint satisfaction during and after the learning process. Three case studies are conducted to demonstrate the benefits of the LRG method in ARPOD missions.
JOURNAL OF SPACECRAFT AND ROCKETS
(2023)
Article
Engineering, Aerospace
Xun Wang, Yanyan Li, Xueyang Zhang, Rui Zhang, Daoning Yang
Summary: This study investigates model predictive control (MPC) for spacecraft close-proximity maneuvering. It presents a method to improve the performance and computational efficiency of MPC for rendezvous and docking with both nonrotating and rotating client spacecraft. The proposed method utilizes an ellipsoid and linearization technique to handle collision avoidance constraints and derives an adaptive convex programming algorithm suitable for real-time implementation.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Automation & Control Systems
Qinglei Hu, Biru Chi
Summary: This article investigates the problem of autonomous spacecraft rendezvous and docking under the presence of space obstacles, path constraints, and thrust limitations. A combination scheme of guidance and control is proposed using the explicit reference governor (ERG) framework to ensure system stabilization and constraints satisfaction. The artificial potential function (APF) method is employed to guide a collision-free trajectory and the constraints are satisfied by limiting the states within the safe invariant set. Furthermore, a simplified method is proposed to obtain the maximum bound of the Lyapunov-based invariant sets for input boundedness and collision avoidance. The convergence of the system under the potential field is proven through Lyapunov stability analysis. Numerical simulation results demonstrate the comprehensive validation and good performance of the proposed method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Aerospace
Wanqing Zhang, Wanchun Chen, Wenbin Yu
Summary: A new guidance law is proposed to target a maneuvering target with impact angle and terminal acceleration constraints. The impact angle constraint is addressed by solving an optimal guidance problem with time-varying target's maneuvering acceleration. The closed-form solutions of the new guidance are derived and a linear time-varying system is obtained for analytical solving. The stability domain of the guidance coefficients is determined by analyzing the generalized solutions, ensuring the convergence of missile's maneuvering acceleration to zero.
Article
Engineering, Aerospace
Xiangtian Zhao, Shijie Zhang
Summary: This paper investigates the problem of position tracking and attitude synchronization for spacecraft rendezvous and docking with a tumbling target. By introducing a novel artificial potential function and adaptive control strategy, the paper achieves position tracking and attitude synchronization, while mitigating input saturation using a linear anti-windup compensator. The effectiveness and robustness of the proposed control strategy is demonstrated through a specific simulation scenario.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Aerospace
Xiangtian Zhao, Shijie Zhang
Summary: This paper develops an integrated framework for path planning and control in spacecraft rendezvous based on image features. Offline path planning generates desired image trajectories, and a robust image-based visual servoing controller is designed for tracking. Comparative studies with conventional control schemes are conducted through numerical simulations.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2022)
Article
Automation & Control Systems
Lu Cao, Bing Xiao
Summary: This article proposes a suboptimal velocity artificial potential-based control scheme to provide obstacle avoidance capability for spacecraft on-orbital services and docking. The approach utilizes an ellipsoid model and an eigenvalue algorithm to accurately describe the spacecraft and obstacles. It also uses a potential sigmoid function to generate repulsive force and a velocity artificial potential function-based controller to ensure a safe rendezvous with reduced fuel cost.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2022)
Review
Automation & Control Systems
Bharani P. Malladi, Ricardo G. Sanfelice, Eric A. Butcher
Summary: The problem of rendezvous, proximity operations, and docking of an autonomous spacecraft can be divided into three phases: rendezvous, docking, and docked. Different control algorithms are required for each phase due to the different tasks and constraints. A hybrid systems approach is used to study the problem, characterizing individual controllers and their properties needed to solve the problem within each phase.
ANNUAL REVIEWS IN CONTROL
(2021)
Article
Engineering, Aerospace
David Paolo Madonna, Mauro Pontani, Paolo Gasbarri
Summary: This study addresses the problem of attitude maneuvering of a spacecraft with flexible solar panels in response to debris detection and collision avoidance scenarios. The research introduces efficient strategies for rotating the solar panels to maximize irradiation or minimize oscillations. A new nonlinear reduced-attitude control law is proposed to improve the performance of attitude maneuvers.
Article
Engineering, Aerospace
Akan Selim, Ibrahim Ozkol
Summary: The author studied a rendezvous mission with a tumbling space object using a novel three-phase mission design architecture based on Ensemble Optimal Control and warm-start Bellman Pseudospectral Optimal Control. They developed a software called SC-EPOCS to solve the ensemble optimal control problem and introduced the concept of checkpoints for transition trajectory planning. Through the use of Deep Neural Networks and the Covector Mapping Theorem, optimal trajectories were derived and a recursive optimal control problem was solved, accounting for state estimation errors. The approach was proven to be feasible, robust, and optimal.
Article
Engineering, Aerospace
Yufeng Gao, Dongyu Li, Shuzhi Sam Ge
Summary: This article proposes a method to improve control performance and reduce energy consumption for the short-range relative motion of the on-orbit service spacecraft during rendezvous and docking missions. By using time-synchronized stability and fixed-time-synchronized stability controllers, the system trajectory tends to a straight line, suppressing redundant motion components and reducing energy loss. Furthermore, the article introduces the linear combination theorem of the ratio persistence property, enriching the theoretical tools for the time-synchronized control method.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Automation & Control Systems
Qinglei Hu, Yueyang Liu, Youmin Zhang
Summary: This article describes a practical solution for path-constrained proximity maneuvers of spacecraft, utilizing controller enforcement of actuator magnitude constraints without velocity measurement. The controller is constructed from a potential function method repelling the spacecraft from possible collisions, overcoming the local minima problem. The control capability can be estimated and adjusted by changing feedback gains under any control limit, with explicit calculation of specific performance for guaranteed safety.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Engineering, Aerospace
Ahmed Mehamed Oumer, Dae-Kwan Kim
Summary: This paper proposes a fuel optimization and guidance technique for Autonomous Rendezvous and Docking (RVD) suitable for onboard computation on CubeSats. By dividing the guidance problem into separate orbit and attitude guidance problems, the computation time is reduced. Simulation results show that the proposed method performs better in terms of fuel efficiency compared to conventional methods.
Article
Automation & Control Systems
Qi Li, Chong Sun, Shuo Song, Qiuxiong Gou, Zhiqi Niu
Summary: This paper addresses the robust quantized proximity control problem for spacecraft with uncertain system parameters, external disturbances, and safety constraints. By establishing a nonconvex forbidden zone and utilizing a novel repulsive potential function, an adaptive safety controller is proposed to ensure ultimate boundedness of all system signals.
Article
Automation & Control Systems
Nan Li, Sijia Geng, Ilya Kolmanovsky, Anouck Girard
Summary: In this article, a novel reference governor (RG) scheme is proposed for prestabilized linear sampled-data systems to meet pointwise-in-time constraints in the presence of bounded disturbances and uncertain input and/or measurement delays. By deriving an explicit bound on the system response to step changes in the reference signal using the logarithmic norm, this RG scheme provides a closed-form solution for updating the reference signal at sample time instants, ensuring both sample-time and intersample constraint satisfaction. The closed-form expression of the proposed RG scheme requires minimal computational effort, making it suitable for systems with limited computing capability.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Liang Lu, Daniel Limon, Ilya Kolmanovsky
Summary: This paper presents a self-triggered MPC controller design strategy for tracking piecewise constant reference signals. The proposed triggering scheme computes both the updated control action and the next triggering time based on the relaxed dynamic programming inequality and the idea of reference governor. The resulting self-triggered tracking MPC control law ensures stability, constraint satisfaction, and meets a priori chosen performance requirements without imposing stabilizing terminal conditions. An illustrative example demonstrates the effectiveness of this self-triggered tracking MPC implementation.
Article
Automation & Control Systems
Seyed Shahabaldin Tohidi, Yildiray Yildiz, Ilya Kolmanovsky
Summary: This paper proposes a combined approach of adaptive control allocation and sliding mode control in order to solve the problem of distributing control action among redundant actuators with uncertain dynamics in the presence of actuator saturation. Simulation studies using the Aerodata Model in Research Environment demonstrate the effectiveness of the proposed controller.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Mehdi Hosseinzadeh, Bruno Sinopoli, Ilya Kolmanovsky, Sanjoy Baruah
Summary: This article proposes a traffic control scheme focused on emergency vehicles to alleviate traffic congestion in a network of interconnected signaled lanes/roads. Both centralized and decentralized schemes are considered and extensively simulated to validate their effectiveness. The results show significant reductions in travel times for emergency vehicles without causing congestion in other lanes.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Civil
Mohammad Reza Amini, Qiuhao Hu, Ashley Wiese, Ilya Kolmanovsky, Julia Buckland Seeds, Jing Sun
Summary: We propose an integrated spatio-temporal framework for predicting traction power and speed of connected vehicles. It combines data-driven and model-based strategies to optimize energy efficiency. The framework focuses on urban arterial corridors with signalized intersections and utilizes historical and real-time data from vehicles and infrastructure to predict location-specific traction loads and time-specific speed profiles. A Bayesian network is developed for long-term load prediction based on probabilistic analysis of traffic data, while a shockwave profile model is adopted for short-range speed prediction at intersections using vehicle-to-infrastructure communications. The framework's benefits are demonstrated in energy management of connected hybrid electric vehicles, achieving near-global optimal fuel consumption with <1% deviation from dynamic programming results.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Kaiwen Liu, Nan Li, H. Eric Tseng, Ilya Kolmanovsky, Anouck Girard
Summary: In this paper, the problem of autonomous vehicle control for forced merge scenarios is addressed. A novel game-theoretic controller called the Leader-Follower Game Controller (LFGC) is proposed, which models the interactions between the autonomous ego vehicle and other vehicles with uncertain driving intentions as a partially observable leader-follower game. The LFGC estimates the other vehicles' intentions online, predicts their future trajectories, and plans the ego vehicle's trajectory using Model Predictive Control (MPC) to achieve both probabilistically guaranteed safety and merging objectives. The LFGC demonstrates a high success rate of 97.5% in merging based on simulations and NGSIM data.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Aerospace
Torbjorn Cunis, Ilya Kolmanovsky, Carlos E. S. Cesnik
Summary: In traditional multidisciplinary aircraft design, nonlinear controllability is often ignored until the later stages. This paper introduces a control-aware design optimization framework that integrates nonlinear controllability constraints into the overall design process. By considering optimal control problems, the proposed approach allows control-related constraints to inform the gradient-based design optimization. A case study on a supersonic aircraft demonstrates the effectiveness of this methodology.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Engineering, Aerospace
Kosuke Ikeya, Kaiwen Liu, Anouck Girard, Ilya Kolmanovsky
Summary: This paper presents a learning-based reference governor (LRG) method for spacecraft automated rendezvous, proximity maneuvering, and docking (ARPOD) operations, to enforce safety constraints. The LRG method replaces the spacecraft dynamics model with learning and guarantees constraint satisfaction during and after the learning process. Three case studies are conducted to demonstrate the benefits of the LRG method in ARPOD missions.
JOURNAL OF SPACECRAFT AND ROCKETS
(2023)
Article
Automation & Control Systems
Qiuhao Hu, Mohammad Reza Amini, Ashley Wiese, Ronald Semel, Julia Buckland Seeds, Ilya Kolmanovsky, Jing Sun
Summary: This article applies model predictive control (MPC) to minimize the energy consumption of the thermal management system (TMS) in electric vehicles (EVs) while enforcing power and thermal constraints. The strategy relies on a control-oriented model that captures the dynamics of the powertrain and thermal subsystems, as well as the coupling between them at different timescales. A long prediction horizon is necessary for the slow dynamics of the thermal systems, but uncertainties in speed prediction and preview information significantly impact performance and robustness. The study conducts sensitivity analysis to identify key traffic and speed features that influence EV performance and examines the impact of uncertainties on energy efficiency and constraint enforcement.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Renato Quartullo, Andrea Garulli, Ilya Kolmanovsky
Summary: A periodic model predictive control (MPC) scheme is proposed for tracking halo orbits in the elliptic restricted three-body problem (ER3BP) setting. The MPC design exploits the periodicity of the tracking model and guarantees exponential stability of the linearized closed-loop system. The proposed control scheme is validated on two simulated missions, showcasing its advantages over approximate solutions based on the circular restricted three-body problem (CR3BP).
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Civil
Mushuang Liu, Ilya Kolmanovsky, H. Eric Tseng, Suzhou Huang, Dimitar Filev, Anouck Girard
Summary: Decision-making for autonomous driving faces the challenge of complex interactions among multiple traffic agents and the computation load required for evaluating these interactions. This paper presents two general potential game-based frameworks, namely finite and continuous potential games, for decision-making in autonomous driving. The developed frameworks provide theoretical guarantees for the existence of pure-strategy Nash equilibria and for the convergence of the Nash equilibrium seeking algorithms. The scalability challenge is also addressed, and the performance of the developed algorithms is demonstrated in diverse traffic scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Aerospace
Molong Duan, Carlos E. S. Cesnik, Ilya V. Kolmanovsky, Fabio Vetrano
Summary: This paper presents a method for establishing a low-order model of a flexible aircraft. By combining the dynamics of the elastic body with the numerical linearization of the high-order structure and aerodynamics models, a semi-analytical model is derived. The accuracy of the model is enhanced using static residualization.
JOURNAL OF AIRCRAFT
(2023)
Article
Automation & Control Systems
Aaron I. Rabinowitz, Chon Chia Ang, Yara Hazem Mahmoud, Farhang Motallebi Araghi, Richard T. Meyer, Ilya Kolmanovsky, Zachary D. Asher, Thomas H. Bradley
Summary: This article reviews the state of autonomous eco-driving control research and evaluates different methods through simulations. The results show that dynamic programming methods are most effective in improving energy economy but are computationally expensive, while genetic algorithm methods have the potential to improve energy economy and run-time.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Proceedings Paper
Automation & Control Systems
Mingfei Ye, Ilya Kolmanovsky
Summary: The paper explores shrinking horizon model predictive control as an approximation to optimal finite horizon control. The theoretical results bounding the approximation error, as well as a computational case study and examination of inexactness in solving the optimization problem, are discussed. The properties and benefits of an implementation based on gradient descent method with warm-starting and varying iterations per time step are also examined.
Proceedings Paper
Computer Science, Cybernetics
Mehdi Hosseinzadeh, Bruno Sinopoli, Ilya Kolmanovsky, Sanjoy Baruah
2ND INTERNATIONAL WORKSHOP ON COMPUTATION-AWARE ALGORITHMIC DESIGN FOR CYBER-PHYSICAL SYSTEMS (CAADCPS 2022)
(2022)