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Characteristic model-based control of aerial manipulator for improved interaction stability

Science China(Technological Sciences) 2025年第4期68卷 166-178页

作者： Bingkai XIU Zhan LI Yipeng YANG Huijun GAO Research Institute of Intelligent Control and Systems Harbin Institute of TechnologyHarbin150001China State Key Laboratory of Robotics and Systems(HIT) Harbin Institute of TechnologyHarbin150001China

Maintaining contact stability is crucial when the aerial manipulator interacts with the surrounding environment. In this paper, a novel output feedback framework based on a characteristic model is proposed to improve the contact stability of the aerial manipulator. First, only position measurements of the aerial manipulator are introduced to design the practical finite-time command filter-based force observer. Second, an attitude control architecture including characteristic modeling and controller design is presented. In the modeling part, input-output data is utilized to build the characteristic model with fewer parameters and a simpler structure than the traditional dynamic model. Different from conventional control methods, fewer feedback values,namely only angle information, are required for designing the controller in the controller part. In addition, the convergence of force estimation and the stability of the attitude control system are proved by the Lyapunov analysis. Numerical simulation comparisons are conducted to validate the effectiveness of the attitude controller and force observer. The comparative results demonstrate that the tracking error of x and θ channels decreases at least 10.62% and 10.53% under disturbances and the force estimation precision increases at least 45.19% in the different environmental stiffness. Finally, physical flight experiments are conducted to validate the effectiveness of the proposed framework by a self-built aerial manipulator platform.

关键词： aerial manipulator interaction stability contact force observer characteristic model

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Distributionally Robust Model Predictive control: Closed-Loop Guarantees and Scalable Algorithms

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IEEE Transactions on Automatic control 2025年第5期70卷 2963-2978页

作者： McAllister, Robert D. Esfahani, Peyman Mohajerin Delft University of Technology Delft Center for Systems and Control Delft2628 Netherlands

We establish a collection of closed-loop guarantees and propose a scalable optimization algorithm for distributionally robust model predictive control (DRMPC) applied to linear systems, convex constraints, and quadratic costs. Via standard assumptions for the terminal cost and constraint, we establish distributionally robust long-term and stagewise performance guarantees for the closed-loop system. We further demonstrate that a common choice of the terminal cost, i.e., via the discrete-algebraic Riccati equation, renders the origin input-to-state stable for the closed-loop system. This choice also ensures that the exact long-term performance of the closed-loop system is independent of the choice of ambiguity set for the DRMPC formulation. Thus, we establish conditions under which DRMPC does not provide a long-term performance benefit relative to stochastic MPC. To solve the DRMPC optimization problem, we propose a Newton-type algorithm that empirically achieves superlinear convergence and guarantees the feasibility of each iterate. We demonstrate the implications of the closed-loop guarantees and the scalability of the proposed algorithm via two examples. To facilitate the reproducibility of the results, we also provide open-source code to implement the proposed algorithm and generate the figures. © 1963-2012 IEEE.

关键词： Riccati equations

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High-Order Fully Actuated System Approach-Based Attitude Stabilization for Underactuated Rigid and Flexible Spacecraft

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15094-15105页

作者： Jia, Shixiang Qiu, Jianbin Wang, Tong Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin150001 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150080 China

This paper addresses the challenge of attitude stabilization for a class of underactuated rigid and flexible spacecrafts by utilizing only two control inputs. The attitude stabilization problem of underactuated spacecraft poses substantial challenges to the High-Order Fully Actuated (HOFA) system approach, due to the fact that it heavily depends on the full actuation characteristics of the system. To circumvent the aforementioned limitation, we first derive a HOFA system for underactuated rigid spacecraft using homogeneity theory and averaged system approach. Subsequently, we design a controller based on the HOFA system approach, which yields a linear closed-loop system. This methodology is then extended to address the simplified attitude stabilization problem of underactuated flexible spacecraft. By utilizing the HOFA system approach in tandem with an observer for estimating modal variables, we propose a control strategy that not only stabilizes the attitude but also actively suppresses elastic vibration. The performance of the proposed control schemes are demonstrated through simulation studies. © 2004-2012 IEEE.

关键词： Satellites

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On-Policy and Off-Policy Value Iteration Algorithms for Stochastic Zero-Sum Dynamic Games

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Journal of systems Science & Complexity 2025年第1期38卷 421-435页

作者： GUO Liangyuan WANG Bing-Chang ZHANG Ji-Feng School of Control Science and Engineering Shandong UniversityJinan 250063China School of Automation and Electrical Engineering Zhongyuan University of TechnologyZhengzhou 450007China Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.

关键词： Approximate dynamic programming on-policy off-policy stochastic zero-sum games valueiteration

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A Divide-and-conquer Approach for Sparse Recovery in High Dimensions

A Divide-and-conquer Approach for Sparse Recovery in High Di...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Bevelander, Aron Batselier, Kim Myers, Nitin Jonathan Delft Center for Systems and Control Delft University of Technology Netherlands

ISBN: (纸本)9798350368741

Block compressed sensing (BCS) alleviates the high storage and memory complexity with standard CS by dividing the sparse recovery problem into sub-problems. This paper presents a Welch bound-based guarantee on the reconstruction error with BCS, revealing that sparse recovery deteriorates with more partitions. To address this performance loss, we propose a data-driven BCS technique that leverages correlation across signal partitions. Our method surpasses classical BCS in moderate SNR regimes, with a modest increase in storage and computational complexities. © 2025 IEEE.

关键词： Block compressed sensing computational complexity memory limitation

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Guided Swarm Self-Clustering in Safe Area

Guided Swarm Self-Clustering in Safe Area

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Jain, Sweksha Vachhani, Leena Indian Institute of Technology Centre for Systems and Control Bombay India

ISBN: (纸本)9798331531614

In high-stress situations, guiding a non-communicating, location-unaware swarm to the safe area is challenging, especially as they self-organize into clusters with nearby agents. This paper presents a novel decentralized non-interacting swarm algorithm to form guided swarm clusters autonomously in an area without nearby danger, termed as "safe area". The proposed strategy guides the swarm of robots towards safe area to form self-clusters in a bounded environment. It is achieved by fixing the locations of static obstacles which prevents cluster formation in the danger area. We evaluate the performance based on cluster formation in the safe area. The Monte-Carlo simulations are performed with varying percentage occupancy of obstacles in danger area, where we achieved percentage of convergence (PoC) in safe area over 85% (on an average). The proposed algorithm potentially find its application in a crowded environment, while evacuating to a safer area during emergency. © 2025 IEEE.

关键词： Intelligent systems

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On Data-Driven Stochastic Output-Feedback Predictive control

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IEEE Transactions on Automatic control 2025年第5期70卷 2948-2962页

作者： Pan, Guanru Ou, Ruchuan Faulwasser, Timm TU Dortmund University Institute for Energy Systems Energy Efficiency and Energy Economics Dortmund Germany Hamburg University of Technology Institute of Control Systems Hamburg21073 Germany

The fundamental lemma by J. C. Willems and coauthors enables the representation of all input–output trajectories of a linear time-invariant (LTI) system by measured input–output data. This result has proven to be pivotal for data-driven control. Building on a stochastic variant of the fundamental lemma, this article presents a data-driven output-feedback predictive control scheme for stochastic LTI systems. The considered LTI systems are subject to non-Gaussian disturbances about which only information about their first two moments is known. Leveraging polynomial chaos expansions, the proposed scheme is centered around a data-driven stochastic optimal control problem (OCP). Through tailored online design of initial conditions, we provide sufficient conditions for the recursive feasibility of the proposed output-feedback scheme based on a data-driven design of the terminal ingredients of the OCP. Furthermore, we provide a robustness analysis of the closed-loop performance. A numerical example illustrates the efficacy of the proposed scheme. © 1963-2012 IEEE.

关键词： Predictive control systems

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Fast Iterative Region Inflation for Computing Large 2-D/3-D Convex Regions of Obstacle-Free Space

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IEEE Transactions on Robotics 2025年 41卷 3223-3243页

作者： Wang, Qianhao Wang, Zhepei Wang, Mingyang Ji, Jialin Han, Zhichao Wu, Tianyue Jin, Rui Gao, Yuman Xu, Chao Gao, Fei Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China Zhejiang University Huzhou Institute Huzhou313000 China

Convex polytopes have compact representations and exhibit convexity, which makes them suitable for abstracting obstacle-free spaces from various environments. Existing generation methods struggle with balancing high-quality output and efficiency. Moreover, another crucial requirement for convex polytopes to accurately contain certain seed point sets, such as a robot or a front-end path, is proposed in various tasks, which we refer to as manageability. In this paper, we propose Fast Iterative Regional Inflation (FIRI) to generate high-quality convex polytope while ensuring efficiency and manageability simultaneously. FIRI consists of two iteratively executed submodules: Restrictive Inflation (RsI) and Maximum Volume Inscribed Ellipsoid (MVIE) computation. By explicitly incorporating constraints that include the seed point set, RsI guarantees manageability. Meanwhile, iterative MVIE optimization ensures high-quality result through monotonic volume bound improvement. In terms of efficiency, we design methods tailored to the low-dimensional and multi-constrained nature of both modules, resulting in orders of magnitude improvement compared to generic solvers. Notably, in 2-D MVIE, we present the first linear-complexity analytical algorithm for maximum area inscribed ellipse, further enhancing the performance in 2-D cases. Extensive benchmarks conducted against state-of-the-art methods validate the superior performance of FIRI in terms of quality, manageability, and efficiency. Furthermore, various real-world applications showcase the generality and practicality of FIRI. The high-performance code of FIRI will be open-sourced. © 2004-2012 IEEE.

关键词： Efficiency

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Model-Free Current Predictive control for PMSMs With Ultra-Local Model Employing Fixed-Time Observer and Extremum-Seeking Method

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IEEE Transactions on Power Electronics 2025年第8期40卷 10682-10693页

作者： Lin, Xinpo Liu, Jianxing Liu, Zhuang Gao, Yabin Peretti, Luca Wu, Ligang Harbin Institute of Technology Department of Control Science and Engineering Weihai264209 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China KTH Royal Institute of Technology Division of Electric Power and Energy Systems Stockholm10044 Sweden

Conventional model predictive current control of permanent magnet synchronous machines (PMSMs) relies heavily on a precise mathematical model, which may be challenging to obtain in certain cases. To address this issue, this paper proposes a model-free predictive current controller for PMSMs. Specifically, the dynamic model of the motor currents is represented using two ultra-local models, which express the derivatives of a controlled output as the sum of an amplified control input and an unknown offset term. All system parameters, nonlinear terms, and unmodeled dynamics are encapsulated into two offset terms. Online estimation of these two offset terms is performed using a second-order fixed-time convergence observer without requiring exact knowledge of the system parameters in advance. In contrast to both the linear extended state observer and the super-twisting observer, the fixed-time observer enhances convergence speed while concurrently sustaining minimal chatting. To get rid of the need for model rated parameters, an extremum-seeking approach is utilized to tune the control gains in the ultra-local model, where the amplitude of the disturbance item in extremum-seeking approach is adaptively attenuated, resulting in effective reduction of the fluctuations of both the control gains and PMSM's currents in steady state. Subsequently, a predictive controller is designed using this ultra-local model. Finally, the effectiveness and advantages of the proposed control scheme are confirmed through experimental results. © 1986-2012 IEEE.

关键词： Permanent magnets

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control valve simulation method integrable into the global gradient algorithm

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ISH Journal of Hydraulic Engineering 2025年第1期31卷 1-7页

作者： Sivakumar, P. Gorev, N.B. Gorev, V.N. Kodzhespirova, I.F. Shedlovsky, I.A. Itanagar India Department for Functional Elements of Control Systems Institute of Technical Mechanics Dnipro Ukraine Department of Physics Dnipro University of Technology Dnipro Ukraine Department of Automation and Computer Systems Dnipro University of Technology Dnipro Ukraine

This paper presents a refinement of a method that simulates flow- and pressure-regulating valves by replacing them with pipes and adjusting the resistances (diameters) of those pipes to meet the valve settings. The method, referred to as the replacing pipe method (RPM), is readily integrable into the global gradient algorithm, which is the heart of the commonly used EPANET 2 water distribution system modeling software. The RPM proved to be more robust, yet slower than the EPANET 2 valve handling heuristics. In this work, the RPM was modified to increase its computational speed. The modification involved the RPM check valve handling algorithm and condition for updating the diameters of the valve-replacing pipes. The modified RPM was tested as part of a hybrid simulator, which switches from the EPANET 2 valve handling heuristics to the RPM when the former fails. The test networks included a large network with thousands of nodes, pipes, and valves, and a case of an ill-posed problem. As the testing showed, the modified RPM offers a significant reduction in the number of iterations compared to its previous version. © 2024 Indian Society for Hydraulics.

关键词： Safety valves

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