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IEEE International Conference on Industrial Technology (ICET)

作者： Wang, Hengyi Liu, Steven Univ Kaiserslautern Inst Control Syst D-67663 Kaiserslautern Germany

ISBN: (纸本)9781467380751

This paper presents an optimal control strategy for load current compensation under different PCC voltages, including the ideal, distorted and unbalanced situations. This optimal strategy compromises the conflicting targets in the source currents, leading to a non-convex problem with convex quadratic cost function and non-convex quadratic constraints. To solve this non-convex quadratic constraints quadratic programming(QCQP) problem, by writing the constraints as a difference of two convex quadratic functions(DC), this paper introduces the sequential convex programming(SCP) algorithm based on the iterative method of the DC programming, in which the non-convex parts in the constraints are sequentially linearized. The fast convergence in a few iterations is illustrated to demonstrate the performance of the algorithm. The simulation in MATLAB of a three-phase system feeding a nonlinear load has shown the effectiveness and feasibility of the proposed compensation strategy.

关键词： Active power filter(APF) non-convex QCQP DC programming iteration sequential convex programming power conditioning

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A convex Formulation for Collision Avoidance Maneuver Strategies During Low-Thrust Phases

A Convex Formulation for Collision Avoidance Maneuver Strate...

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AIAA SciTech Forum

作者： Pavanello, Zeno Pirovano, Laura Armellin, Roberto De Vittori, Andrea di Lizia, Pierluigi Univ Auckland Te Punaha Atea Space Inst Dept Mech Engn 20 Symonds St Auckland 1010 New Zealand Politecn Milan Dept Aerosp Sci & Technol DAER Piazza Leonardo Da Vinci 32 I-20133 Milan Italy

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Conjunctions between spacecraft are increasingly common across orbital regimes, demanding reliable and efficient collision avoidance (CA) strategies. The typical solution to the CA problem is to compute a maneuver that reduces the collision risk while minimizing fuel expenditure. If the spacecraft is in a continuously propelled phase, this approach must be modified since the thrust profile is determined a priori, aiming to reach a final orbit. This work proposes using convex optimization to solve the fuel-optimal short-term encounter CA problem in such conditions. The optimization problem is two-fold: (i) the collision must be avoided, i.e., the collision risk must be reduced below a certain threshold;(ii) after the conjunction, the spacecraft must be rerouted into the correct trajectory to reach the final state that is the end-point of the original thrust trajectory. Through the casting of the problem as a sequential convex program, the original nonlinear optimal control problem is solved iteratively, recovering an optimal solution. Within the second-order cone program framework, three methods are proposed to address the problem: (i) determining the optimal switch-off time to evade collision while minimizing deviation from the nominal trajectory;(ii) computing a new thrust profile, deviating as little as possible from the original one;(iii) combining the previous methods, the thrust is switched off prior to conjunction and after the encounter a new thrust profile is computed. The three strategies are tested on practical operational scenarios, using the nominal thrust profile from a low-thrust Geostationary Transfer Orbit and conjunction details from a Conjunction Data Message.

关键词： Collision Avoidance Thrust Optimal Control Problem Geostationary Transfer Orbit sequential convex programming convex Optimization Computing Earth Centered Inertial Satellites Attitude Control System

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Maximum Likelihood Network Localization Using Range Estimation and GPS Measurements 9

Maximum Likelihood Network Localization Using Range Estimati...

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9th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yu, Hongwei Jiang, Yi Fudan Univ Key Lab Informat Sci Elect Waves MoE Dept Commun Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781538620625

Localization of wireless networks has remained an active research topic for more than a decade, as it finds more and more applications in numerous scenarios, including environment surveillance, asset tracking, and healthcare monitoring, etc. In this paper, we consider the maximum likelihood localization of a network where some of the nodes are GPS-capable while the others attempt to achieve self localization by estimating the ranges between itself to the neighboring nodes. Assuming no clock synchronization between the distributed nodes, we introduce a two-way network signaling protocol, based on which pairs of nodes can not only estimate the line-of-sight (LOS) propagation distance between themselves, but also resolve their clock offsets. By modeling both range estimation errors and GPS measurement errors as Gaussian, we derive the maximum likelihood (ML) localization as well as the ML estimation of the clock offsets between the nodes. It turns out that the two ML estimations can be decoupled. While the ML estimation of the clock offset can be obtained using a simple least square (LS) method, we propose a sequential convex programming (SCP) algorithm to obtain the ML estimation of the locations of all the nodes. The Cramer-Rao bounds (CRB) are also derived as the performance benchmark. Simulation results demonstrate that the proposed SCP algorithm can significantly outperform the existing algorithms and can even achieve the CRB.

关键词： Network Localization Maximum Likelihood Estimation sequential convex programming Cramer-Rao Bounds

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Real-Time Optimisation-Based Path Planning for Visually Impaired People in Dynamic Environments

Real-Time Optimisation-Based Path Planning for Visually Impa...

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IEEE/CVF International Conference on Computer Vision (ICCV)

作者： Surougi, Hadeel R. McCann, Julie A. Imperial Coll London London SW7 2AZ England

ISBN: (纸本)9798350307443

Most existing outdoor assistive mobility solutions notify Visually Impaired People (VIP) about potential collisions but fail to provide Optimal Local Collision-Free Path Planning (OLCFPP) to enable the VIP to get out of the way effectively. In this paper, we propose MinD, the first VIP OLCFPP scheme that notifies the VIP of the shortest path required to avoid Critical Moving Objects (CMOs), like cars, motorcycles, etc. This simultaneously accounts for the VIP's mobility constraints, the different CMO types and movement patterns, and predicted collision times, conducting a safety prediction trajectory analysis of the optimal path for the VIP to move in. We implement a real-world prototype to conduct extensive outdoor experiments that record the aforementioned parameters, and this populates our simulations for evaluation against the state-of-the-art. Experimental results demonstrate that MinD outperforms the Artificial Potential Field (APF) approach in effectively planning a short collision-free route, requiring only 1.69m of movement on average, shorter than APF by 90.23%, with a 0% collision rate;adapting to the VIP's mobility limitations and provides a high safe time separation (> 5.35s on average compared to APF). MinD also shows near real-time performance, with decisions taking only 0.04s processing time on a standard off-the-shelf laptop.

关键词： Local path planning Moving objects avoidance sequential convex programming

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UAV Altitude Optimization for Efficient Energy Harvesting in IoT Networks 27

UAV Altitude Optimization for Efficient Energy Harvesting in...

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28th National Conference on Communications (NCC)

作者： Singh, Aditya Redhu, Surender Hegde, Rajesh M. Indian Inst Technol Kanpur Kanpur Uttar Pradesh India Univ Agder Kristiansand Norway

ISBN: (纸本)9781665451369

Energy harvesting plays a crucial role in improving the operational lifetime of an IoT network. Moreover, the source and receiver separation dominates the amount of energy harvested in rechargeable IoT networks. In recent, Unmanned Aerial Vehicles (UAVs) have been utilized as RF energy transmitters for energy harvesting IoT networks. In this work, a method is proposed for optimizing the altitude of UAVs for energy-efficient charging of the IoT nodes. The proposed method maximizes the energy usage efficiency of the UAV over the IoT network subject to altitude and energy harvesting constraints. The proposed maximization problem is first transformed into an equivalent convex optimization problem using the First-Order Taylor Series Approximation. A heuristic algorithm based on the sequential convex programming approach is employed to obtain the optimal UAV altitude above the IoT network. The accuracy of the obtained results is evaluated analytically by computing the global optimum of the optimization problem via monotonic transformations. The results motivate the usage of UAV-aided energy harvesting in self-sustaining IoT networks.

关键词： Energy Harvesting Energy usage efficiency sequential convex programming UAVs Wireless Power Transfer

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JOINT NODE AND RESOURCE SCHEDULING STRATEGY FOR THE DISTRIBUTED MIMO RADAR NETWORK TARGET TRACKING VIA convex programming

JOINT NODE AND RESOURCE SCHEDULING STRATEGY FOR THE DISTRIBU...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Su, Yang He, Zishu Cheng, Ting Wang, Jiaheng Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Sichuan Peoples R China

ISBN: (数字)9781665427920

ISBN: (纸本)9781665427920

In this paper, for the application of multi-target tracking (MTT), a joint node and resource scheduling (JNRS) strategy based on convex programming is proposed for the distributed multiple-input multiple-output (MIMO) radar network. To be more precise, the JNRS strategy is first formulated as a mathematic optimization problem, which is NP-hard. Then, an iterative and efficient solution technique incorporating the sequential convex programming (SCP) and the semi-definite programming (SDP) is proposed to tackle the NP-hard problem. Finally, numerical simulation results are provided to verify the effectiveness of the proposed JNRS strategy. Furthermore, the proposed JNRS strategy can achieve better MTT performance than other existing benchmark strategies.

关键词： Transmitter and receiver selection dwell time allocation power and bandwidth allocation sequential convex programming semi-definite programming

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Successive convexification for Tethered Debris Deorbiting

Successive Convexification for Tethered Debris Deorbiting

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AIAA SciTech Forum

作者： Field, Liam Hecht, Grant R. Botta, Eleonora M. Univ Buffalo Dept Mech & Aerosp Engn 211 Bell Hall Buffalo NY 14260 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Tether-based debris removal methods present a promising option for the mitigation of large space debris in the near Earth orbital regime. A necessary component of these methods is the deorbiting phase, where the debris is removed from its initial orbit by the action of an active spacecraft. However, further development of onboard guidance and control for tethered satellite system (TSS) is required. For this purpose, a planar model of the system is constructed which includes the chaser and target as point masses connected by a flexible tether. Then, a minimum-time optimal control problem for this model is developed and discretized to fit the requirements of a sequential convex programming algorithm - specifically successive convexification (SCvx). An additional problem, in which the minimum-time cost is augmented with a term that penalizes the libration rate, is introduced to reduce the oscillatory motion present in the libration angle and tether length. The resulting augmented problem converged in less iterations and with less oscillatory libration motion compared to the original problem. The time of flight for the augmented problem solution amounted to only a few seconds more than the original problem, indicating that the SCvx algorithm can be used effectively for the tethered debris deorbiting problem.

关键词： Optimal Control Problem Active Debris Removal sequential convex programming Tethered Satellite System Earth Periapsis Adaptive Mesh Refinement State Dependent Riccati Equation Nonlinear Dynamics Hohmann Transfer

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Cooperative Guidance Law Based on Cover Penetration in Two-on-two Engagement 38

Cooperative Guidance Law Based on Cover Penetration in Two-o...

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Huang, Jikai Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Beihang University School of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350303636

Aiming at the two-on-two interception engagement scenario, a cooperative penetration guidance method based on cover strategy is proposed. This method is used to head-on intercept situations where the speed and maneuverability of the opposing sides are close. A team comprised of defender and penetration missile lure the two interceptors and damage them. Firstly, the application scenarios and assumptions of the strategy are introduced, and the kinematic equation are given to describe the penetration process. The optimal control problem is established and solved using sequential convex optimization method. In addition, a continuously optimal guidance law based on receding horizon policy is proposed to deal with the uncertainty and observation error of enemy. The effectiveness of the method are verified by numerical simulation. © 2023 IEEE.

关键词： cooperative guidance cooperative penetration hypersonic vehicle optimal guidance receding horizon sequential convex programming

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Optimization of collision-free trajectories for advanced air mobility under risk of a non-cooperative intruder 14

Optimization of collision-free trajectories for advanced air...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Choi, Uihwan Lee, Soojeon Electronics and Telecommunications Research Institute Mobility Infra Research Section Air Mobility Research Division Digital Convergence Research Laboratory Daejeon Korea Republic of

ISBN: (纸本)9798350313277

Advanced air mobility (AAM) is anticipated to revolutionize transportation and mobility by fully exploiting the three-dimensional airspace of urban and regional areas. One of the main challenges for ensuring AAM safety is to manage a non-cooperative aerial intruder such as illegal drones or a group of birds. This paper proposes an iterative convex optimization framework for trajectory planning of multiple eVTOLs to avoid collision with the aerial intruder. Several avoidance strategies are discussed, and simulation results show the validity of the avoidance capability of the proposed algorithm. © 2023 IEEE.

关键词： advanced air mobility collision avoidance non-cooperative intruder sequential convex programming trajectory optimization

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Whole body motion generation with centroidal dynamics of legged robots using sequential bounds tightening of McCormick envelopes

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ROBOTICS AND AUTONOMOUS SYSTEMS 2023年 164卷

作者： Rojas-Rodriguez, Jose C. Aguilar-Bustos, Ana Y. Bugarin, Eusebio Tecnol Nacl Mexico IT Ensenada Blvd Tecnol 150 Exejido Chapultepec Ensenada 22780 BC Mexico

In this paper we introduce a sequential convex programming (SCP) algorithm for the motion generation with the centroidal dynamics of legged robots using a sequential bounds tightening of McCormick envelopes strategy to cope with the nonconvexity of the problem (related to bilinear terms). Therefore, the proposed SCP algorithm is initialized with relaxed McCormick envelopes and then their bounds are sequentially tightened around the current estimate of the solution enforcing this way convergence to a feasible point. The SCP algorithm solves a quadratic program at each iteration by an interior point method. Additionally, the proposed SCP algorithm is alternated with an inverse kinematics algorithm to achieve the whole body motion generation. Finally, extensive numerical experiments show the effectiveness of the proposed algorithm in generating highly agile motions such as trotting, bounding, stotting and running for humanoid and quadruped robots.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Centroidal dynamics Legged robots sequential convex programming McCormick envelopes Bounds tightening Quadratic programming

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