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3rd Conference on Fully Actuated System Theory and Applications (FASTA)

作者： Yan, Huixing Lu, Hongqian Wang, Hanyu Zhang, Zhen Huang, Xianlin Harbin Inst Technol Control Theory & Guidance Ctr Harbin 150001 Peoples R China

ISBN: (纸本)9798350373707;9798350373691

To address the underactuation issue induced by passive dampers in a suspension Gravity offload(SGO) system, this paper introduces the utilization of active control using Pneumatic Artificial Muscles(PAM) to transform it into a fully actuated physical system. However, due to the inherent non-linear characteristics such as flexibility and hysteresis in PAM, achieving precise force control poses challenges. Therefore, this paper proposes a Neural Network-based nonlinear model predictive control (NMPC) approach. We apply the proposed approach to the constant force control of the SGO system based on PAM. Simulation results demonstrate a marked improvement in control accuracy when compared to the feedforward PID control method.

关键词： Pneumatic Artificial Muscles nonlinear model predictive control suspension Gravity offload

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Trajectory Tracking control of AUV Formation Systems based on Adaptive nonlinear model predictive control 36

Trajectory Tracking Control of AUV Formation Systems based o...

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36th Chinese control and Decision Conference (CCDC)

作者： Wang, Zhaoyang Diao, Weiqing Xu, Bo Li, Weihao Zhong, Rongxing Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China China State Shipbldg Corp Lab Sci & Technol Marine Nav & Control Tianjin 300000 Peoples R China Univ Elect Sci & Technol China Sch Aeronaut & Astronaut Chengdu 611731 Peoples R China

ISBN: (纸本)9798350387780;9798350387797

The objective of this work is to examine the difficulty of accomplishing multi-AUV trajectory tracking in underwater environments, which is essential for several underwater jobs like patrol, surveillance, and environment identification. The paper proposes a distributed nonlinear model predictive formation control based on adaptive prediction interval, which enables the achievement of AUV formation tracking and reduction in the computational burden associated with formation tasks. Firstly, a distributed auxiliary control law is proposed to ensure terminal convergence of the prediction interval of the AUV formation system. Second, by creating various constraint terms and adaptive prediction interval in the distributed nonlinear model predictive control (NMPC), the suggested technique tackles the problem of computationally cumbersome and input saturation. Then, by addressing a local MPC optimization problem that considers the state information of the AUV and its neighbors, the control input for every AUV is ascertained. Finally, the coordination and stability of the suggested predictive control system are shown by the presentation of numerical simulation results.

关键词： AUV Formation trajectory tracking Adaptive prediction interval nonlinear model predictive control

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nonlinear model predictive control for improving range-based relative localization by maximizing observability

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INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES 2022年 14卷

作者： Li, Shushuai De Wagter, Christophe de Croon, Guido C. H. E. TUDelft MAVLab Delft Netherlands

Wireless ranging measurements have been proposed for enabling multiple Micro Air Vehicles (MAVs) to localize with respect to each other. However, the high-dimensional relative states are weakly observable due to the scalar distance measurement. Hence, the MAVs have degraded relative localization and control performance under unobservable conditions as can be deduced by the Lie derivatives. This paper presents a nonlinear model predictive control (NMPC) by maximizing the determinant of the observability matrix to generate optimal control inputs, which also satisfy constraints including multi-robot tasks, input limitation, and state bounds. Simulation results validate the localization and control efficacy of the proposed MPC method for range-based multi-MAV systems with weak observability, which has faster convergence time and more accurate localization compared to previously proposed random motions. A real-world experiment on two Crazyflies indicates the optimal states and control behaviours generated by the proposed NMPC.

关键词： Optimal control micro air vehicle swarming ultra-wideband nonlinear model predictive control

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Towards Energy Saving: nonlinear model predictive control for Quadrotor UAV with Trajectory Optimization 14

Towards Energy Saving: Nonlinear Model Predictive Control fo...

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14th International Conference on control (control)

作者： Mubdir, Bilal Prempain, Emmanuel Sulaimani Polytech Univ Sulaumaniyah Iraq Univ Leicester Sch Engn Leicester England

ISBN: (纸本)9798350374278;9798350374261

In this paper, a nonlinear model predictive control is proposed to make a Quadrotor UAV track an energy-efficient trajectory generated off-line. The dynamically constrained, open-loop control problem is solved once and provides an energy-efficient trajectory that will have to be tracked by the quadrotor. The preliminary results demonstrate a noteworthy reduction in energy consumption when compared with the use of a standard MPC feedback controller. A 37% of energy saving was achieved in some cases

关键词： nonlinear model predictive control Quadrotor Energy Efficient control

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Path Following of Cable Suspended Parallel Robots Through nonlinear model predictive control 9th

Path Following of Cable Suspended Parallel Robots Through No...

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9th European Conference on Mechanism Science (EuCoMeS)

作者： Bettega, Jason Richiedei, Dario Tamellin, Iacopo Trevisani, Alberto Univ Padua Dept Management & Engn DTG Str San Nicola 3 I-36100 Vicenza Italy

ISBN: (纸本)9783031672972;9783031672958;9783031672941

Cable-driven parallel robots (CDPRs) are spreading very fast due to their large workspaces and their high payload-to-weight ratio, therefore representing an interesting solution for the next generation of industrial automation. Among the different topologies of CDPRs, the suspended configuration covers a huge interest because it simplifies the robot installation. At the same time, Cable Suspended Parallel Robots (CSPRs) represent a highly challenging configuration from the control design point of view because they lack positive controllability. This paper shows how nonlinear model predictive control (NMPC) algorithms represent an effective control method to perform path following tasks in the presence of CSPRs;in particular, a two-stage controller is proposed. Firstly, a NMPC algorithm is designed by considering only the dynamical subsystem made of the end-effector, achieving the optimal cable tensions for the execution of the desired path;this procedure easily includes constraints on the feasible tensions. Secondly, the related motor torques are achieved through inversion of the dynamic model of the electric motors. To assess the proposed controller, a 3-dof cable suspended spatial robot, moved by four cables, is considered. Numerical results are reported, showing low contour errors in the execution of the path following tasks and therefore confirming the effectiveness of the proposed method.

关键词： nonlinear model predictive control Path following Cable-driven Parallel Robots Cable Suspended Parallel Robots Optimal control

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Primary-Side nonlinear model predictive control for Dynamic Wireless Power Transfer System in Electric Vehicles 32

Primary-Side Nonlinear Model Predictive Control for Dynamic ...

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32nd International Conference on Electrical Engineering (ICEE)

作者： Shahriari, Kioumars Sadeghian, Salar Fooman, Sahand Fardadidokht Abrishamifar, Adib Iran Univ Sci & Technol Sch Adv Technol Tehran Iran Iran Univ Sci & Technol Sch Elect Engn Tehran Iran

ISBN: (纸本)9798350376357;9798350376340

The Dynamic Wireless Charging (DWC) system offer a favorable solution to Electric Vehicle (EV) charging limitations, allowing for on-the-go charging. However, such systems usually require complex control strategies that involve communication between the primary and secondary systems. These requirements can result in higher costs, increased system complexity, and energy losses. In this paper, we present a new Primary-Side nonlinear model predictive control (NMPC) method that operates based on the identification of load characteristics and which has been designed specifically for use in Wireless Power Transfer (WPT) system for EVs to counteract variations in mutual inductance caused by coil movement. The NMPC is favored over conventional control techniques like the traditional Proportional Integral Derivative (PID) method thanks to its ability to anticipate future events and adjust control inputs proactively for robust and dynamic system response. The NMPC exhibits superior performance by yielding faster control response, decreased overshoot, and enhanced stability. Systematic simulations validate the proposed solution's efficacy.

关键词： Dynamic Wireless Charging Wireless Power Transfer nonlinear model predictive control Variations in Mutual inductance Electric Vehicle Charger Primary-Side Wireless control

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Robust nonlinear model predictive control for Ship Dynamic Positioning Using Laguerre Function

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IEEE ACCESS 2022年 10卷 127563-127574页

作者： Hou, Xiuhui Deng, Fang Yang, Hualin Yu, Dunjing Zhang, Hanlin Li, Boyang Qingdao Univ Sci & Technol Coll Mech & Elect Engn Qingdao 266061 Peoples R China

This paper is devoted to the issue of computationally efficient and robust nonlinear model predictive control (NMPC) for ship dynamic positioning (DP) systems subjected to input constraints and unknown environmental disturbances. The Laguerre functions, typically applied to the linear systems, are introduced to the constrained NMPC design of the nonlinear DP system to reduce the computational burden. The unscented Kalman filter is adopted to estimate the unknown disturbances and states;thus, the disturbance estimates are utilized as the cancellation signal to achieve robust offset-free control. Simulations of the proposed Laguerre function-based NMPC scheme are implemented and compared with the performance of typical Laguerre function-based linear model predictive control (LMPC) for the DP system. Simulation results well demonstrate the effectiveness, robustness and superiority of the proposed controller.

关键词： Laguerre functions nonlinear model predictive control input constraints ship dynamic positioning

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Aggressive Trajectory Tracking for Nano Quadrotors Using Embedded nonlinear model predictive control 1

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18th International Conference on Intelligent Autonomous Systems (IAS)

作者： Kazim, Muhammad Sim, Hyunjae Shin, Gihun Hwang, Hwancheol Kim, Kwang-Ki K. Inha Univ Dept Elect & Comp Engn Incheon South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

This paper presents an aggressive trajectory tracking method for a small lightweight nano-quadrotor using nonlinear model predictive control (NMPC) based on acados. controlling a nano quadrotor for accurate trajectory tracking at high speed in dynamic environments is challenging due to complex aerodynamic forces that introduce significant disturbances and large positional tracking errors. These aerodynamic effects are difficult to be identified and require feedback control that compensates for them in real time. NMPC allows the nano-quadrotor to control its motion in real time based on onboard sensor measurements, making it well-suited for tasks such as aggressive maneuvers and navigation in complex and dynamic environments. The software package acadosenables the implementation of the NMPC algorithm on embedded systems, which is particularly important for nano-quadrotor due to its limited computational resources. Our autonomous navigation system is developed based on an AI-deck that is a GAP8-based parallel ultra-low power computing platform with onboard sensors of a multi-ranger deck and a flow deck. The proposed method of NMPC-based trajectory tracking control is tested in simulation and the results demonstrate its effectiveness in trajectory tracking while considering the dynamic environments. It is also tested on a real nano quadrotor hardware, 27-g Crazyflie 2.1, with a customized MCU running embedded NMPC, in which accurate trajectory tracking results are achieved in dynamic real-world environments.

关键词： Optimal tracking control nonlinear model predictive control acados Crazyflie2.1 AI-deck

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Simultaneous design and nonlinear model predictive control under uncertainty: A back-off approach

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JOURNAL OF PROCESS control 2022年 110卷 45-58页

作者： Palma-Flores, Oscar Ricardez-Sandoval, Luis A. Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada

We propose the use of an iterative back-off approach for the integration of design and NMPC-based control under uncertainty. This methodology is based on the use of power series expansions (PSE) to feature the simplification of the resulting bilevel optimization formulation when nonlinear model predictive control (NMPC) is incorporated as the control scheme. To illustrate the benefits of the proposed approach, the optimal design and control of a wastewater treatment plant is formulated under different scenarios. The results show that the proposed methodology leads to improvements in control performance compared with the use of decentralized PI-based controllers and a linear MPC strategy to maintain the dynamic operation of the system in the presence of disturbances and parameter uncertainty. Thus, the present approach not only reduces the computational effort by solving single-level NMPC-based optimization problems but it also returns economically attractive and dynamically operable designs while using NMPC. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Back-off method Integration of design and control Power series expansion nonlinear model predictive control

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Approximate two-loop robust nonlinear model predictive control with real-time execution and closed-loop guarantee

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INTERNATIONAL JOURNAL OF ROBUST AND nonlinear control 2022年第10期32卷 5967-5982页

作者： Farajzadeh Devin, Mohammad Ghassem Hosseini Sani, Seyed Kamal Ferdowsi Univ Mashhad Dept Elect Engn Fac Engn Mashhad Razavi Khorasan Iran

In this article, a robust nonlinear model predictive control (NMPC) scheme with two control loops is considered and its real-time execution is guaranteed for a predefined sampling time. Robustness of the NMPC scheme against bounded input uncertainty is achieved by assuming Lipschitz continuity of the inner-loop dynamic function. The NMPC control law is approximated using piecewise affine linear functions over hyper-rectangle regions generated by k-d tree partitioning algorithm. Additionally, error bound on the approximation of the optimal solution function is obtained by assuming bounds on the subgradient of the optimal solution function. Consequently, the robust stability and recursive feasibility of the closed-loop system for the proposed approximate NMPC framework are proven, and at the same time, real-time execution of the proposed scheme for a predefined sampling time is guaranteed. Simulation results, on a nonlinear benchmark problem, are used to better illustrate the proposed approach and to compare it with some other methods.

关键词： nonlinear model predictive control real-time control robust control

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