A robust high-precision velocity-regulation controller is researched for gimbal servo systems (GSSs) in this paper, which aims to mitigate the impact of multiple adverse factors, including both the internal time-delay...
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To enhance the estimation accuracy and dynamic performance of sensorless surface-mounted permanent magnet synchronous motor (SPMSM) drives, a sensorless control scheme based on generalized super-twisting observer (GST...
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In view of the problems of high energy consumption, long inventory time and low production efficiency in the production process of traditional aluminum extrusion machine, this paper establishes an efficient two-stage ...
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As a kind of heavy cargo lifting equipment,it is very important to improve transportation efficiency,save energy and strictly ensure safety for overhead ***,many traditional control strategies can not meet these needs...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
As a kind of heavy cargo lifting equipment,it is very important to improve transportation efficiency,save energy and strictly ensure safety for overhead ***,many traditional control strategies can not meet these needs *** this end,a composite control framework made up of optimal trajectory planning and Safety-Critical tracking controller is studied in this ***,optimal trajectories are obtained by the optimal control *** analysis is used to obtain a tractable optimal solution for overhead crane ***,control Lyapunov functions(CLFs) and high-order control barrier functions(HOCBFs) are used to track the optimal states and account for constraints with arbitrary relative degrees,*** CBF method is computationally efficient while providing safety *** results show that the proposed method is effective.
作者：
Xu, RuijieChen, ShichaoSun, WenqiaoLv, YishengLuo, JialiangTang, YingInstitute of Automation
Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation
Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute
The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation
Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation
Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University
Department of Electrical and Computer Engineering Glassboro United States
Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system ...
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Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers th...
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In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman ***, an algorithm is propo...
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To address the challenges of low position tracking accuracy and high vibrations in mechanical arms controlled by PID closed-loop systems, this paper introduces a torque feedforward control scheme based on dynamic mode...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
To address the challenges of low position tracking accuracy and high vibrations in mechanical arms controlled by PID closed-loop systems, this paper introduces a torque feedforward control scheme based on dynamic models. The paper initially analyzes the causes of vibrations during robot motion, establishing a mathematical model to quantify the trajectory accuracy and repeatability of vibrations. Subsequently, a torque feedforward control scheme based on dynamic models is designed, and its feasibility is theoretically analyzed. In this motion control scheme, precise dynamic models are utilized to calculate and output the desired torque. The torque values are then converted into motor current values, which are superimposed on the control output of the current loop in the servo to achieve real-time torque compensation. Finally, through simulation experiments, the paper validates that the dynamics-based torque feedforward control effectively suppresses robot vibrations, enhances tracking accuracy,and improves dynamic performance. The findings demonstrate the efficacy of the proposed control strategy in addressing the challenges associated with PID-controlled robotic arm systems.
Aiming at the compliance control of rigid manipulators in human-robot interaction scenarios, a new variable impedance control(VIC) model is proposed to improve the adaptive ability of the manipulator to adjust complia...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
Aiming at the compliance control of rigid manipulators in human-robot interaction scenarios, a new variable impedance control(VIC) model is proposed to improve the adaptive ability of the manipulator to adjust compliance in different phases of the task. The parameter selection problem is transformed into a controller design problem. Impedance constraints are set by introducing the prior knowledge of the person, information about the state and contact force, and manipulability. The one-step model predictive control(MPC) method is used to search for the optimal solution of impedance parameters, so that the manipulator can adaptively select different balance relations between tracking accuracy and compliance. Moreover, in order to avoid the damage of time-varying impedance parameters to the stability, a tank-based method is implemented to ensure the passivity of the impedance system. Finally, the simulation results verify the effectiveness of the proposed control scheme.
Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a ...
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Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a loss ***,the imbalance of the loss function caused by parameter settings usually makes it difficult for PINNs to converge,*** they fall into local *** other words,the presence of balanced PDE loss,initial loss and boundary loss may be critical for the *** addition,existing PINNs are not able to reveal the hidden errors caused by non-convergent boundaries and conduction errors caused by the PDE near the ***,these problems have made PINN-based methods of limited use on practical *** this paper,we propose a novel physics-informed neural network,*** adaptive physics-informed neural network with a two-stage training *** algorithm adds spatio-temporal coefficient and PDE balance parameter to the loss function,and solve PDEs using a two-stage training process:pre-training and formal *** pre-training step ensures the convergence of boundary loss,whereas the formal training process completes the solution of PDE by balancing various loss *** order to verify the performance of our method,we consider the imbalanced heat conduction and Helmholtz equations often appearing in practical *** Klein-Gordon equation,which is widely used to compare performance,reveals that our method is able to reduce the hidden *** results confirm that our algorithm can effectively and accurately solve models with unbalanced loss function,hidden errors and conduction *** codes developed in this manuscript are publicy available at https://***/callmedrcom/ATPINN.
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