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A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators

A Trajectory Tracking Algorithm Based on Interior Point Meth...

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2022 Chinese Automation Congress, CAC 2022

作者： Rao, Xuechen Gan, Yahui Wang, Xiaoteng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation NanJing China

ISBN: (纸本)9781665465335

At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm. © 2022 IEEE.

关键词： Convex optimization

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Generalized Proportional Integral Observer Based Sliding Mode control for Biaxial Motion control System with Mismatched Disturbances 41

Generalized Proportional Integral Observer Based Sliding Mod...

引用

第41届中国控制会议

作者： Guancheng Ren Zuo Wang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Shenzhen Research Institute Southeast University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the biaxial motion system,nonlinearities and mismatched disturbances always have adverse effects on the contouring accuracy,which are often *** of existing advanced control methods are developed only to suppress matched *** this paper,the necessity of taking the contour error as the control target is ***,four generalized proportional integral observers(GPIOs) are developed to estimate both matched and mismatched lumped ***,based on contour error,a sliding mode controller is developed for the biaxial motion *** introducing the disturbance estimations into the modified sliding surface design,a composite controller is *** proposed method effectively improves the contouring accuracy and suppress the mismatched disturbances,while the chattering caused by large switching gains is *** stability analysis of the system is established by means of the Lyapunov ***,to demonstrate the superiority and effectiveness of the controller,simulation results of the biaxial motion control system are presented in various working cases.

关键词： Biaxial motion control system contouring control mismatched disturbances generalized proportional-integral observer(GPIO) sliding mode control chattering reduction

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Composite Model Predictive control for PMSM Servo Systems Based on Backlash Cancellation and Disturbance Compensation 41

Composite Model Predictive Control for PMSM Servo Systems Ba...

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第41届中国控制会议

作者： Lei Li Zuo Wang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Shenzhen Research Institute Southeast University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper investigates the speed regulation problem of permanent magnet synchronous motor(PMSM) servo system with backlash based on model predictive control(MPC).It is known that the existing backlash in servo systems causes steady-state errors,limit cycles and rigid *** order to counteract the adverse performance degradations of the backlash nonlinearity,a composite MPC strategy is investigated based on backlash cancellation and disturbance ***,an approximated dead-zone model of backlash is ***,a generalized proportional-integral observer(GPIO) is constructed to estimate the lumped disturbances,including backlash modelling residual error,parameter uncertainties and external *** introducing disturbance estimation and backlash transmission torque into system model,a composite MPC can be obtained based on the prediction-precision enhanced model,which brings significantly improvements to control ***,the efficacy of the presented method is demonstrated by simulation results.

关键词： Model predictive control(MPC) PMSM servo system Backlash cancellation Generalized proportional-integral observer(GPIO)

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Multi-task Learning Based Single Temporal Remote Sensing Image Change Detection 23

Multi-task Learning Based Single Temporal Remote Sensing Ima...

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Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition

作者： Peixuan Yang Yichao Cao Xiaobo Lu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University China

ISBN: (纸本)9798400707988

Change Detection is a classic and fundamental task in remote sensing(RS), and has accomplish remarkable achievement on bitemporal image based methods. However, bitemporal images are very expensive and needs professional researchers to align and label the paired images. Furthermore, most bitemporal image based methods are only semantic-aware not instance-aware, which indicates these methods only use paired images’ semantic information. Thus, we propose a method that only needs unpaired RS images with semantic labels. In this paper, we introduce multi-task learning into change detection progress, which comprises four major parts: Boundary-Aware Module, Contextual-Aware Module, Segmentation Module, Change Detection Module. At first, we construct Boundary-Aware Module and Contextual-Aware Module to extract sharp boundary and dense contextual features. Then we feed the feature maps to Change Detection Module and Segmentation Module to accomplish the subtasks. The comprehensive experiments on a single temporal image dataset demonstrate the efficiency of our approach over other bitemporal image based methods, and the experimental results shows our approach is competitive with other methods while all methods was trained on bitemporal image dataset.

关键词： Change Detection Multi-task Learning Single Temporal Image

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Anti-disturbance Low Speed Regulation control of PMSMs Using Modified Extended State Observer Based on Rotor Position

Anti-disturbance Low Speed Regulation Control of PMSMs Using...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. However, the position signal of encoder with quantization errors results in crawling and shaking at low speeds. Considering quantization error as a type of noise limited their own accuracy, the environmental influences like mechanical vibration and electromagnetic interference also lead to noise in rotor position. The modified ESO method incorporated a Kalman filter (KF) is proposed to reduce the negative impact of noise. Due to differential amplification noise, the position signal is used instead of traditional speed signal for observers design because of its undesirable characteristics at low speed. The modified ESO based on rotor position is used to estimate both speed signal and disturbances to enhance the low speed performance in the presence of disturabances and measurement noise. The friction model is embedded for above integrated structure due to its nonliearity at low speeds. Considering the negative effects of measurement noise and disturbance at low speeds, it has verified that the proposed algorithm has better dynamic and steady-state performance and anti-disturbance ability through simulation. © The Institution of Engineering & Technology 2024.

关键词： State estimation

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A nested constraints based anti-disturbance collision-free formation control scheme for multi-mobile robot systems

A nested constraints based anti-disturbance collision-free f...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Guodong Wang, Xiangyu Li, Shihua Niu, Dan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China

ISBN: (纸本)9781665465335

This paper investigates distributed formation control of multi-mobile robot systems with collision avoidance. A novel nested constraints based anti-disturbance formation control scheme is established, which contains two parts. In the first part, a formation signal generator is constructed on the communication network by using proper distributed cooperative control approaches and artificial potential field-based methods, such that it "completes"the desired formation control task in its outputs. In the second part, by combining proper disturbance estimations, some nonlinear tracking controllers are designed for the robots to track the corresponding outputs of the generator asymptotically. A "nested constraint mechanism"is put forward accordingly and applied to limit the generator's outputs and the robots' tracking errors. In this way, the studied multi-mobile robot systems realize the formation control goal with collision avoidance. Compared with existing results, the proposed method has a better plug-and-play feature to deal with the tight encapsulations of the practical robot products, and has better convergence performances with the existence of disturbances. Some experiments are given to validate the effects of the proposed methods. © 2022 IEEE.

关键词： Collision avoidance

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Transformer Based Multi-modal Fusion For Place Recognition with Self-attention Mechanism

Transformer Based Multi-modal Fusion For Place Recognition w...

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2022 Chinese Automation Congress, CAC 2022

作者： Pan, Yan Yu, Xiang Chang, Zeqing Fang, Fang Zhou, Bo School of Automation Southeast University Ministry of Education The Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China

ISBN: (纸本)9781665465335

Autonomous driving still leaves a challenging task that how to apply the complementary information captured from different sensors, i.e. cameras and LiDAR, to handle place recognition task. In this paper, a brand new pipeline was designed to tackle the retrieval problem with a multi-modal late fusion. The light-weighted convolutional blocks is applied to encode features from images, followed by converting them into pseudo point clouds. Inspired by the progress of the Transformer, the network employs a residual point transformer module to extract feature vectors for 3D points and pseudo point clouds respectively. Finally, the two corresponding local descriptors are fused to get a robust fused global descriptor, which is capable of place recognition task after end-to-end training. Experimental results collected from sequence 00, 02, 05, 06 of KITTI dataset validate that fusing information from two modalities is able to enhance performance. © 2022 IEEE.

关键词： Autonomous vehicles

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Robust Velocity-Regulation control of Gimbal Servo Systems Using a Predictive Comprehensive Disturbance Observer

Robust Velocity-Regulation Control of Gimbal Servo Systems U...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Yang, Weifeng Jiang, Yuan Li, Shihua Nanjing Chenguang Group Co. Ltd Nanjing210008 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

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 characteristics and external time-varying disturbances. First, to enable a more accurate estimation and compensation against disturbances of multifrequency-band under input time-delay, a generalized system modelling of GSS is developed with detailed classification and description of different uncertainties. On the basis of such a generalized model, a predictive comprehensive disturbance observer (PCDO) is designed to accurately predict both system states and multiple disturbances with multi-frequency-band. Based upon the predictions provided from PCDO, a composite controller is further constructed to ensure the closed-loop stability of GSS. A rigorous robust stability proof of the closed-loop system is presented. Simulation analysis under various uncertainties are conducted to thoroughly validate the efficacy of the proposed PCDO-based control approach. © The Institution of Engineering & Technology 2024.

关键词： Time delay

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Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control 5

Inverse Reinforcement Learning Integrated Reinforcement Lear...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Gu, Shiyi Zhang, Tingting Zhang, Ya Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China Army Engineering University College of Command and Control Engineering Nanjing210017 China

ISBN: (纸本)9798350325294

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises. © 2023 IEEE.

关键词： Reinforcement learning

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Optimal Trajectory Planning and Safety-Critical control for Underactuated Overhead Cranes

Optimal Trajectory Planning and Safety-Critical Control for ...

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第43届中国控制会议

作者： Weihong Chen Zheng Tian Jun Yang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

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.

关键词： Safety-Critical control Optimal control control Barrier Functions Overhead Cranes

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