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Chinese Automation Congress (CAC)

作者： Liang Xu Hao Wang Ying Liu Wei Xue Ningning Li Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China National Key Laboratory for Complex Systems Simulation Beijing China Beijing Aerospace Propulsion Institute Beijing China

ISBN: (纸本)9781665426480

To address the problem of aeroengine PID parameter optimization and tuning, this work employs the excellent performance of the sparrow search algorithm (SSA) with high convergence accuracy and fast convergence speed to propose a self-tuning PID control method (SSA-PID) for aeroengine parameters. Considering that the oil supply output by the actuator may have a substantial overshoot, the proposed technique adds a penalty mechanism for the overshoot at the output, designs and improves the fitness function weighted by performance indicators, and effectively avoids the possible excessive overshoot and sharp oil supply phenomenon of the engine oil supply. The SSA-PID simulates and verifies the mathematical models of the turbofan engine’ s steady-state operating points on the ground and at high altitudes. The results show that the SSA-PID control method has better parameter tuning and optimization effects, a faster speed step response, and generates a fuel supply that does not have a targe overshoot, thereby proving its effectiveness and feasibility.

关键词： PI control Oils Search problems Mathematical models Steady-state PD control Fuels

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Study on control Strategy of the Vascular Interventional Surgical Robot Based on LADRC

Study on Control Strategy of the Vascular Interventional Sur...

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IEEE International Conference on Mechatronics and Automation

作者： Wenqiang Zhang Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots.

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Displacement measurement method based on laser self-mixing interference in the presence of speckle

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Chinese Optics Letters 2020年第5期18卷 11-15页

作者： Yan Zhao Haiwei Zhang School of Electrical and Electronic Engineering Tianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384China Tianjin Key Laboratory of Film Electronic and Comm unication Device Tianjin 300384China

In order to achieve the accurate measurement of displacement, this Letter presents a self-mixing interference displacement measurement method suitable for the speckle effect. Because of the speckle effect, the amplitude of the self-mixing interference signal fluctuates greatly, which will affect the measurement accuracy of displacement. The ensemble empirical mode decomposition is used to process the interference signal, which can filter out high-frequency noise and low-frequency noise at the same time. The envelope of the self-mixing interference signal is extracted by Hilbert transform, and it is used to realize the normalization of the signal. Through a series of signal processing, the influence of speckle can be effectively reduced, and the self-mixing interference signal can be transformed into standard form. The displacement can be reconstructed by fringe counting and the interpolation method. The experimental results show that the method is successfully applied to the displacement measurement in the presence of speckle, which verifies the effectiveness and feasibility of the method.

关键词： measurement displacement laser self-mixing interference

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Path Planning of the Spherical Robot based on Improved Ant Colony Algorithm 17

Path Planning of the Spherical Robot based on Improved Ant C...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Guo, Jian Huo, Xiaojie Guo, Shuxiang Xu, Jigang Tianjin University of Technology Binshui Xidao Extension 391 Tianjin Key Laboratory for Control Theory Applications In Complicated Systems and Intelligent Robot Laboratory Faculty of Engineering Tianjin300384 China Unit68709 Qinghai Haidong810700 China

ISBN: (纸本)9781728164151

With the development and progress of science and technology, the requirement of intelligent algorithm performance in the field of path planning is constantly improved. It is very important to improve the performance of intelligent algorithm and apply it in the field of path planning. In order to overcome the problem that ant colony algorithm tends to fall into local optimal in the early stage and converge slowly in the late stage. This paper proposed an ant colony algorithm based on adaptive pheromone updating strategy and enhanced negative feedback mechanism. The simulation results show that the improved ant colony algorithm is superior to the traditional ant colony algorithm and solves the problem of insufficient convergence in the early stage and low convergence in the late stage. Finally, the algorithm is tested by spherical robot. The experimental results show that the improved ant colony algorithm overcomes the shortcomings of traditional algorithms and verifies the effectiveness and convergence of the algorithm. © 2020 IEEE.

关键词： Motion planning

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Study on 6D Pose Estimation System of Occlusion Targets for the Spherical Amphibious Robot based on Neural Network

Study on 6D Pose Estimation System of Occlusion Targets for ...

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IEEE International Conference on Mechatronics and Automation

作者： Chaofeng Du Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications in Complicated systems and Intelligent Robot Laboratory Tianjin University of Technology BinshuiXidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

The amphibious robot needs to accurately estimate the 6D pose of the target in tasks such as target tracking, docking with the recovery module, and target grasping. The current research on target 6D pose estimation is mainly applied to unoccluded targets, but when the target is occluded, the target’s pose cannot be accurately identified. Compared with other algorithms, the PVNet algorithm shows better robustness when target is occluded, but the accuracy is still low. To improve the accuracy of the PVNet algorithm, this paper adds the confidence score prediction of the prediction vector at the last layer of the PVNet network, and designs a vector confidence score loss function to train the network. Before generating the hypothetical keypoints, the pixels whose confidence score is lower than the set threshold are screened out, so that the generated hypothetical 2D keypoints are closer to the true 2D keypoints. Finally, the method in this paper is compared with the Tekin, PoseCNN, Oberweger and Pvnet algorithm, and demonstrate the superiority of the proposed method.

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A DDPG-Based Method of Autonomous Catheter Navigation in Virtual Environment

A DDPG-Based Method of Autonomous Catheter Navigation in Vir...

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IEEE International Conference on Mechatronics and Automation

作者： Wei Tian Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

Vascular interventional surgery is the main method for treating cardiovascular diseases. But navigating endovascular catheters through the vascular tree is a highly challenging task even for highly trained specialists. Automation of this task can reduce the burden on surgeons and is expected to improve the surgical outcomes. Although there have been relevant studies utilizing reinforcement learning algorithms to realize autonomous navigation of catheter in the virtual environment Cathsim. However, the kinematics model of the catheter in Cathsim does not conform to the operating mode of the catheter in real vascular interventional surgery. Besides, there are problems such as low success rates of catheter autonomous navigation tasks. To address these issues, this paper modifies the kinematics model of the catheter in Cathsim and designs a catheter autonomous navigation model based on reinforcement learning DDPG (Deep Deterministic Policy Gradient) algorithm. The experimental results show that the agents trained through DDPG in this paper performs better than the agents trained through PPO (Proximal Policy optimization) in other studies in terms of navigation task success rate, completion time, and contact force between the catheter and vascular wall during the navigation process.

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A New Locally Active Memristive Synapse Coupled Neuron Model

Research Square

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Research Square 2021年

作者： Li, Ronghao Wang, Zenghui Dong, Enzeng Tianjin Key Laboratory For Control Theory & Applications in Complicated Systems Tianjin University of Technology Tianjin300384 China Department of Electrical and Mining Engineering University of South Africa Florida1710 South Africa

In this paper, a new type of non-volatile locally active memristor with bi-stability is proposed by injecting appropriate voltage pulses to realize a switching mechanism between two stable states. It is found that the memristive parameters of the new memristor can affect the local activity, which has been rarely reported, and this phenomenon is explained based on mathematical analyses and numerical simulations. Then, a locally active memristive coupled neuron model is constructed using the proposed memristor as a connecting synapse. The parameter-associated dynamical behaviors are revealed by bifurcation plots, phase plane portraits and dynamical evolution maps. Moreover, the bi-stability phenomenon of the new coupled neuron model is disclosed by local attraction basins, and the periodic burster and multi-scroll chaotic burster are found if a multi-level pulse current is used to imitate a periodical external stimulus on the neurons. The Hamiltonian energy function is calculated and analyzed with or without external excitation. Finally, the neuronal circuit is designed and implemented, which can mimic electrical activity of the neurons and is useful for physical applications. The experimental results captured from the analog circuit are consistent well with the numerical simulation results. © 2021, CC BY.

关键词： Memristors

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application of Improved PSO-ELM in Auto Insurance Customer Risk Level Prediction 17

Application of Improved PSO-ELM in Auto Insurance Customer R...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Chen, Xi Xu, Liang Wang, Yalong Zhai, Xiang Guo, Xiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory Applications in Complicated Systems School of Electrical and Electronic Engineering Tianjin300384 China Picc Property and Casualty Limited Operation Sharing Department Beijing100022 China

ISBN: (纸本)9781728164151

In order to improve the prediction accuracy of automobile insurance customer's risk level, a prediction model of automobile insurance customer's risk level based on GSPSO - ELM is proposed. The premium, insurance amount, number of risks, gender, driving age and other indicators were used as the main criteria to predict the risk level. The simulation results show that the proposed GSPSO - ELM prediction model can not only overcome the local optimal, and has higher precision of prediction, forecasting results of the mean square error (mse), decision coefficient and mean absolute percentage error and dynamic inertia weight PSO algorithm to optimize extreme learning machine, linear decreasing inertia weight PSO algorithm to optimize extreme learning machine model are improved. © 2020 IEEE.

关键词： Forecasting

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Study on Autonomous Surgical control System of The Vascular Interventional Surgical Robot Based on Catheter Tip Location Tracking

Study on Autonomous Surgical Control System of The Vascular ...

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IEEE International Conference on Mechatronics and Automation

作者： Zhimin Feng Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

The control system of vascular interventional surgical robot is a complex nonlinear system. When the catheter is inserted into human blood vessels, due to the irregular and curved shape of human blood vessels, the catheter will undergo small deformation, which will affect the displacement of the catheter. In order to reduce the displacement tracking error, a BP neural network PID controller was designed to compensate the displacement error of the autonomous vascular interventional surgical robot. Firstly, the dynamic analysis is carried out according to the axial displacement motion of the vascular interventional surgical robot, and the catheter displacement tracking controller was designed. According to the displacement error, BP neural network PID control is used to output three parameters of PID. Finally, in the experiment and PID control simulation comparison, the results show that the BP neural network PID control has a small displacement tracking error and superior tracking performance, which can meet the requirements.

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Design of control System for Lower Limb Rehabilitation Robot on the Healthy Side sEMG Signal

Design of Control System for Lower Limb Rehabilitation Robot...

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IEEE International Conference on Mechatronics and Automation

作者： Shiqin Yu Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

With the number of stroke patients increasing year by year, rehabilitation exoskeleton robot has been paid more and more attention. For the rehabilitation exoskeleton robot, human-computer interaction ability is an important index, which affects the effect of rehabilitation therapy to a great extent. Surface Electromyography (sEMG) signals are the combined effect of sEMG signals and electrical activities on nerve stem on the skin surface, which can reflect neuromuscular activities in advance and can be used to predict movement intention by sEMG signals. Therefore, this article proposes to use sEMG signals to monitor the motion information of the healthy leg in real-time, extract the characteristics of the electromyography signals, use the sEMG of the healthy leg as the control signal, reflect the motion patterns reflected by the sEMG collected from the healthy side, and then use the motion intention recognition method of Long Short Term Memory(LSTM) neural network to identify the motion intention of the prosthetic limb by identifying the motion patterns of the swing phase of the healthy side. The results indicate that the predicted maximum Root Mean Squared Error(RMSE) is 5.3729, which proves the feasibility of using LSTM model for motion intention recognition and contributes to the real-time and accuracy of lower limb exoskeleton rehabilitation.

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