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第43届中国控制会议

作者： Zhuolin Tan Xiaochen Xie Jiantai Huang Department of Automation Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper investigates the direct model reference adaptive control(MRAC) of periodic systems with slow timevarying dynamics and disturbance input. It is necessary to approximate the periodic slow time-varying system as a periodic piecewise linear system for MRAC. Based on the stability criteria of the periodic piecewise linear reference system, a new sufficient condition in terms of linear matrix inequalities(LMIs) is established to obtain the Lyapunov matrices and design the adaptive update law for the state feedback controller gains. Different from previous studies, where asymptotic tracking was possible only in the presence of a common Lyapunov function for the reference models, the asymptotic tracking in this work is achieved through a periodic time-varying Lyapunov matrix function. A numerical example validates the proposed MRAC scheme, and the effectiveness of the modified approach is discussed.

关键词： Model Reference Adaptive Control Periodic Slow Time-Varying System Periodic Piecewise Linear System

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Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

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Modeling of the Constant-Current Stimuli Response of a Bio-Robot for Long-Term Motion Control

Modeling of the Constant-Current Stimuli Response of a Bio-R...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhou, Jie Fang, Yuan Chen, Yang Li, Yao Li, Bing Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

ISBN: (纸本)9781665481090

Bio-robots continue to receive attention because of their small size and low power consumption. Unfortunately, it currently faces two major obstacles before practical application. The first is the habituation issue, insects are difficult to be effectively controlled for a long time by electrical stimuli signals. The other one is the lack of model for motion control. In this research, we established a stimuli-response model for cockroach bio-robot based on long time current. A more convenient optic lobe implantation method has been proposed, which has lower attenuation and better stimuli effect. Constant electrical stimuli also significantly increased the number of effective controls for crawling. A cockroach bio-robot stimuli distance response model was established and validated with experiment data. Five parameters were including in this model, namely sex, length, weight, current amplitude and equivalent stiumated-number. This model can predict the movement distance of biological robots well. © 2024 IEEE.

关键词： Microrobots

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Design and Implementation of Model Predictive Control (MPC) Based Pressure Regulation System for a Precision Agricultural Sprayer

Design and Implementation of Model Predictive Control (MPC) ...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Adrees Khan Fazal Nasir Muhammad Tufail Muhammad Haris Muhammad Tahir Khan Zhang Dong Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

Model Predictive Control (MPC) is a control scheme that involves predicting the future behavior of a system and optimizing control actions to accomplish the desired objective. In this study, we develop an intelligent control algorithm, based on MPC to regulate the target pressure in variable-rate agriculture sprayer robots. Modeling and simulation steps of the spraying system are developed using MATLAB/Simulink environment, before passing to the description of the MPC algorithm. Real-time implementation of the MPC algorithm was conducted on an Arduino Mega 2560 controller board by using Simulink Support Package for Arduino Hardware in MATLAB/Simulink to experimentally validate the preliminary results of simulations. The work evaluates MPC to regulate the pressure in the system and compares the results with a traditional PID control system. Moreover, MPC is a novel method for nonlinear system control that achieves zero steady-state error, low transient response, and reduces peak overshoot compared to the results obtained with a PID controller, thereby reducing the waste of chemicals, and minimizing the toxicology and environmental risk.

关键词： Transient response Toxicology Software packages Spraying Agriculture Regulation Real-time systems

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Fault Diagnostic Opportunities for Robot Servo Motors Using the Physics of Failure Analysis 14

Fault Diagnostic Opportunities for Robot Servo Motors Using ...

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14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Zhang, Bo Liang, Shan Wang, Kai Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Computer Science and Technology University of Chemical Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350329988

Joint robots are widely used in various industries, such as aviation, aerospace, and automotive manufacturing. The performance degradation of servo motors can significantly affect the overall performance of the robots because of the core component of joint robots, and therefore, it is critical to detect and address servo motor failures promptly. In this study, we analyze some common causes and mechanisms of performance degradation in robot servo motors using the physics of failure analysis. We also discuss strategies for detecting and diagnosing faults using these mechanisms before the servo motors fail completely. © 2023 IEEE.

关键词： Servomotors

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Integrated Cam Contour Optimization Method Considering Kinematic and Dynamic Characteristics: A Paradigm of Offset Press Open-Close Gripper Mechanism

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Journal of Shanghai Jiaotong University (Science) 2024年 1-13页

作者： Li, Wenwei Cao, Shuai Qian, Qian Zhang, Yaling Chen, Nan Robotic Laboratory South China Robotics Innovation Research Institute Guangdong Foshan528300 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangzhou510070 China Foshan Zhiyouren Technology Co. Ltd. Guangdong Foshan528300 China School of Mechanical Engineering Southeast University Nanjing211189 China

To efficiently search out the optimal cam contour, a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented, and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism. The acceleration curve and the residual vibration model of the follower were separately studied. A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration, and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration. Accordingly, corresponding motion curve design software and Simulink vibration model of the follower were developed respectively, and they were integrated into an automatic optimization platform with iSIGHT. The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm. An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve. Based on the follower’s new motion curve, the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion. The offset press that installed our new designed cam exhibited a lower vibration than the previous machine, and the maximum measured acceleration of the offset press at a printing speed of 15 000 r/h is reduced by 7.7%. © Shanghai Jiao Tong University 2024.

关键词： Acceleration

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Smart Saline Level Monitoring System using Liquid Level Switch Contactless Sensor, NodeMCU and MQTT-S 1

Smart Saline Level Monitoring System using Liquid Level Swit...

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1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Kishore, S. Abarnaa, K.P. Priyanka, S. Sri Atchaya, S. Priyanka, P.L. Amala, Jerrin J Nikhil Bannari Amman Institute of Technology Department of Biomedical Engineering Sathyamangalam India Tu Dortmund University MSc Automation and Robotics Dortmund Germany

ISBN: (纸本)9781665497107

Advancement in the healthcare system is rapidly increasing in recent years due to the application of engineering principles and design concepts to medicine and biology. One of the most commonly used intravenous (IV) therapies, saline, plays a significant role in the treatment of disease patients. Saline plays a major role in replenishing lost fluid, extracellular fluid replacement like dehydration, hypovolemia, haemorrhage, sepsis. Generally, Surveillance of saline bottle levels is monitored by nurses and caretakers. There is an endless need to check the saline level after a particular time. If you don't, there's a good risk your blood may flow back into the saline bottle. Most of the time, due to negligence or an unusual scenario, the proper planning of removing the needle from the patient's vein is forgotten, resulting in a significant loss and maybe death. To avoid such accidents taking place due to the negligence of caretakers, it is proposed that the cost-effective smart saline level monitor which may be a reliable, user friendly and price effective system for saline level monitoring. This technique is built by employing a liquid level switch contactless sensor which is an ultra-low power and low cost sensor and NodeMCU ESP8266 Wi-Fi module microcontroller. The sensor's output is a specific voltage based on the presence of saline. The ESP8266 Wi-Fi module integrated on the NodeMCU microcontroller creates and broadcasts a specific message based on the voltage received from the sensor. MQTT-S is used to distribute/buy in convention, which works over TCP, to convey and introduce the communications to the end customer gadgets of endorsers such as specialists, medical attendants, or guardians. This proposed watching system ensures that messages are sent to supporters in a reliable manner, which is critical in medical treatment. © 2022 IEEE.

关键词： Microcontrollers

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CSANet: Cross-Semantic Attention Network for Open-Set Object Recognition 38

CSANet: Cross-Semantic Attention Network for Open-Set Object...

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

作者： Li, Yu Sun, Gan Liang, Wenqi Cheng, Pengchao Shenyang University of Technology Shenyang110870 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350303636

With the increase of real-world scenarios such as robotics, urban rescue and autonomous driving, deep learning models are increasingly exposed to open-set scenarios where established methods should separate the known and unknown categories in the real world. However, most existing open-set recognition methods treat all features equally and focus on learning features that facilitate the discrimination of categories during the training, which is detrimental to the performance of models in the open world. In response to this challenge, we propose a novel framework based on a Cross-Semantic Attention Network (i.e., CSANet) to guide the model to explore more comprehensive features. In detail, we apply cross-semantic attention to guide both the high-level semantic features and a set of learnable category prototypes, which encourages the model to better characterise known categories and facilitates its ability to discriminate unknown categories in the open world. In addition, we develop a combined loss that widens the inter-category distance and narrows the intra-category distance, thus reserving the unknown categories a larger position in the feature space. Experimental results on several popular open-set recognition datasets demonstrate the effectiveness and efficiency of our method. © 2023 IEEE.

关键词： Attention Open-Set Recognition Prototype Learning

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Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car

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Computers, Materials & Continua 2022年第5期71卷 2285-2302页

作者： Hajira Saleem Faisal Riaz Asadullah Shaikh Khairan Rajab Adel Rajab Muhammad Akram Mana Saleh Al Reshan Control Automotive and Robotics Lab Affiliated lab of National Center of Robotics and Automation(NCRA HEC Pakistan)and with the Department of Computer Science and Information TechnologyMirpur University of Science and Technology(MUST)Mirpur Azad Kashmir10250Pakistan College of Computer Science and Information System Najran UniversityNajran61441Saudi Arabia College of Computer Science and Engineering University of South FloridaTampa33620United States

Deep learning techniques,particularly convolutional neural networks(CNNs),have exhibited remarkable performance in solving visionrelated problems,especially in unpredictable,dynamic,and challenging *** autonomous vehicles,imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of *** this regard,globally,researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best *** has proven the superiority of metaheuristic algorithms over the manual-tuning of ***,to the best of our knowledge,these techniques are yet to be applied to address the problem of imitationlearning-based steering angle ***,in this study,we examine the application of the bat algorithm and particle swarm optimization algorithm for the optimization of the CNN model and its hyperparameters,which are employed to solve the steering angle prediction *** validate the performance of each hyperparameters’set and architectural parameters’set,we utilized the Udacity steering angle dataset and obtained the best results at the following hyperparameter set:optimizer,Adagrad;learning rate,0.0052;and nonlinear activation function,exponential linear *** per our findings,we determined that the deep learning models show better results but require more training epochs and time as compared to shallower *** show the superiority of our approach in optimizing CNNs through metaheuristic algorithms as compared with the manual-tuning *** testing was also performed using the model trained with the optimal architecture,which we developed using our approach.

关键词： Bat algorithm convolutional neural network hyperparameters metaheuristic optimization algorithm steering angle prediction

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Design and Control of Continuous Jumping Gaits for Humanoid Robots Based on Motion Function and Reinforcement Learning

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Procedia Computer Science 2024年 250卷 51-57页

作者： Zida Zhao Shilong Sun Haodong Huang Qingbin Gao Wenfu Xu State Key Laboratory of Robotics and System (HIT) Harbin Institute of Technology Harbin Heilongjiang China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China

Continuous jumping of humanoid robots is a challenging problem that requires appropriate gait and force control for the robot to achieve. Reinforcement learning (RL) has been applied to the motion control of humanoid robots and has achieved significant progress. However, traditional RL control methods primarily rely on designing reward signals to generate human-like movements, and it requires developing complex reward signals for continuous jumping, resulting in limited actions and suboptimal jumping performance. To address this issue, we have designed motion functions for humanoid continuous jumping and incorporated them into the RL framework to obtain desired human-like continuous jumping actions. Furthermore, two different jumping gaits are designed to investigate the jumping effects produced by different jumping functions: bent-knee jumping (BJ) and straight-knee jumping (SJ). BJ is a typical jumping style where the legs flex during the jumping process to accumulate energy, enabling higher explosive power. SJ is more suitable for tasks requiring quick responses, as the legs remain upright during the jump, providing faster reaction speed. The performance in continuous jumping tasks has been evaluated by comparing the effects of training with different jumping functions. This research has particular guidance for improving the jumping ability of robots and enhancing the stability and efficiency of humanoid continuous jumping.

关键词： Continuous jumping gaits Humanoid robots Motion function Reinforcement learning

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