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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Hong Zhan Chao Zeng Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Computer Science University of Liverpool Liverpool UK

ISBN: (数字)9798331517519

ISBN: (纸本)9798331517526

This paper applies the proposed hybrid force and position control method to the physical robot system with interaction tasks to further improve our previous study. In the control scheme, the variable stiffness based on proportional integral derivative(PID) admittance control is adopted for interaction force tracking and the radial basis function neural network(RBFNN) based fixed-time control is designed to ensure position tracking. We have performed interaction tasks based on a Baxter robot for drawing on the plane and slope plane with different expected interaction forces and position trajectories. The experiment results indicate that the method performs well in terms of interaction force and trajectory tracking.

关键词： Mechatronics Automation Trajectory tracking Force Dynamics Position control Trajectory Robots Admittance control Convergence

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A vision-based autonomous landing method on mobile platform for UAV

A vision-based autonomous landing method on mobile platform ...

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第42届中国控制会议

作者： Yongbin Zhu Hailong Pei Liping Wang Yuyuan Huang Kangqi Ou Key Lab of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Eng.Tech.Research Center of Guangdong College of Automation Science and Engineering South China University of Technology

As the application scenarios of multi-rotor Unmanned Aerial Vehicles(UAVs) become more and more extensive, the field of target tracking and accurate landing has become one of the research hotspots. In order to realize the accurate autonomous landing of UAV, considering the increasingly mature visual navigation technology, this paper proposed a hierarchical landmark based on nested rectangles and its relative positioning algorithm, and designed a set of autonomous landing system for the mobile platform of quadrotor UAV. The landmark has a high recognition rate of different heights and good expansibility. The algorithm has high computational efficiency and low performance requirements for image processing equipment, thus the system has good accuracy and robustness. The simulation and flight experiment show that the proposed algorithm can effectively realize the accurate autonomous landing of UAV.

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Process Monitoring of Operational Cost for Wastewater Treatment Processes Using Variants of ARMA Models Based Soft-sensors 11

Process Monitoring of Operational Cost for Wastewater Treatm...

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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Lu, Yu Liu, Yiqi Li, Dong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Technical University of Denmark Department of Chemical and Biochemical Engineering Lyngby Denmark

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Process monitoring of operation cost index (OCI) is of great importance for wastewater treatment plants (WWTPs), which is not only able to support financial budget, but also to optimize local operation. This paper proposed four variants of auto-regressive and moving average (ARMA), based on recursive least squares algorithm (RLS), ARMA based on recursive extended least squares algorithm (RELS), nonlinear auto-regressive neural network (NARNN), and nonlinear auto-regressive neural network with external input (NARXNN) respectively, to predict the operating cost in WWTPs. The proposed methods were validated in the simulation platform, Benchmark Simulation Model No.2-P (BSM2-P). On account of the strong nonlinearity of the wastewater treatment process, the nonlinear model, like NARXNN, achieved better performance in terms of mean square error (MSE) and correlation coefficient (R). © 2022 IEEE.

关键词： Wastewater treatment

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Compound Learning-Based Model Predictive control Approach for Ducted-Fan Aerial Vehicles

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2025年第5期36卷 9395-9407页

作者： Manzoor, Tayyab Pei, Hailong Xia, Yuanqing Sun, Zhongqi Ali, Yasir Zhongyuan Univ Technol Sch Automat & Elect Engn Zhengzhou Henan Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Key Lab Autonomous Syst & Networked Control Sch Automat Sci & EngnMinist Educ Guangzhou 510640 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Zhongyuan Univ Technol Zhengzhou 450007 Henan Peoples R China Silesian Tech Univ Fac Automat Control Elect & Comp Sci Joint Doctoral Sch Dept Telecommun & Teleinformat PL-44100 Gliwice Poland

Designing an efficient learning-based model predictive control (MPC) framework for ducted-fan unmanned aerial vehicles (DFUAVs) is a difficult task due to several factors involving uncertain dynamics, coupled motion, and unorthodox aerodynamic configuration. Existing control techniques are either developed from largely known physics-informed models or are made for specific goals. In this regard, this article proposes a compound learning-based MPC approach for DFUAVs to construct a suitable framework that exhibits efficient dynamics learning capability with adequate disturbance rejection characteristics. At the start, a nominal model from a largely unknown DFUAV model is achieved offline through sparse identification. Afterward, a reinforcement learning (RL) mechanism is deployed online to learn a policy to facilitate the initial guesses for the control input sequence. Thereafter, an MPC-driven optimization problem is developed, where the obtained nominal (learned) system is updated by the real system, yielding improved computational efficiency for the overall control framework. Under appropriate assumptions, stability and recursive feasibility are compactly ensured. Finally, a comparative study is conducted to illustrate the efficacy of the designed scheme.

关键词： Aerial robots machine learning (ML) model predictive control (MPC) reinforcement learning (RL) unmanned aerial vehicles (UAVs) Aerial robots machine learning (ML) model predictive control (MPC) reinforcement learning (RL) unmanned aerial vehicles (UAVs)

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Event-triggered distributed model predictive control scheme for temperature regulation in multi-zone air conditioning systems with improved indoor thermal preference indicator

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INTERNATIONAL JOURNAL OF ADAPTIVE control AND SIGNAL PROCESSING 2023年第6期37卷 1389-1409页

作者： Gao, Jingjing Yang, Xu Zhang, Shilong Tu, Rang Ma, Hongjun Univ Sci & Technol Beijing Sch Automation & Elect Engn Key Lab Knowledge Automation Ind Proc Minist Educ Beijing Peoples R China Univ Sci & Technol Beijing Sch Civil & Resources Engn Beijing Peoples R China South China Univ Technol Sch Automation Sci & Engn Key Lab Autonomous Syst Networked Control Minist Educ Guangzhou Peoples R China Univ Sci & Technol Beijing Sch Automation & Elect Engn Lab Knowledge Automation Ind Proc Minist Educ Beijing 100083 Peoples R China

Driven by the increasing needs in multi-zone buildings for reducing the air conditioning (A/C) system related energy consumption and increasing the occupants' thermal comfort, an event-triggered distributed model predictive control (DMPC) scheme for building temperature regulation with improved indoor thermal preference indicator is proposed. To this end, a temperature-energy model of the A/C system in a zone which considers multiple types of heat transfer, and the system model of the multi-zone A/C system are derived first. On this basis, an improved indoor thermal preference indicator that trades off the A/C systems related energy consumption with the aggregate thermal comfort of the occupants is proposed for the multi-zone A/C system, then the optimal indoor temperature set-points for each zone are determined by using the distributed consensus algorithm. It is followed by an event-triggered DMPC scheme by adjusting the A/C systems to arrive at the optimal indoor temperature set-points for all the zones with lower communication and computation load. The performance and effectiveness of the proposed methods are demonstrated through a case study on an actual multi-zone A/C system.

关键词： distributed consensus algorithm event-triggered distributed model predictive control improved indoor thermal preference indicator multi-zone air conditioning system

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Prescribed Time Attitude Tracking control of Unmanned Aerial Vehicles Under Unknown Attacks and Input Saturation

Prescribed Time Attitude Tracking Control of Unmanned Aerial...

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International Conference on control and Automation (ICCA)

作者： Liping Wang Hailong Pei Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems South China University of Technology Guangzhou P. R. China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper addresses the prescribed time performance attitude tracking control problem of un-manned aerial vehicles under unknown attacks and input saturation. The attitude error dynamic model is constructed under the framework of Lie group SO(3). By integrating a prescribed time performance function with coordinate transformation, the tracking error can remain within a given region in a prescribed time. In the backstepping design process, a first-order sliding mode differentiator is given to overcome the explosion of complexity problem, and nonlinear disturbance observer is developed to deal with the unknown attacks and input saturation. A prescribed time performance attitude tracking control method is designed to ensure that all of the closed-loop signals are bounded. Finally, the superiority and effectiveness of the designed controller are stated by the simulation results.

关键词： Backstepping Attitude control Communication systems Simulation Lie groups Explosions Disturbance observers

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Multi-Objective Optimal control of Wastewater Treatment Processes Constrainted by Energy-Saving and Effluent Qualities 6

Multi-Objective Optimal Control of Wastewater Treatment Proc...

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6th International Conference on Robotics, control and Automation Engineering, RCAE 2023

作者： Zhang, Jing Yan, Haoming Chen, Hongtian Xu, Shuiqing Liu, Yiqi School of Automation Science & Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou510640 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China College of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

ISBN: (纸本)9798350315301

Considering the high energy consumption problem in the wastewater treatment process, this paper proposes a multi-objective optimization control scheme based on NSGA-II algorithm. The proposed scheme can not only ensures meet effluent quality requirements but also can achieves energy cost savings. This method takes the aeration energy consumption and pumping energy consumption of the system as the optimization goal with the effluent water quality being the constraint condition. At the same time, the adaptive fuzzy PID controller is designed to ensure the control accuracy and stability of the controlled system. The results of simulation experiments validated in benchmark simulation platform, BSM1, show that, compared with PI control and single-objective optimization control, the proposed optimization scheme in this paper can achieve the desired quality of the effluent water withmore energy-saving. © 2023 IEEE.

关键词： Energy utilization

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Novel neural adaptive terminal sliding mode control for TCP network systems with arbitrary convergence time

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NEURAL COMPUTING & APPLICATIONS 2023年第27期35卷 20365-20374页

作者： Qi, Xuelei Li, Chen Chen, Bao Ni, Wei Ma, Hongjun Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Commonwealth Sci & Ind Res Org CSIRO Sydney NSW 2122 Australia South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou Peoples R China

The problem of adaptive arbitrary convergence time terminal sliding mode control (TSMC) for nonlinear networked systems with completely unknown functions and nonresponsive UDP stream disturbances is studied. In this work, an improved sliding surface based on arbitrary convergence time is designed to overcome the issue that the convergence rate depends on the system state. Different from the traditional TSMC, this paper introduces holistically an auxiliary term (nonautonomous differential equation) into the design of a sliding mode controller, which can compensate for the influence of neural adaptive approximation error and ensure the convergence of a closed-loop system at prescribed time. A robust compensation signal is also constructed by introducing a super twisting disturbance observer to process nonresponsive UDP flows. In addition, the controller is designed in a piecewise continuous manner, so that the sliding mode surface can be selected arbitrarily, according to the adaptation after the prescribed time. The effectiveness of the new controller is verified by extensive simulations in comparison with related works.

关键词： Network congestion control Terminal sliding mode control Arbitrary convergence time Neural network

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Affine Iterative Closest Point Algorithm Based on Color Information and Correntropy for Precise Point Set Registration

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SENSORS 2023年第14期23卷 6475-6475页

作者： Liang, Lexian Pei, Hailong South China Univ Technol Key Lab Autonomous Syst & Networked Control Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Minist Educ Guangzhou 510640 Peoples R China

In this paper, we propose a novel affine iterative closest point algorithm based on color information and correntropy, which can effectively deal with the registration problems with a large number of noise and outliers and small deformations in RGB-D datasets. Firstly, to alleviate the problem of low registration accuracy for data with weak geometric structures, we consider introducing color features into traditional affine algorithms to establish more accurate and reliable correspondences. Secondly, we introduce the correntropy measurement to overcome the influence of a large amount of noise and outliers in the RGB-D datasets, thereby further improving the registration accuracy. Experimental results demonstrate that the proposed registration algorithm has higher registration accuracy, with error reduction of almost 10 times, and achieves more stable robustness than other advanced algorithms.

关键词： point set registration RGB-D data iterative closest point color Information correntropy

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Adaptive Dynamic Programming for Optimal control of Unknown LTI System via Interval Excitation

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IEEE Transactions on Automatic control 2025年

作者： Ma, Yong-Sheng Sun, Jian Xu, Yong Cui, Shi-Sheng Wu, Zheng-Guang The National Key Lab of Autonomous Intelligent Unmanned Systems School of Automation Beijing Institute of Technology Beijing100081 China The Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

This paper investigates the optimal control problem for an unknown linear time-invariant (LTI) system. To solve this problem, a novel composite policy iteration (CPI) algorithm based on adaptive dynamic programming is developed to adaptively learn the optimal control policy from system data. The existing methods require the initial stabilizing control policy, the persistence of excitation (PE) condition and the data storage to ensure the algorithm convergence. Fundamentally different from them, these restrictions can be relaxed in the proposed method. Specifically, an adaptive parameter is elaborately designed to remove the requirement of the initial stabilizing control policy. Besides, an online data calculation scheme is proposed, which can not only replace the stored historical data by online data, but also can relax the PE condition to the interval excitation (IE) condition. The simulation results demonstrate the efficacy of the proposed algorithm, and its superiority is also demonstrated by comparing it with existing algorithms. © 1963-2012 IEEE.

关键词： Dynamic programming

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