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Control for a Class of Stochastic Mechanical Systems Based on the Discrete-Time Approximate Observer

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Journal of Systems Science & Complexity 2019年第2期32卷 526-541页

作者： FU Xinxin kang yu LI Pengfei yu Peilong Department of Automation University of Science and Technology of China

This paper investigates the observer-based control problem of a class of stochastic mechanical systems. The system is modelled as a continuous-time It o stochastic differential equation with a discrete-time output. Euler-Maruyama approximation is used to design the discrete-time approximate observer, and an observer-based feedback controller is derived such that the closed-loop nonlinear system is exponentially stable in the mean-square sense. Also, the authors analyze the convergence of observer error when the discrete-time approximate observer servers as a state observer for the exact system. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.

关键词： Approximate model discrete-time observer exponential stability stochastic nonlinear system

FVO: floor vision aided odometry

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Science China(Information Sciences) 2019年第1期62卷 95-107页

作者： Wenjun LV yu kang Jiahu QIN Department of Automation University of Science and Technology of China State Key Laboratory of Fire Science University of Science and Technology of China

In many indoor scenarios, such as restaurants, laboratories, and supermarkets, the planar floors are covered with rectangular tiles. We realized that the abundant parallel lines and crossing points formed by tile joints can be used as natural features to assist indoor localization, and thus we propose a novel indoor localization method for mobile robots by fusing odometry and monocular vision. The method comprises three steps. First, the heading and location of the mobile robot are approximately estimated by odometry based on incremental encoders. Second, with the aid of a camera, the lens of which points vertically toward the floor, the odometric heading estimation can be corrected by detecting the relative angle between the robot’s heading and the tile joints. Third, the odometric location estimation is corrected by detecting the perpendicular distance between the image center and the tile joints. As compared with the existing indoor localization methods, the proposed method, called floor vision aided odometry, is not only relatively low in economic cost and computational complexity, but also relatively high in accuracy and robustness. The effectiveness of this method is verified by a real-world experiment based on a differential-drive wheeled mobile robot.

关键词： mobile robot indoor localization monocular vision odometry tile joint

Self-Tuning Asynchronous Filter for Linear Gaussian System and Applications

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1054-1061页

作者： Wenjun Lv yu kang yunbo Zhao Department of Automation University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Fire Science Department of Automation and Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei 230027China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

In this paper, optimal filtering problem for a class of linear Gaussian systems is studied. The system states are updated at a fast uniform sampling rate and the measurements are sampled at a slow uniform sampling rate. The updating rate of system states is several times the sampling rate of measurements and the multiple is constant. To solve the problem,we will propose a self-tuning asynchronous filter whose contributions are twofold. First, the optimal filter at the sampling times when the measurements are available is derived in the linear minimum variance sense. Furthermore, considering the variation of noise statistics, a regulator is introduced to adjust the filtering coefficients adaptively. The case studies of wheeled robot navigation system and air quality evaluation system will show the effectiveness and practicability in engineering.

关键词： Air quality evaluation system linear Gaussian system wheeled robot navigation system

Price-Based Residential Demand Response Management in Smart Grids:A Reinforcement Learning-Based Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 123-134页

作者： Yanni Wan Jiahu Qin Xinghuo yu Tao Yang yu kang Department of Automation University of Science and Technology of ChinaHefei 230027China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China School of Engineering RMIT UniversityVIC 3000Australia State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Automation State Key Laboratory of Fire ScienceInstitute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei 230027China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of SciencesBeijing 100190China

This paper studies price-based residential demand response management(PB-RDRM)in smart grids,in which non-dispatchable and dispatchable loads(including general loads and plug-in electric vehicles(PEVs))are both *** PB-RDRM is composed of a bi-level optimization problem,in which the upper-level dynamic retail pricing problem aims to maximize the profit of a utility company(UC)by selecting optimal retail prices(RPs),while the lower-level demand response(DR)problem expects to minimize the comprehensive cost of loads by coordinating their energy consumption *** challenges here are mainly two-fold:1)the uncertainty of energy consumption and RPs;2)the flexible PEVs’temporally coupled constraints,which make it impossible to directly develop a model-based optimization algorithm to solve the *** address these challenges,we first model the dynamic retail pricing problem as a Markovian decision process(MDP),and then employ a model-free reinforcement learning(RL)algorithm to learn the optimal dynamic RPs of UC according to the loads’*** proposed RL-based DR algorithm is benchmarked against two model-based optimization approaches(i.e.,distributed dual decomposition-based(DDB)method and distributed primal-dual interior(PDI)-based method),which require exact load and electricity price *** comparison results show that,compared with the benchmark solutions,our proposed algorithm can not only adaptively decide the RPs through on-line learning processes,but also achieve larger social welfare within an unknown electricity market environment.

关键词： Demand response management(DRM) Markovian decision process(MDP) Monte Carlo simulation reinforcement learning(RL) smart grid

Sampled-data Observer Design for a Class of Stochastic Nonlinear Systems Based on the Approximate Discrete-time Models

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 507-511页

作者： Xinxin Fu yu kang Pengfei Li Department of Automation University of Science and Technology of China State Key Laboratory of Fire Science Department of AutomationInstitute of Advanced TechnologyUniversity of Science and Technology of China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Chinese Academy of Sciences IEEE

In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear ***-Maruyama approximation was investigated in this paper because it is the basis of other higher precision numerical methods,and it preserves important structures of the nonlinear ***,the form of Euler-Maruyama model is simple and easy to be *** results provide a reference for sampled-data observer design method for such stochastic nonlinear systems,and may be useful to many practical control applications,such as tracking control in mechanical *** the effectiveness of the approach is demonstrated by a simulation example.

关键词： Approximation model exponentially bounded sampled-data observer stochastic nonlinear

Microstructure and mechanical properties of automobile beam steels produced by EAF-CSP process

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Journal of University of Science and Technology Beijing 2006年第6期13卷 508-511页

作者： Zhengzhi Zhao Yonglin kang Hao yu Materials Science and Engineering School University of Science and Technology Beijing Beijing 100083 China

The microstructure, mechanical properties, and misorientation of automobile beam steels produced by EAF-CSP process were studied using optical microscopy （OM） and electron back-scattered diffraction （EBSD）. It is shown that the microstructure of strips is mainly polygonal ferrite, and the average grain size is about 5-8 μm. The electron back-scattered diffraction results show that grain boundaries in ferrite are basically high-angle grain boundaries without remarkable preferred orientation. Hot strips of automobile beam steels possess a good combination of strength and plasticity because of their fine microstructures and low quantity of impurities.

关键词： steel CSP microstructure mechanical property electron back-scattered diffraction

Robust Approximation-Based Event-Triggered MPC for Constrained Sampled-Data Systems

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Journal of Systems Science & Complexity 2021年第6期34卷 2109-2124页

作者： WANG Tao kang yu LI Pengfei ZHAO yun-Bo yu Peilong Department of Automation University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Fire Science University of Science and Technology of ChinaHefei 230027China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230027China College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

In this paper,an approximation-based event-triggered model predictive control(AETMPC)strategy is proposed to implement event-triggered model predictive control for continuous-time constrained nonlinear systems under the digital *** the AETMPC strategy,both of the optimal control problem(OCP)and the triggering conditions are defined in a discrete-time manner based on approximate discrete-time models,while the plant under control is continuous *** doing so,sensing load is alleviated because the triggering condition does not need to be checked continuously,and the computation of the OCP is simpler since which is calculated in the discrete-time ***,robust constraints are satisfied in a continuous-time sense by taking inter-sampling behavior into consideration,and a novel constraint tightening approach is presented ***,the feasibility of the AETMPC strategy is analyzed and the associated stability of the overall system is ***,this strategy is validated by a numerical example.

关键词： Approximations event-triggered control model predictive control sampled-data systems

Projection-based 3D bioprinting for hydrogel scaffold manufacturing

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Bio-Design and Manufacturing 2022年第3期5卷 633-639页

作者： yuan Sun kang yu Qing Gao Yong He State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Engineering for Life Group(EFL) Suzhou 215101China Key Laboratory of Materials Processing and Mold Zhengzhou UniversityZhengzhou 450002China Cancer Center Zhejiang UniversityHangzhou 310058China

Projection-based 3D bioprinting(PBP):a powerful method to fabricate 3D cellular structures Three-dimensional(3D)bioprinting has played an important role in tissue engineering and regenerative medicine areas over the past decade[1].Different from traditional cell cultures in Petri dishes,3D bioprinting can build bionic structures with a better potential to become artificial organ substitutes[2–4].With the development of photocurable biomaterials,the projection-based 3D printing method has been successfully applied in biological research[5,6].

关键词： printing biomaterials projection

Sampled-Data Stabilization of a Class of Stochastic Nonlinear Markov Switching System with Indistinguishable Modes Based on the Approximate Discrete-Time Models

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Journal of Systems Science & Complexity 2021年第3期34卷 843-859页

作者： ZHANG Qianqian kang yu yu Peilong ZHU Jin LIU Chunhan LI Pengfei Department of Automation University of Science and Technology of ChinaHefei 230026China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230026China

This paper investigates the stabilization issue for a class of sampled-data nonlinear Markov switching system with indistinguishable *** order to handle indistinguishable modes,the authors reconstruct the original mode space by mode clustering method,forming a new merged Markov switching *** specifying the difference between the Euler-Maruyama(EM)approximate discrete-time model of the merged system and the exact discrete-time model of the original Markov switching system,the authors prove that the sampled-data controller,designed for the merged system based on its EM approximation,can exponentially stabilize the original system in mean square ***,a numerical example is given to illustrate the effectiveness of the method.

关键词： Controller design Euler-Maruyama approximate discretization Markov switching system mode clustering