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第35届中国控制会议

作者： Dezhi Xu Yao Tang Nan Ji Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education)Institute of Automation Jiangnan University Editorial Office of Journal Systems Engineering and Electronics

ISBN: (纸本)9781509009107

In this paper,a reconfiguration flight-control via control re-allocation is developed for a reusable launch vehicle(RLV) under aerodynamic control surfaces *** dynamic control re-allocation scheme is based on real-time computation of linear matrix inequalities(LMIs).In the approach proposed here,control allocation is formulated as an optimization problem to minimize the performance *** into account non-negligible dynamics of the actuators with hard constraints,the presented scheme extends the existing algorithms by providing asymptotic tracking of time-varying input commands for a class of ***,simulation results of X-3 3 reentry vehicle model dynamic show the effectiveness of the reconfiguration approach developed in this study.

关键词： Actuator faults stuck fault-tolerant control(FTC) linear matrix inequalities(LMIs) reusable launch vehicle(RLV)

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optimization research of genetic neural network based on Scilab

Optimization research of genetic neural network based on Sci...

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2011 IEEE International Workshop on Open-Source Software for Scientific Computation, OSSC-2011

作者： Zhao, Baoyong Qi, Yingjian Tao, Xing School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China Science School Communication University of China Beijing 100024 China Beijing Research Center of Urban System Engineering Beijing 100089 China Key Laboratory of Advanced Control for Iron and Steel Process Ministry of Education China

ISBN: (纸本)9781612844930

Radial basis function (RBF) network is one of the significant neural networks. It has been used successfully in various fields. But in RBF network approximation algorithm, the initial value of the network weights, Gauss function center vector and broad-based vector is not easy to determine, and when these parameter choice is undeserved, RBF network approximation precision will decline and even the serious consequences of network spread will be produced. By using genetic algorithm in this paper, which can better realize RBF network parameter optimization, thereby increasing the accuracy of approximation. Scilab is open source software and has good simulation capabilities. Experiments using Scilab shows that the optimization method of genetic neural network is feasible and results are satisfied. © 2011 IEEE.

关键词： Genetic algorithms

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Streaming-Data-Driven Multi-Objective Optimal Operation for Ammonia-based Integrated Energy chemical Systems:An Event-Triggered Scheme

Streaming-Data-Driven Multi-Objective Optimal Operation for ...

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第42届中国控制会议

作者： Longyan Li Chao Ning Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology

As an important component in the industry sector,the integrated energy chemical system is inescapably responsible for carbon reduction in addition to economic and reliability *** propose a novel streaming-data-driven multi-objective optimal operation for ammonia-based integrated energy chemical systems（AIECS）.In the day ahead scheduling,a detailed mathematical model for AIECS is presented,upon which a multi-objective optimization considering cost,CO emission and reliability is *** the intra-day operation,an event-triggered mechanism is firstly developed in the real-time operation of AIECS,and it enables the AIECS to be risk-aware just in *** monitoring the difference between the predicted state of charge and the capacity limitations of battery,the AIECS identifies whether it is in hazardous ***,the intelligent switch between certainty equivalence model predictive control and online-learning based distributionally robust model predictive control is proposed,such that their respective advantages are *** studies demonstrate that the proposed approach guarantees the system safety,and brings good revenue.

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Multiple Model Predictive control with Undisturbed Switch for Wind Turbines System

Multiple Model Predictive Control with Undisturbed Switch fo...

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Asian control Conference

作者： Xianda Huang Tianhong Pan Zhengming Li Shihong Ding Tan Shuai School of Electrical & Information Engineering Jiangsu University Zhenjiang Jiangsu China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai PR China

ISBN: (纸本)9781509015740;9781509015733

The variable-speed, variable-pitch speed wind turbines are widely used in the wind-energy system. However, the fluctuation of power generation is serious because of the erratic speed of wind and the nonlinearity of the energy conversion systems (ECS). How to keep the ECS work well during the whole operating region is a challenge issue. In this paper, a multiple model predictive control (MMPC) using the state estimation is present to solve this issue. The whole operating region is divided into several sub-regions according to the wind's speed, in which several linear models and corresponding MPCs are constructed. The state variables of each local model are estimated by using the Kalman filter. A new switching criterion without perturbation is present to keep the MMPC works well at the different operating region switching. Considering the operating constraints, a quadratic programming procedure is used to calculate the optimal value of MMPC. Comparing the conventional PI controller, the proposed control achieves a good performance and reduces the fluctuation of power generation. Simulation results show the excellent performance of the present method.

关键词： Wind speed Generators Wind turbines Torque Switches Predictive control Wind energy

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Data-Driven Distributionally Robust Planning of Energy Hub Coupled with Carbon Capture Utilization and Storage Facilities

Data-Driven Distributionally Robust Planning of Energy Hub C...

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第42届中国控制会议

作者： Xutao Ma Chao Ning Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology

Toward carbon peaking and carbon neutrality goals in China, a transition from traditional fossil power to renewable energy becomes an imperative need. This paper aims to address the planning problem of a highly renewable-energy penetrated energy hub system, coupled with carbon capture facilities and downstream production processes of hydrogen and methanol,under the uncertainty of renewable power output. To this end, we propose a two-stage distributionally robust optimal planning model, where investment decisions are the first-stage variables and operation variables are determined at the second stage after the realization of uncertainty. In the proposed model, we utilize historical data samples to construct a strengthened ambiguity set that leverages both Wasserstein distance and moment information for a better characterization of renewable generation uncertainty. Moreover, to efficiently solve the proposed planning problem, we develop a simplified affine decision rule method in a general setting with both moment and Wasserstein ambiguity, and then apply it to reformulate the distributionally robust planning problem. The derived reformulation possesses the favorable property that its scale is free from the sample size, thus greatly reducing the computational complexity. Computational results validate the effectiveness of the proposed planning model and the computational efficiency of the solution methodology.

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A Transfer State Estimator for Uncertain Parameters and Noise Statistics ⁎

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IFAC-PapersOnLine 2024年第14期58卷 192-197页

作者： Shuang Gao Xiaoli Luan Biao Huang Shunyi Zhao Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Wuxi 214122 China Department of Chemical and Materials Engineering University of Alberta Edmonton AB T6G 1H9 Canada

This paper proposes a novel approach to tackle uncertainties in model parameters and noise statistics for state estimation. The proposed method leverages transfer learning to combine the strengths of the unbiased finite impulse response (UFIR) filter and the Kalman filter (KF), with UFIR serving as the source domain filter and KF as the target domain filter. To bolster the robustness of state estimation within the target domain, the proposed method transfers the predicted state probability density functions (pdfs) from UFIR and fine-tunes the error covariance of the KF filter to achieve seamless integration. Unlike conventional fusion techniques, this method avoids the need for UFIR’s error covariance, thus mitigating its adverse impact on estimation accuracy. We demonstrate the competitiveness of this transfer state estimator in handling parameter uncertainties through moving target tracking, showing superior performance compared to existing fusion methods for state estimation.

关键词： State estimation parameter uncertainty variational inference transfer learning

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Cooperative control of heterogeneous multi-agent systems via distributed adaptive output regulation under switching topology

Cooperative control of heterogeneous multi-agent systems via...

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Annual Conference of Industrial Electronics Society

作者： Ruohan Yang Hao Zhang Huaicheng Yan Fuwen Yang Department of Control Science and Engineering Tongji University Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China School of Engineering Griffith University Australia

A novel distributed adaptive output feedback control strategy is developed to solve the cooperative output regulation problem of heterogeneous general linear multi-agent systems(MASs) under switching topology. The proposed control strategy avoids using the minimal non-zero eigenvalue of Laplacian matrix when calculating gain matrix, and the communication topology is assumed to contain a directed spanning tree only frequently. It is shown that individual agents could track external signal asymptotically and achieve disturbance rejection. Ultimately, a simulation is presented to exemplify the effectualness of the main result.

关键词： Topology Switches Laplace equations Output feedback Eigenvalues and eigenfunctions Adaptive control

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Anti-windup Disturbance Rejection control Design for Sampled Systems with Output Delay and Asymmetric Actuator Saturation Constraint ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1349-1354页

作者： Xinpeng Geng Zhencai Wang Shoulin Hao Tao Liu Zoltan Kalman Nagy Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian 116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian 116024 China Davidson School of Chemical Engineering Purdue University West Lafayette Indiana 47907 United States

A novel anti-windup disturbance rejection control design is proposed for industrial sampled systems with output delay and asymmetric actuator saturation constraint. To deal with the asymmetric actuator saturation constraint as often encountered in engineering practice, the input constraint is equivalently transformed into a symmetric actuator saturation constraint for the convenience of control design. Based on the equivalent system description, a model-based extended state observer (MESO) is designed to simultaneously estimate the system state and disturbance, which becomes an anti-windup compensator when the actuator saturation occurs. In order to compensate for the delay mismatch in MESO, a generalized predictor is utilized to estimate the undelayed system output. Accordingly, a pole placement approach is given to design the feedback controller. A set-point pre-filter is designed to ensure no steady-state output tracking error, in terms of a desired transfer function for the set-point tracking. Based on the delay-dependent sector condition and generalized free-weighting-matrix (GFWM), a sufficient condition guaranteeing the stability of the closed-loop system is established in terms of linear matrix inequalities (LMIs). An illustrative example from the literature is used to demonstrate the effectiveness and advantage of the proposed control method.

关键词： Sampled systems Asymmetric actuator saturation Output delay Anti-windup design Extended state observer (ESO)

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A Novel Improved Grey Wolf optimization Algorithm for Numerical optimization and PID controller Design

A Novel Improved Grey Wolf Optimization Algorithm for Numeri...

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Data Driven control and Learning Systems (DDCLS)

作者： Tao Zhang Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Center of Electrical & Electronic Technology Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538626191

The grey wolf optimization (GWO) algorithm, one of the recently proposed bio-inspired algorithms, simulates the leadership hierarchy and hunting mechanism of grey wolves in nature. The GWO has a good performance in some optimization tasks, but its search capacity decreases with the increasing search scope and dimension. This paper proposes an improved GWO (IGWO) algorithm, in which Levy flight strategy and a sine cosine operator with adaptive step are incorporated to significantly improve the performance of the algorithm. The Levy flight strategy is used to strengthen the efficiency of global search. The adaptive sine cosine operator is introduced to improve the local search ability. Experimental results based on twenty unconstrained benchmark problems show the superiority of the proposed IGWO. Furthermore, the IGWO is utilized in PID controller design. The comparison results show that the IGWO algorithm is better than, or at least comparable to, other well-established swarm intelligence algorithms.

关键词： optimization Power system stability Sociology Statistics Prediction algorithms Particle swarm optimization Genetic algorithms

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Co-simulation research of autonomous landing control system

Co-simulation research of autonomous landing control system

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Chinese control Conference (CCC)

作者： Zhaoning Wang Shengxi Wu Xiangming Dun Xingsheng Gu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai Shanghai CN Research Institute of Robotics Shanghai Jiao Tong University Shanghai CN

In this paper, a control simulation of the autonomous landing process of a Vertical Take-Off and Landing (VTVL) Reusable Launch Vehicle (RLV) is proposed and we consider the effects of the inner liquid propellant sloshing, elastic vibration, disturbance force, disturbance torque and other complex conditions in the virtual RLV model. On the basis of dynamics modeling of the RLV, we analyzed RLV's landing process. The landing control system was designed under certain conditions. Co-simulation Research was achieved by ADAMS and MATLAB/Simulink. The simulation results show that the control system performs well.

关键词： Force control systems Data models Mathematical model Attitude control Angular velocity Equations

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