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Astrodynamics 2019年第2期3卷 137-153页

作者： Xinwei Wang Haijun Peng Department of Engineering Mechanics State Key Laboratory of Structural Analysis for Industrial EquipmentDalian University of TechnologyDalian 116024China

Accurate state estimations are perquisites of autonomous navigation and orbit maintenance *** extended Kalman lter(EKF)and the unscented Kalman lter(UKF),are the most commonly used ***,the EKF results in poor estimation performance for systems are with high *** for the UKF,irregular sampling instants are *** addition,both the EKF and the UKF cannot treat *** this paper,a symplectic moving horizon estimation algorithm,where constraints can be considered,for nonlinear systems are *** estimation problem to be solved at each sampling instant is seen as a nonlinear constrained optimal control *** original nonlinear problem is transferred into a series of linear-quadratic problems and solved iteratively.A symplectic method based on the variational principle is proposed to solve such linear-quadratic problems,where the solution domain is divided into sub-intervals,and state,costate,and parametric variables are locally interpolated with linear *** optimality conditions result in a linear complementarity problem which can be solved by the Lemke's method *** developed symplectic moving horizon estimation method is applied to the Earth-Moon L2 libration point *** numerical simulations demonstrate that though more time-consuming,the proposed method results in better estimation performance than the EKF and the UKF.

关键词： moving horizon estimation symplectic method quasilinearization variational principle L2 libration point navigation

Combined moving horizon estimation and Model Predictive Control for Main Steam Temperature System 36

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Combined Moving Horizon Estimation and Model Predictive Cont...

第36届中国控制会议

作者： Huaizhong Hu Yu Li Qingyu Yang Yuanli Cai Institute of Control Engineering Xi’an Jiaotong University

ISBN: (纸本)9781538629185

This paper considers a robust control strategy for main steam temperature system of thermal power plant that is affected by immeasurable bounded disturbances. An output-feedback min-max optimization approach is proposed to obtain a controller which could effectively reject disturbances and stabilize the system. This approach combines moving horizon estimation with model predictive control and is formulated into a min-max optimization. At each sampling time, the optimization criterion is maximized over worst-case estimate of disturbance sequence and minimized over optimal control sequence via a primal-dual interior-point method. In this way, the controller can improve robustness under constrained disturbances. Simulation results verify that the presented approach could provide significant anti-disturbance capability compared with a conventional DMC-PID strategy.

关键词： Main steam temperature moving horizon estimation model predictive control min-max optimization robust control

Decentralized moving horizon estimation for Networked Navigation System with packet dropouts

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Decentralized Moving Horizon Estimation for Networked Naviga...

第三十九届中国控制会议

作者： Shuai Liu Guorong Zhao Yunfeng He Chao Gao Coastal defence academy Naval Aviation University

This paper is concerned with state estimation for networked navigation system with packet dropouts. The packet dropout phenomenon is modeled by a stochastic variable satisfying the Bernoulli binary distribution, the predictor of the lost measurement is used as a compensator when packets dropout occur. At each local estimator, moving horizon strategy is applied to update the state, in which only cooperative packets and relative measurements over the most recent time horizon are used. Then the fusion estimator is obtained by applying the covariance intersection criterion. Finally, an illustrative example is given to demonstrate the efficiency of the proposed method.

关键词： moving horizon estimation Networked Navigation System Packet Dropouts Prediction Compensation

Temperature estimation of cement rotary kiln based on moving horizon estimation

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Temperature estimation of cement rotary kiln based on moving...

第40届中国控制会议

作者： Zhaogang LI Jianyu ZHAO Shi LI School of Control Science ＆ Engineering University of Jinan

In this paper,moving horizon estimation（MHE） is applied to the temperature estimation of cement rotary kiln calcination system.A mechanism model is established based on mass and energy ***,the nonlinear mechanism model is simplified and linearized to obtain a state space model,which is used in MHE *** results clarify that the moving horizon estimator can effectively reduce the estimation error of cement rotary kiln temperatures under different noise conditions.

关键词： moving horizon estimation mechanism model cement rotary kiln temperature estimation

Event-Triggered moving horizon Pose estimation for Spacecraft Systems

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Journal of Beijing Institute of Technology 2022年第4期31卷 382-390页

作者： Shuangxi Li Hengguang Zou Dawei Shi Junzheng Wang School of Automation Beijing Institute of TechnologyBeijing 100081China China Academy of Space Technology Beijing 100094China

An event-triggered moving horizon estimation strategy is proposed for spacecraft pose *** error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled *** order to reduce the energy consumption on spacecraft,an event-triggered moving horizon estimator(MHE)is designed for real-time pose estimation with limited communication *** model mismatch caused by event-triggered is finally solved by solving the cost function of the min-max optimization *** system simulation model is built in Matlab/Simulink,and the spacecraft pose estimation simulation is carried *** numerical results demonstrate that the designed estimator could ensure the estimation effect and save spacecraft communication and computing resources effectively.

关键词： state estimation pose estimation event-triggered moving horizon estimation

Optimization of β-L-glutamic Acid Crystallization Processes via moving horizon estimation

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Optimization of β-L-glutamic Acid Crystallization Processes...

第40届中国控制会议

作者： Wang Yao Yan Cui Tao Liu Feiran Sun Institute of Advanced Control Technology Dalian University of Technology

In this paper,a process optimization method is proposed for cooling crystallization process of β form L-glutamic acid,based on the moving horizon estimation（MHE） of the moment information of crystal growth *** transforming the population balance equations（PBEs） of the process kinetic model into differential algebraic equations using the quadrature method of moments（QMOM）,a modified MHE estimation algorithm with variable horizon is developed to estimate low-order moments reflecting the fundamental characteristics of cooling crystallization *** on these estimated moments,an optimization program is established to solve the optimal operation profile of cooling temperature,by imposing the constraints of moment and cooling rate for numerical *** illustrative example of seeded cooling crystallization process of β-LGA is studied,which demonstrates that the proposed MHE algorithm could obtain better accuracy compared to the classical state estimation methods of extended Kalman filter（EKF） and ***,the optimized result of target crystal size distribution（CSD） by the proposed method is significantly better than those of the conventional linear or programming cooling strategies in practice.

关键词： Process Optimization State estimation Population Balance Model moving horizon estimation

Cloud-Based Optimal Control of Individual Borehole Heat Exchangers in a Geothermal Field

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Journal of Thermal Science 2022年第5期31卷 1253-1265页

作者： STOFFEL Phillip KÜMPEL Alexander MÜLLER Dirk RWTH Aachen University E.ON Energy Research CenterInstitute for Energy Efficient Buildings and Indoor Climate52074 AachenGermany

Integrating renewable energy sources is a crucial component in reducing CO_(2) emissions in the building sector. In particular, shallow geothermal energy is expected to play a significant role in the regenerative energy supply of buildings. An effective control strategy for the geothermal field is crucial to reduce the overall energy consumption. This paper analyzes the benefits of controlling an existing field’s individual borehole heat exchangers(BHE) using nonlinear model predictive control(NMPC) and moving horizon estimation. The considered geothermal field consists of 41 BHEs and is used for heating and cooling. Each BHE is equipped with temperature sensors for in-and outflow and has individually controllable valves, while a central hydraulic pump feeds all BHEs. The sensor measurements are accessed through a cloud platform, enabling also set point writing for the pump speed and the valve positions. To control the BHEs individually, we propose a two-stage process. In the calibration stage, a moving horizon estimator estimates the actual borehole and ground temperatures for each BHE. In the second stage, first, a nonlinear model predictive controller optimizes the number of active BHEs necessary to meet the buildings’ energy demand. With the estimated ground temperatures as a basis, it is determined which BHEs shall be(de)-activated. The active BHEs are fed with a fixed volume flow of 24 L/min to ensure turbulent heat transfer. To reduce the power usage of the pumps, an optimal control problem based on a simple hydraulic model of the geothermal field is used. The methodology is analyzed through simulations first and then validated experimentally. The results show that half or more of the BHEs could be deactivated most of the time, leading to 67% savings in electricity consumption by the hydraulic pump. The experimental validation confirms the high energy saving potential of the proposed methodology, reducing the consumption of electrical energy by 71%. Additiona

关键词： geothermal energy moving horizon estimation model predictive control operation optimization optimal control

Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm

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International Journal of Automation and computing 2007年第2期4卷 183-188页

作者： Ling-Lai Li Dong-Hua Zhou Ling Wang Department of Automation Tsinghua University Beijing 100084 PRC

Fault diagnosis of nonlinear systems is of great importance in theory and practice, and the parameter estimation method is an effective strategy. Based on the framework of moving horizon estimation, fault parameters are identified by a proposed intelligent optimization algorithm called PSOSA, which could avoid premature convergence of standard particle swarm optimization （PSO） by introducing the probabilistic jumping property of simulated annealing （SA）. Simulations on a three-tank system show the effectiveness of this optimization based fault diagnosis strategy.

关键词： Fault diagnosis nonlinear systems moving horizon estimation particle swarm optimization(PSO).

Characteristics Extraction of Vehicle State Information Based on Entropy Calculation

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Journal of Beijing Institute of Technology 2020年第2期29卷 232-240页

作者： Zepeng Gao Zheng Liu Sizhong Chen Hongbin Ren Zechao Li Yong Chen Automobile Research Institute School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China

A method of extracting and detecting vehicle stability state characteristics based on entropy is *** vehicle’s longitudinal and lateral dynamics models are established for complex driving and maneuver *** corresponding state observer is designed by adopting the moving horizon estimation algorithm,which realizes the observation of the vehicle stability state considering the global state ***,the Shannon entropy is modified to approximate entropy,and the approximate entropy value of the observed vehicle state is ***,the optimal controller is designed to further validate the reliability of the entropy value as the reference of control *** results demonstrate that this method can quickly detect the instability state of the system during the process of vehicle driving,which provides a reference for risk prediction and active control.

关键词： vehicle stability state state observer moving horizon estimation Shannon entropy approximate entropy

Distributed State estimation of FCCU Riser Temperature 36

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Distributed State Estimation of FCCU Riser Temperature

第36届中国控制会议

作者： Li Mengying Zheng Yi Li Shaoyuan Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education

ISBN: (纸本)9781538629185

The temperature of riser reactor plays an important role in the operation and control of fluid catalytic cracking unit（FCCU）. However, the FCCU riser only has limit temperature sensors. In this paper, a distributed state observer strategy is proposed to estimate temperature distribution of the whole riser. Based on moving horizon estimation（MHE）, this paper presents a simplified MHE scheme for differential-algebraic systems that is applied to each observer that are combined together to form a large distributed state observer. The simulation results show that the distributed state observer works well and is able to estimation the temperature distribution.

关键词： state observer moving horizon estimation differential-algebraic equations riser reactor of fluid catalytic cracking unit