Filters








17,160 Hits in 10.4 sec

Robust Explicit Moving Horizon Control and Estimation: A Batch Polymerization Case Study

Dan Sui, Le Feng, Morten Hovd
2009 Modeling, Identification and Control  
This paper focuses on the design and evaluation of a robust explicit moving horizon controller and a robust explicit moving horizon estimator for a batch polymerization process.  ...  applicability to a case with industrially relevant complexity.  ...  Acknowledgment This work is supported by European project "Design of Advanced Controllers for Economic, Robust and Safe Manufacturing Performance (CONNECT)".  ... 
doi:10.4173/mic.2009.1.2 fatcat:jjl4auzlu5gqfdhk5xzvjr6oym

Finite-Horizon Robust Kalman Filter for Uncertain Attitude Estimation System with Star Sensor Measurement Delays

Hua-Ming Qian, Wei Huang, Biao Liu
2014 Abstract and Applied Analysis  
This paper addresses the robust Kalman filtering problem for uncertain attitude estimation system with star sensor measurement delays.  ...  Therefore, a finite-horizon robust Kalman filter is proposed to cope with this question.  ...  Based on the above discussion, a finite-horizon robust Kalman filter is proposed for uncertain attitude estimation system with star sensor delays.  ... 
doi:10.1155/2014/494060 fatcat:na7hlvilhnam3mlkxo6nyvrkqq

Model predictive control based on finite impulse response models

Guru Prasath, John Bagterp Jorgensen
2008 2008 American Control Conference  
The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC. Westin Seattle Hotel,  ...  We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter.  ...  The closed-loop performance can also be improved by adopting a FIR based moving horizon estimator instead of the simple estimator used in this paper.  ... 
doi:10.1109/acc.2008.4586531 dblp:conf/amcc/PrasathJ08 fatcat:og246nt2kbdubp6rajk22f2mpa

2013 Index IEEE Transactions on Automatic Control Vol. 58

2013 IEEE Transactions on Automatic Control  
D., +, TAC March 2013 667-681 Moving Horizon Estimation for Large-Scale Interconnected Systems.  ...  ., +, TAC Oct. 2013 2536-2549 Moving Horizon Estimation for Large-Scale Interconnected Systems.  ... 
doi:10.1109/tac.2013.2295962 fatcat:3zpqog4r4nhoxgo4vodx4sj3l4

Page 9813 of Mathematical Reviews Vol. , Issue 2003m [page]

2003 Mathematical Reviews  
for nonlinear discrete-time systems: stability and moving horizon approximations.  ...  State estimation of discrete-time nonlinear systems, with inequality constraints on the state and disturbances, is considered. A moving horizon type on line algorithm is proposed.  ... 

Soft Constraints for Robust MPC of Uncertain Systems

Guru Prasath, John Bagterp Jørgensen
2009 IFAC Proceedings Volumes  
In this paper we develop a robust constrained predictive controller for linear systems.  ...  The controller is equipped with soft output constraints that are used in a novel way to have robustness against model plant mismatch.  ...  ( 2 b ) v k ∼ N iid (0, R) ( 2 c ) The measured output, y, is the signal available for feedback and used by the estimator. u is the signal generated by the control system and implemented on the plant.  ... 
doi:10.3182/20090712-4-tr-2008.00034 fatcat:ammyebrmlnalpk72dmrsnyvxuq

Moving Horizon Estimation for Networked Systems With Quantized Measurements and Packet Dropouts

Andong Liu, Li Yu, Wen-An Zhang, Michael Z. Q. Chen
2013 IEEE Transactions on Circuits and Systems Part 1: Regular Papers  
This paper is concerned with the moving horizon estimation (MHE) problem for linear discrete-time systems with limited communication, including quantized measurements and packet dropouts.  ...  Index Terms-Moving horizon estimation (MHE), networked systems, packet dropout, quantization.  ...  ACKNOWLEDGMENT The authors would like to thank the Associate Editor and the anonymous reviewers for their constructive suggestions and comments, which are very valuable for improving the quality of the  ... 
doi:10.1109/tcsi.2012.2226499 fatcat:nvyomwqi2vcz7dgorfkpisj7li

Model predictive control: past, present and future

Manfred Morari, Jay H. Lee
1999 Computers and Chemical Engineering  
Among the broader research needs the following areas are identified: multivariable system identification, performance monitoring and diagnostics, non-linear state estimation, and batch system control.  ...  Much progress has been made on these issues for non-linear systems but for practical applications many questions remain, including the reliability and efficiency of the on-line computation scheme.  ...  We wish to thank Alberto Bemporad for his assistance in preparing the paper, and Tom Badgwell and Alex Zheng for their helpful reviews.  ... 
doi:10.1016/s0098-1354(98)00301-9 fatcat:4cri3rcjobdjpd4zmfgfcxmcci

Chance-constrained model predictive control

Alexander T. Schwarm, Michael Nikolaou
1999 AIChE Journal  
This work focuses on robustness of model predictive control (MPC) with respect to satisfaction of process output constraints. A method of improving such robustness is presented.  ...  Suggestions for further improvements are made.  ...  ., Texas A&M University for sharing their chance-constrained optimization experience with the authors.  ... 
doi:10.1002/aic.690450811 fatcat:yxb5hyv7t5hsxcvkzvfrin7vcu

Scanning the Issue*

2019 IEEE Transactions on Automatic Control  
The authors construct a robust stealthy attack that compromises uncertain cyberphysical systems having unstable zeros.  ...  of the measured output.  ...  possible to design observers for linear, time-invariant systems by feeding classical linear observers with the successive integrals and the moving average of the measured output.  ... 
doi:10.1109/tac.2019.2952442 fatcat:wnfzvd3zdfcaho65j2agb662fi

Simulation-based optimal tuning of model predictive control policies for supply chain management using simultaneous perturbation stochastic approximation

J.D. Schwartz, D.E. Rivera
2006 2006 American Control Conference  
The results of the optimization on a singleechelon system show that it is advantageous to act cautiously to forecasted information and gradually become more aggressive (with respect to factory starts)  ...  For a three-echelon problem, the results of the optimization demonstrate that safety stock levels can be significantly reduced and financial benefit gained while maintaining robust operation in the supply  ...  For this case study, both demand and supply (factory output) are uncertain.  ... 
doi:10.1109/acc.2006.1655415 fatcat:iv2tgahtkjbv3cchfbiwmbzwey

Robust output feedback model predictive control for linear systems via moving horizon estimation

D. Sui, L. Feng, M. Hovd
2008 2008 American Control Conference  
Index Terms-Model predictive control; Moving horizon estimation; Constrained linear systems with bounded disturbances.  ...  This paper provides a simple approach to the problem of robust output feedback model predictive control (MPC) for linear systems with state and input constraints, subject to bounded state disturbances  ...  This paper considers the problem of robust output feedback MPC for linear systems with state and input constraints, subject to bounded state disturbances and output measurement errors.  ... 
doi:10.1109/acc.2008.4586533 dblp:conf/amcc/SuiFH08 fatcat:ulkl3weq5ze57b74lji2ocqawi

Page 6498 of Mathematical Reviews Vol. , Issue 2003h [page]

2003 Mathematical Reviews  
horizon estimation for hybrid systems.  ...  By exploiting the equivalence between hybrid systems modeled by mixed logical dynamical systems and piecewise affine systems, a state-smoothing algorithm based on moving-horizon estimation is proposed.  ... 

Towards In-Field and Online Calibration of Inertial Navigation Systems using Moving Horizon Estimation

Fabian Girrbach, Raymond Zandbergen, Manon Kok, Tijmen Hageman, Giovanni Bellusci, Moritz Diehl
2019 2019 18th European Control Conference (ECC)  
By adopting a moving horizon scheme, the resulting estimator has the potential to run on embedded hardware allowing for online calibration without sacrificing robustness.  ...  The evaluated statistics clearly show that moving horizon estimation improves the robustness and accuracy of the presented calibration approach in the presence of uncertain initial conditions and outperforms  ...  Hol for his advise and guidance during his time at Xsens Technologies B.V..  ... 
doi:10.23919/ecc.2019.8796310 dblp:conf/eucc/GirrbachZKHBD19 fatcat:csczqfbylzgo5mkkzdpi4vmd4i

Robust Control Framework Based on Input-Output Models Enhanced with Uncertainty Estimation

Mariana RODRIGUEZ-JARA, Hilario FLORES-MEJIA, Alejandra VELASCO-PEREZ, Hector PUEBLA
2021 Studies in Informatics and Control  
Three robust model-based control schemes are then formulated based on the enhanced simple input-output model.  ...  The proposed control framework departs from a simple low-order model which is enhanced by estimating model uncertainties due to model reduction, uncertain model parameters, and external disturbances.  ...  Finally, robustness properties of the closed-loop system are provided by the estimation and cancelation of uncertain terms in each control design.  ... 
doi:10.24846/v30i1y202109 fatcat:f6ssqt5xivcvnako55py3boquu
« Previous Showing results 1 — 15 out of 17,160 results