State Estimation Using Non-uniform and Delayed Information: A Review

The study and application of methods for incorporating nonuniform and delayed information in state estimation techniques are important topics to advance in soft sensor development.Therefore, this paper presents a review of these methods and proposes a taxonomy that allows a faster selection of state estimator in this type of applications. The classification is performed according to the type of estimator, method, and used tool. Finally, using the proposed taxonomy, some applications reported in the literature are described.

[1]  Harold L. Alexander,et al.  State estimation for distributed systems with sensing delay , 1991, Defense, Security, and Sensing.

[2]  Jing Zhang,et al.  Observer-enhanced distributed moving horizon state estimation subject to communication delays , 2014 .

[3]  Roberto Sanchis,et al.  State estimator for multisensor systems with irregular sampling and time-varying delays , 2012, Int. J. Syst. Sci..

[4]  Masoud Soroush,et al.  Multirate nonlinear state estimation with application to a polymerization reactor , 1999 .

[5]  Yuanqing Xia,et al.  State estimation for asynchronous multirate multisensor dynamic systems with missing measurements , 2010 .

[6]  S. Andrew Gadsden,et al.  Gaussian filters for parameter and state estimation: A general review of theory and recent trends , 2017, Signal Process..

[7]  John B. Moore,et al.  Optimal State Estimation , 2006 .

[8]  B. W. Bequette,et al.  Behavior of a CSTR with a recirculating jacket heat transfer system , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[9]  Yeng Chai Soh,et al.  Filtering for networked control systems with single/multiple measurement packets subject to multiple-step measurement delays and multiple packet dropouts , 2011, Int. J. Syst. Sci..

[10]  Tao Yu,et al.  Nonlinear state estimation for fermentation process using cubature Kalman filter to incorporate delayed measurements , 2015 .

[11]  Wang Min.  Survey of sequence measurement filtering algorithm , 2012 .

[12]  Piyapong Niamsup,et al.  Robust Finite-time H∞ Control of Linear Time-varying Delay Systems with Bounded Control via Riccati Equations , 2018, Int. J. Autom. Comput..

[13]  Jing Ma,et al.  Multi-sensor distributed fusion estimation with applications in networked systems: A review paper , 2017, Inf. Fusion.

[14]  S. Żak,et al.  Comparative study of non-linear state-observation techniques , 1987 .

[15]  A. Juloski,et al.  Two approaches to state estimation for a class of piecewise affine systems , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[16]  O. J. M. Smith,et al.  A controller to overcome dead time , 1959 .

[17]  Niket S. Kaisare,et al.  Incorporating delayed and infrequent measurements in Extended Kalman Filter based nonlinear state estimation , 2011 .

[18]  P. T. Nam,et al.  Partial state estimation for linear systems with output and input time delays. , 2014, ISA transactions.

[19]  Alfredo Germani,et al.  A Chain Observer for Nonlinear Systems with Multiple Time-Varying Measurement Delays , 2014, SIAM J. Control. Optim..

[20]  Magdi S. Mahmoud,et al.  State estimation with asynchronous multi-rate multi-smart sensors , 2012, Inf. Sci..

[21]  YALI DONG,et al.  Observer design for nonlinear systems with interval time-varying delay , 2014 .

[22]  Alfredo Germani,et al.  Filtering Continuous-Time Linear Systems With Time-Varying Measurement Delay , 2015, IEEE Transactions on Automatic Control.

[23]  Sirish L. Shah,et al.  Nonlinear Bayesian state estimation: A review of recent developments , 2012 .

[24]  S Lee.  Observer for discrete-time Lipschitz non-linear systems with delayed output , 2011 .

[25]  Jingcheng Wang,et al.  Reset observers for linear time-varying delay systems: Delay-dependent approach , 2014, J. Frankl. Inst..

[26]  Panagiotis D. Christofides,et al.  Lyapunov-Based Model Predictive Control of Nonlinear Systems Subject to Data Losses , 2007, IEEE Transactions on Automatic Control.

[27]  Rudolph van der Merwe,et al.  Sigma-point kalman filters for probabilistic inference in dynamic state-space models , 2004 .

[28]  Niels Kjølstad Poulsen,et al.  Incorporation of time delayed measurements in a discrete-time Kalman filter , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[29]  Alireza Khosravian,et al.  State estimation for invariant systems on Lie groups with delayed output measurements , 2016, Autom..

[30]  Jing Zeng,et al.  Distributed moving horizon state estimation: Simultaneously handling communication delays and data losses , 2015, Syst. Control. Lett..

[31]  Juan Diego Sanchez-Torres,et al.  A Soft Sensor for Biomass in a Batch Process with Delayed Measurements , 2016 .

[32]  Biao Huang,et al.  State estimation incorporating infrequent, delayed and integral measurements , 2015, Autom..

[33]  Biao Huang,et al.  Development of soft sensor by incorporating the delayed infrequent and irregular measurements , 2014 .

[34]  Tyrone Fernando,et al.  Design of distributed functional observers for interconnected time-delay systems , 2013, 2013 IEEE 8th International Conference on Industrial and Information Systems.

[35]  Alfredo Germani,et al.  A new approach to state observation of nonlinear systems with delayed output , 2002, IEEE Trans. Autom. Control..

[36]  Denis Dochain,et al.  Review and classification of recent observers applied in chemical process systems , 2015, Comput. Chem. Eng..

[37]  Jay H. Lee,et al.  Receding Horizon Recursive State Estimation , 1993, 1993 American Control Conference.

[38]  Xionglin Luo,et al.  A novel calibration approach of soft sensor based on multirate data fusion technology , 2010 .

[39]  Nikolaos Kazantzis,et al.  Nonlinear observer design in the presence of delayed output measurements , 2005, Syst. Control. Lett..

[40]  Petros G. Voulgaris,et al.  On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..

[41]  L. Biegler,et al.  A Moving Horizon Estimator for processes with multi-rate measurements: A Nonlinear Programming sensitivity approach , 2012 .

[42]  Denis Dochain,et al.  State and parameter estimation in chemical and biochemical processes: a tutorial , 2003 .

[43]  Tianhong Pan,et al.  Recursive Bayesian Algorithm for Identification of Systems with Non-uniformly Sampled Input Data , 2017, International Journal of Automation and Computing.

[44]  C. Vasseur,et al.  Piecewise continuous hybrid systems based observer design for linear systems with variable sampling periods and delay output , 2015, Signal Process..

[45]  Alireza Khosravian,et al.  State estimation for nonlinear systems with delayed output measurements , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[46]  James B. Rawlings,et al.  Application of MHE to large-scale nonlinear processes with delayed lab measurements , 2015, Comput. Chem. Eng..

[47]  B. Bequette,et al.  Product property and production rate control of styrene polymerization , 2002 .

[48]  Mehdi Shahbazian,et al.  Comparison of Adaptive Kalman Filter Methods in State Estimation of a Nonlinear System Using Asynchronous Measurements , 2009 .

[49]  Yuanqing Xia,et al.  State estimation for asynchronous multirate multisensor nonlinear dynamic systems with missing measurements , 2012 .

[50]  Bart De Schutter,et al.  Observers for linear distributed-parameter systems: A survey , 2011, 2011 IEEE International Symposium on Robotic and Sensors Environments (ROSE).

[51]  Maamar Bettayeb,et al.  Multi-sensor Data Fusion for Wheelchair Position Estimation with Unscented Kalman Filter , 2017, International Journal of Automation and Computing.

[52]  Isaac Horowitz,et al.  Synthesis of a non-linear feedback system with significant plant-ignorance for prescribed system tolerances† , 1974 .

[53]  Robert E. Mahony,et al.  Recursive attitude estimation in the presence of multi-rate and multi-delay vector measurements , 2015, 2015 American Control Conference (ACC).