Real-Time Optimal State Estimation of Multi-DOF Industrial Systems Using FIR Filtering

Industrial processes are often organized using mechanical systems with multiple degrees-of-freedom (DOF). For real-time operation of such systems in noise environments, fast, optimal, and robust estimators are required. In this paper, information gathering about multi-DOF system states is provided using the optimal finite impulse response (OFIR) filter. To use this filter in real time, a fast iterative algorithm is developed with a pseudocode available for immediate use. Although the iterative algorithm utilizes Kalman recursions, it is more robust against uncertainties and model errors owing to the transversal structure. We use this algorithm to estimate state in the 1-DOF torsion system and the 3-DOF helicopter system.

[1]  Wook Hyun Kwon,et al.  Minimum Variance FIR Smoothers for Discrete-Time State Space Models , 2007, IEEE Signal Processing Letters.

[2]  Yu Cao,et al.  State Space System Identification of 3-Degree-of-Freedom (DOF) Piezo-Actuator-Driven Stages with Unknown Configuration , 2013 .

[3]  G. Goodwin,et al.  Riccati equations in optimal filtering of nonstabilizable systems having singular state transition matrices , 1986 .

[4]  Wook Hyun Kwon,et al.  $cal H_infty$FIR Filters for Linear Continuous-Time State–Space Systems , 2006, IEEE Signal Processing Letters.

[5]  L. B. Weiner Kalman Filter Initialization With Large Initial Uncertainty And Strong Measurement Nonlinearity , 1981 .

[6]  Vijay Kumar,et al.  Cooperative manipulation and transportation with aerial robots , 2009, Auton. Robots.

[7]  Georg Fuchs,et al.  Application of the Modern Taylor Series Method to a multi-torsion chain , 2013, Simul. Model. Pract. Theory.

[8]  Yuriy S. Shmaliy GPS-Based Optimal FIR Filtering of Clock Models , 2013 .

[9]  Peter Willett,et al.  A Low-Complexity Sliding-Window Kalman FIR Smoother for Discrete-Time Models , 2010, IEEE Signal Processing Letters.

[10]  Fei Liu,et al.  Minimum variance unbiased FIR filter for discrete time-variant systems , 2015, Autom..

[11]  Dan Simon,et al.  Iterative unbiased FIR state estimation: a review of algorithms , 2013, EURASIP J. Adv. Signal Process..

[12]  Pyung-Soo Kim,et al.  A New FIR Filter for State Estimation and Its Application , 2007, Journal of Computer Science and Technology.

[13]  A. Jazwinski Limited memory optimal filtering , 1968 .

[14]  Wook Hyun Kwon,et al.  A receding horizon Kalman FIR filter for discrete time-invariant systems , 1999, IEEE Trans. Autom. Control..

[15]  Yuriy S. Shmaliy,et al.  Time‐variant linear optimal finite impulse response estimator for discrete state‐space models , 2012 .

[16]  Yuriy S. Shmaliy,et al.  Accurate Self-Localization in RFID Tag Information Grids Using FIR Filtering , 2014, IEEE Transactions on Industrial Informatics.

[17]  Fei Liu,et al.  Unbiased, optimal, and in-betweens: the trade-off in discrete finite impulse response filtering , 2016, IET Signal Process..

[18]  Ian R. Petersen,et al.  Robustness and risk-sensitive filtering , 2002, IEEE Trans. Autom. Control..

[19]  Syed Ali Jafar,et al.  Interference Alignment and Degrees of Freedom of the $K$-User Interference Channel , 2008, IEEE Transactions on Information Theory.

[20]  Paul Reynolds,et al.  Modal Testing and Finite-Element Model Updating of a Lively Open-Plan Composite Building Floor , 2007 .

[21]  Choon Ki Ahn New Quasi-Deadbeat FIR Smoother for Discrete-Time State-Space Signal Models: An LMI Approach , 2008, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[22]  Wook Hyun Kwon,et al.  FIR Filters for Linear Continuous-Time , 2006 .

[23]  Ji-Woong Choi,et al.  An FIR Channel Estimation Filter with Robustness to Channel Mismatch Condition , 2008, IEEE Transactions on Broadcasting.

[24]  W. Kwon,et al.  Receding Horizon Control: Model Predictive Control for State Models , 2005 .

[25]  Wen-Yan Chang,et al.  Visual Tracking in High-Dimensional State Space by Appearance-Guided Particle Filtering , 2008, IEEE Transactions on Image Processing.

[26]  Yuriy S. Shmaliy,et al.  An Iterative Kalman-Like Algorithm Ignoring Noise and Initial Conditions , 2011, IEEE Transactions on Signal Processing.

[27]  Yuriy S. Shmaliy,et al.  Unbiased FIR Filtering of Discrete-Time , 2009 .

[28]  Fei Liu,et al.  Fast Computation of Discrete Optimal FIR Estimates in White Gaussian Noise , 2015, IEEE Signal Processing Letters.

[29]  Yuriy S. Shmaliy,et al.  Suboptimal FIR Filtering of Nonlinear Models in Additive White Gaussian Noise , 2012, IEEE Transactions on Signal Processing.

[30]  Visa Koivunen,et al.  Detection and Tracking of MIMO Propagation Path Parameters Using State-Space Approach , 2009, IEEE Transactions on Signal Processing.

[31]  Pedro Albertos,et al.  A new dead-time compensator to control stable and integrating processes with long dead-time , 2008, Autom..

[32]  Kouhei Ohnishi,et al.  Multi-DOF Micro-Macro Bilateral Controller Using Oblique Coordinate Control , 2011, IEEE Transactions on Industrial Informatics.

[33]  Gregory Faraut,et al.  Formal Approach to Multimodal Control Design: Application to Mode Switching , 2009, IEEE Transactions on Industrial Informatics.

[34]  A. Jazwinski Stochastic Processes and Filtering Theory , 1970 .

[35]  Wook Hyun Kwon,et al.  A receding horizon unbiased FIR filter for discrete-time state space models , 2002, Autom..

[36]  Josep M. Guerrero,et al.  Industrial Applications of the Kalman Filter: A Review , 2013, IEEE Transactions on Industrial Electronics.

[37]  Yuriy S. Shmaliy,et al.  Linear Optimal FIR Estimation of Discrete Time-Invariant State-Space Models , 2010, IEEE Transactions on Signal Processing.

[38]  Keck Voon Ling,et al.  Receding horizon recursive state estimation , 1999, IEEE Trans. Autom. Control..

[39]  Myo-Taeg Lim,et al.  Improving Reliability of Particle Filter-Based Localization in Wireless Sensor Networks via Hybrid Particle/FIR Filtering , 2015, IEEE Transactions on Industrial Informatics.

[40]  Alexander L. Fradkov,et al.  Adaptive Control of 3DOF Motion for LAAS Helicopter Benchmark: Design and Experiments , 2007, 2007 American Control Conference.

[41]  Leonid Mirkin,et al.  L2 Optimization in Discrete FIR Estimation: Exploiting State-Space Structure , 2013, SIAM J. Control. Optim..