Download or read book Estimating Disturbance Covariances from Data for Improved Control Performance written by Brian J. Odelson and published by . This book was released on 2003 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data based Techniques to Improve State Estimation in Model Predictive Control written by Murali R. Rajamani and published by . This book was released on 2007 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimation of Noise Covariances and Disturbance Structure from Data Using Least Squares with Optimal Weighting written by Murali R. Rajamani and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Development of a Technique for Estimating Noise Covariances Using Multiple Observers written by W. Thomas Bundick and published by . This book was released on 1988 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book MPC Performance Monitoring and Disturbance Model Identification written by and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although model predictive control (MPC) has been widely implemented in industry, no systematic method exists to assess if MPC controllers are performing optimally or to monitor their performance over time. We address this problem by proposing a benchmark called the key performance index (KPI), which is the expectation of the stage cost. For the linear, unconstrained case, the stage cost is a quadratic form of a normal variable and therefore has a generalized chi-squared distribution. The plant KPI is the time average of the stage cost and therefore has a normal distribution. We derive formulas for the mean and variance of the stage cost and plant KPI. Calculation of the KPI (as well as estimator design) requires an accurate disturbance model. The standard autocovariance least squares (ALS) methods, which estimate the disturbance covariances from data, are not easily applicable to industrial systems with large-dimensional models, which often contain poorly observable states. The covariance estimates also may have a large variance, since the original ALS formulation weights the least squares problem with the identity matrix. We overcome these challenges by reducing the model to contain only the necessary observable states and using a feasible generalized least squares technique to estimate the optimal weighting from data. Application of the improved ALS method to an industrial data set demonstrates that these improvements reduce the computational time and produce more reliable estimates as compared to the original ALS method. As an alternative to the ALS method, a maximum likelihood estimation (MLE) method is proposed; this method eliminates the need to estimate the optimal weighting. Instead, the process and measurement noise covariances are estimated by maximizing the probability of observing the measured outputs. Thus this optimization problem has a more sound theoretical basis. Sufficient conditions for the existence of an MLE solution are given. The conditions for uniqueness are compared to those of the ALS method. Although the computational burden is large compared to the ALS method, the MLE method was applied to several small-scale examples and shown to maximize the likelihood compared to the ALS method
Download or read book Kalman Filters written by Ginalber Luiz Serra and published by BoD – Books on Demand. This book was released on 2018-02-21 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Covariance Estimation from Limited Data written by Ian Tomeo and published by . This book was released on 2018 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: "There are many different methods of filtering that have been known to provide better results than basic Sample-Matrix-Inversion (SMI). Providing a well-conditioned covariance matrix to these filters will provide a higher Signal to Interference plus Noise Ratio (SINR) than SMI filtering when there are large numbers of receiver element and interference signals. The available number of coherent snapshots that will be used for filter estimation is “not large enough” with respect to the array dimensionality. Common techniques to deal with this situation is to use Krylov or Singular Value Decomposition (SVD) reduced rank filtering. Auxiliary Vector (AV) filtering with the CV-MOV and J Divergence methods of choosing a termination index is improved upon by the hybrid estimation technique JMOV. When the Signal to Noise Ratio (SNR) is below 0 [dB] the signal of interest is buried in noise and estimation of the total number of signals present in a system is poor. If we fix the eigenvalues to be constant for eigenvectors that are not thought to correspond to signals, we use the eigenvector information that we have already went through the effort of performing SVD for. Sometimes the Eigenvalue Fixing (EIF) filtering produces better results than reduced rank filtering alone. The performance of the aforementioned filters when utilizing modern covariance matrix estimates is analyzed by varying parameters of the system model."--Abstract.
Download or read book Improving Disturbance Rejection by Using Disturbance Estimator written by Damir Vrancic and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main tasks of control in various industries are either tracking the setpoint changes or rejecting the process disturbances. While both aim at maintaining the process output at the desired setpoint, the controller parameters optimised for setpoint tracking are generally not suitable for optimal disturbance rejection. The overall control performance can be improved to some extent by using simpler 2-DOF PID controllers. Such a controller structure allows the disturbance rejection to be optimised, while it also improves the setpoint tracking performance with additional controller parameters (usually through the setpoint weighting factors). Since such 2-DOF structures are usually relatively simple, the optimization of tracking performance is usually limited to the reduction of process overshoots instead of achieving an optimal (fast) tracking response. In this chapter, an alternative approach is presented in which the parameters of the PID controller are optimised for reference tracking, while the performance of the disturbance rejection is substantially increased by introducing a simple disturbance estimator approach. The mentioned estimator requires adding two simple blocks to the PID controller. The blocks are the second-order transfer functions whose parameters, including the PID controller parameters, can be calculated analytically from the process characteristic areas (also called process moments). The advantage of such an approach is that the mentioned areas can be analytically calculated directly from the process transfer function (of any order with time delay) or from the time response of the process when the steady state of the process is changed. Both of the above calculations are absolutely equivalent. Moreover, the output noise of the controller is under control as it is considered in the design of the controller and compensator. The closed loop results on several process models show that the proposed method with disturbance estimator has excellent tracking and disturbance rejection performance. The proposed controller structure and tuning method also compare favourably with some existing methods based on non-parametric description of the process.
Download or read book Development of a Technique for Estimating Noise Covariances Using Multiple Observers written by W. Thomas Bundick and published by . This book was released on 1988 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal State Estimation for Process Monitoring Fault Diagnosis and Control written by Ch. Venkateswarlu and published by Elsevier. This book was released on 2022-01-31 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines. - Describes various classical and advanced versions of mechanistic model based state estimation algorithms - Describes various data-driven model based state estimation techniques - Highlights a number of real applications of mechanistic model based and data-driven model based state estimators/soft sensors - Beneficial to those associated with process monitoring, fault diagnosis, online optimization, control and related areas
Download or read book Control Performance Management in Industrial Automation written by Mohieddine Jelali and published by Springer Science & Business Media. This book was released on 2012-10-31 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control Performance Management in Industrial Automation provides a coherent and self-contained treatment of a group of methods and applications of burgeoning importance to the detection and solution of problems with control loops that are vital in maintaining product quality, operational safety, and efficiency of material and energy consumption in the process industries. The monograph deals with all aspects of control performance management (CPM), from controller assessment (minimum-variance-control-based and advanced methods), to detection and diagnosis of control loop problems (process non-linearities, oscillations, actuator faults), to the improvement of control performance (maintenance, re-design of loop components, automatic controller re-tuning). It provides a contribution towards the development and application of completely self-contained and automatic methodologies in the field. Moreover, within this work, many CPM tools have been developed that goes far beyond available CPM packages. Control Performance Management in Industrial Automation: · presents a comprehensive review of control performance assessment methods; · develops methods and procedures for the detection and diagnosis of the root-causes of poor performance in complex control loops; · covers important issues that arise when applying these assessment and diagnosis methods; · recommends new approaches and techniques for the optimization of control loop performance based on the results of the control performance stage; and · offers illustrative examples and industrial case studies drawn from – chemicals, building, mining, pulp and paper, mineral and metal processing industries. This book will be of interest to academic and industrial staff working on control systems design, maintenance or optimisation in all process industries.
Download or read book An Analysis of Covariance Estimation Codeword Feedback and Multiple Base Performance of Interference Avoidance written by David E. Tabora and published by . This book was released on 2003 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Structures written by David Wagg and published by John Wiley & Sons. This book was released on 2008-04-09 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive structures have the ability to adapt, evolve or change their properties or behaviour in response to the environment around them. The analysis and design of adaptive structures requires a highly multi-disciplinary approach which includes elements of structures, materials, dynamics, control, design and inspiration taken from biological systems. Development of adaptive structures has been taking place in a wide range of industrial applications, but is particularly advanced in the aerospace and space technology sector with morphing wings, deployable space structures; piezoelectric devices and vibration control of tall buildings. Bringing together some of the foremost world experts in adaptive structures, this unique text: includes discussions of the application of adaptive structures in the aerospace, military, civil engineering structures, automotive and MEMS. presents the impact of biological inspiration in designing adaptive structures, particularly the use of hierarchy in nature, which typically induces multi-functional behavior. sets the agenda for future research in adaptive structures in one distinctive single volume. Adaptive Structures: Engineering Applications is essential reading for engineers and scientists working in the fields of intelligent materials, structural vibration, control and related smart technologies. It will also be of interest to senior undergraduate and postgraduate research students as well as design engineers working in the aerospace, mechanical, electrical and civil engineering sectors.
Download or read book Adaptive Systems in Control and Signal Processing 1989 written by T.S. Durrani and published by Elsevier. This book was released on 2014-06-28 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Symposium covered three major areas: adaptive control, identification and signal processing. In all three, new developments were discussed covering both theoretical and applications research. Within the subject area of adaptive control the discussion centred around the challenges of robust control design to unmodelled dynamics, robust parameter estimation and enhanced performance from the estimator, while the papers on identification took the theme of it being a bridge between adaptive control and signal processing. The final area looked at two aspects of signal processing: recursive estimation and adaptive filters.
Download or read book European Control Conference 1991 written by and published by European Control Association. This book was released on 1991-07-02 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the European Control Conference 1991, July 2-5, 1991, Grenoble, France
Download or read book Probability Random Variables and Stochastic Processes written by Athanasios Papoulis and published by McGraw-Hill Education. This book was released on 2002 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.
