Download or read book Multiple Model Adaptive Estimation and Control Redistribution for the Vista F 16 written by Robert Weston Lewis and published by . This book was released on 1996-12-01 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Performance characteristics of a Multiple Model Adaptive Estimation and Control Redistribution (MMAE/CR) algorithm are evaluated against single and double actuator and sensor failures. MMAE alone can compensate for sensor failures, whereas Control Redistribution compensates for actuator failures by redistributing commands, initially intended for failed actuators, to the unfailed actuators in such a way that the desired system response is achieved. Both failure detection and compensation capabilities are developed and analyzed through an extensive amount of simulation data, particularly addressing multiple failures. Simulations are performed utilizing the high fidelity, non-linear six degree of freedom Simulation Rapid Prototyping Facility for the VISTA F-16, for both benign and maneuvering scenarios. Methods utilized to incorporate the MMAE/ CR techniques are examined and modifications required to enhance performance are also presented. Results are presented which indicate the techniques incorporated provide an excellent means of both failure detection and compensation for the failures of both actuators and sensors. Approximately 98 percent of all secondary failures were successfully detected, and the majority of these detections are shown to occur in less than .5 seconds. The techniques of Multiple Model Adaptive Estimation and Control Redistribution are shown to complement each other well by providing improved failure detection in the face of actuator failures through the redistribution of the dither signal (used to enhance identifiability when there are no maneuvering commands to excite the system), and improved control authority through enhanced state variable estimation in the face of sensor failures.

Download or read book Multiple Model Adaptive Estimation and Control Redistribution Performance on the VISTA F 16 During Partial Actuator Impairments written by Curtis S. Clark and published by . This book was released on 1997-12-01 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation with Control Reconfiguration (MMAE/CR) capability to estimate and compensate for partial actuator failures, or "impairments" is investigated using the high-fidelity, nonlinear, six-degree- of-freedom, VISTA F-16 simulation which currently resides on the Simulation Rapid-Prototyping Facility (SRF). After developing a model for inserting partial actuator impairments into the VISTA F-16 truth model, research begins with a battery of single actuator impairment tests. This stage of research explores the capability of the existing MMAE algorithm to estimate single, partial actuator impairments, and helps to define refinements and expansions needed in the MMAE algorithm for the second phase of research: the detection and estimation of dual, total and partial actuator impairments. It is seen from the first stage of research that, while MMAE is able to estimate partial impairments, there are refinements needed, such as "probability smoothing and quantization", to compensate for the quality of MMAE probability data and to provide a better, more stable estimate value to the Control Reconfiguration module. The Kalman filters and the dual, partial failure filter banks necessary for the detection of dual, partial actuator impairments are also defined as a result of the single impairment tests. Fifteen more banks of "partial first-failure" Kalman filters are added to the existing MMAE algorithm, as well as the "bank swapping" logic necessary to transition to them. Once the revised and expanded MMAE/CR algorithm is ready, research begins on dual combinations of total and partial actuator impairments. While results of these tests (for other than total impairments) are not as good as originally hoped or expected, the potential_for better performance is evident.

Download or read book Multiple Model Adaptive Estimation and Control Redistribution Performance on the Vista F 16 During Partial Actuator Impairments written by Curtis Steven Clark and published by . This book was released on 1997-12-01 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation with Control Reconfiguration (MMAE/CR) capability to estimate and compensate for partial actuator failures, or 'impairments' is investigated using the high fidelity, nonlinear, six degree of freedom, VISTA F-16 simulation which currently resides on the Simulation Rapid-Prototyping Facility (SRF). After developing a model for inserting partial actuator impairments into the VISTA F-16 truth model, research begins with a battery of single actuator impairment tests. This stage of research explores the capability of the existing MMAE algorithm to estimate single, partial actuator impairments, and helps to define refinements and expansions needed in the MMAE algorithm for the second phase of research: the detection and estimation of dual, total and partial actuator impairments. It is seen from the first stage of research that, while MMAE is able to estimate partial impairments, there are refinements needed, such as 'probability smoothing and quantization', to compensate for the quality of MMAE probability data and to provide a better, more stable estimate value to the Control Reconfiguration module. The Kalman filters and the dual, partial failure filter banks necessary for the detection of dual, partial actuator impairments are also defined as a result of the single impairment tests. Fifteen more banks of 'partial first failure' Kalman filters are added to the existing MMAE algorithm, as well as the 'bank swapping' logic necessary to transition to them. Once the revised and expanded MMAE/CR algorithm is ready, research begins on dual combinations of total and partial actuator impairments. While results of these tests (for other than total impairments) are not as good as originally hoped or expected, the potential for better performance is evident.

Download or read book Multiple Model Adaptive Estimation and Control Redistribution Performance on the Vista F 16 During Partial Actuator Impairments Volume III written by and published by . This book was released on 1997 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation with Control Reconfiguration (MMAE/CR) capability to estimate and compensate for partial actuator failures, or 'impairments' is investigated using the high fidelity, nonlinear, six degree of freedom, VISTA F-16 simulation which currently resides on the Simulation Rapid-Prototyping Facility (SRF). After developing a model for inserting partial actuator impairments into the VISTA F-16 truth model, research begins with a battery of single actuator impairment tests. This stage of research explores the capability of the existing MMAE algorithm to estimate single, partial actuator impairments, and helps to define refinements and expansions needed in the MMAE algorithm for the second phase of research: the detection and estimation of dual, total and partial actuator impairments. It is seen from the first stage of research that, while MMAE is able to estimate partial impairments, there are refinements needed, such as 'probability smoothing and quantization', to compensate for the quality of MMAE probability data and to provide a better, more stable estimate value to the Control Reconfiguration module. The Kalman filters and the dual, partial failure filter banks necessary for the detection of dual, partial actuator impairments are also defined as a result of the single impairment tests. Fifteen more banks of 'partial first failure' Kalman filters are added to the existing MMAE algorithm, as well as the 'bank swapping' logic necessary to transition to them. Once the revised and expanded MMAE/CR algorithm is ready, research begins on dual combinations of total and partial actuator impairments. While results of these tests (for other than total impairments) are not as good as originally hoped or expected, the potential for better performance is evident.

Download or read book Multiple Model Adaptive Control of the Vista F 16 written by Michael Joseph Stepaniak and published by . This book was released on 1995 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiple Model Adaptive Estimation and Control Redistribution Performance on the VISTA F 16 During Partial Actuator Impairments Volume 1 written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation with Control Reconfiguration (MMAE/CR) capability to estimate and compensate for partial actuator failures, or "impairments" is investigated using the high-fidelity, nonlinear, six-degree-of-freedom, VISTA F-16 simulation which currently resides on the Simulation Rapid-Prototyping Facility (SRF). After developing a model for inserting partial actuator impairments into the VISTA F-16 truth model, research begins with a battery of single actuator impairment tests. This stage of research explores the capability of the existing MMAE algorithm to estimate single, partial actuator impairments, and helps to define refinements and expansions needed in the MMAE algorithm for the second phase of research: the detection and estimation of dual, total and partial actuator impairments. It is seen from the first stage of research that, while MMAE is able to estimate partial impairments, there are refinements needed, such as "probability smoothing and quantization", to compensate for the quality of MMAE probability data and to provide a better, more stable estimate value to the Control Reconfiguration module. The Kalman filters and the dual, partial failure filter banks necessary for the detection of dual, partial actuator impairments are also defined as a result of the single impairment tests. Fifteen more banks of "partial first-failure" Kalman filters are added to the existing MMAE algorithm, as well as the "bank swapping" logic necessary to transition to them. Once the revised and expanded MMAE/CR algorithm is ready, research begins on dual combinations of total and partial actuator impairments. While results of these tests (for other than total impairments) are not as good as originally hoped or expected, the potential_for better performance is evident.

Download or read book Multiple Model Adaptive Estimation and Control Redistribution Performance on the VISTA F 16 During Partial Actuator Impairments Volume 2 written by and published by . This book was released on 1997 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation with Control Reconfiguration (MMAE/CR) capability to estimate and compensate for partial actuator failures, or "impairments" is investigated using the high-fidelity, nonlinear, six-degree-of-freedom, VISTA F-16 simulation which currently resides on the Simulation Rapid-Prototyping Facility (SRF). After developing a model for inserting partial actuator impairments into the VISTA F-16 truth model, research begins with a battery of single actuator impairment tests. This stage of research explores the capability of the existing MMAE algorithm to estimate single, partial actuator impairments, and helps to define refinements and expansions needed in the MMAE algorithm for the second phase of research: the detection and estimation of dual, total and partial actuator impairments. It is seen from the first stage of research that, while MMAE is able to estimate partial impairments, there are refinements needed, such as "probability smoothing and quantization", to compensate for the quality of MMAE probability data and to provide a better, more stable estimate value to the Control Reconfiguration module. The Kalman filters and the dual, partial failure filter banks necessary for the detection of dual, partial actuator impairments are also defined as a result of the single impairment tests. Fifteen more banks of "partial first-failure" Kalman filters are added to the existing MMAE algorithm, as well as the "bank swapping" logic necessary to transition to them. Once the revised and expanded MMAE/CR algorithm is ready, research begins on dual combinations of total and partial actuator impairments. While results of these tests (for other than total impairments) are not as good as originally hoped or expected, the potential-for better performance is evident.

Download or read book Application of Sliding Mode Methods to the Design of Reconfigurable Flight Control Systems written by Scott R. Wells and published by . This book was released on 2002 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Observer-based sliding mode control is investigated for application to aircraft reconfigurable flight control. An overview of reconfigurable flight control is given, including a review of the current state-of-the-art within the subdisciplines of fault detection parameter identification, adaptive control schemes, and dynamic control allocation. Of the adaptive control methods reviewed, sliding mode control (SMC) appears promising due its property of invariance to matched uncertainty. An overview of SMC is given and its properties are demonstrated. Sliding mode methods, however, are difficult to implement because unmodeled parasitic dynamics cause immediate and severe instability. This presents a challenge for all practical applications with limited bandwidth actuators. One method to deal with parasitic dynamics is the use of an asymptotic observer. Observer-based SMC is investigated, and a method for selecting observer gains is offered. An additional method for shaping the feedback loop using a filter is also developed. It is shown that this SMC prefilter is equivalent to a form of model reference hedging. A complete design procedure is given which takes advantage of the sliding mode boundary layer to recast the SMC as a linear control law. Frequency domain loop shaping is then used to design the sliding manifold. Finally, three aircraft applications are demonstrated. An F-18/HARV is used to demonstrate SISO and MIMO designs. The third application is a linear six degree-of-freedom advanced tailless fighter model. The observer-based SMC is seen to provide excellent tracking with superior robustness to parameter changes and actuator failures.

Download or read book International Aerospace Abstracts written by and published by . This book was released on 1998 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Control Design 2000 ROCOND 2000 written by Vladimír Kuc̆era and published by . This book was released on 2000 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiple Model Adaptive Estimation Using Filter Spawning written by Kenneth A. Fisher (2LT, USAF.) and published by . This book was released on 1999 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book NASA SP written by and published by . This book was released on 1993 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Generalized Multiple Model Adaptive Estimation written by Badr N. Alsuwaidan and published by . This book was released on 2008 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: ?Pub Inc In this dissertation a generalized multiple-model adaptive estimator (GMMAE) is presented that can be used to estimate the unknown noise statistics in filter designs. The assumed unknowns in the adaptive estimator are the process noise covariance elements. Multiple parameter elements are used to drive multiple-model parallel filters for state estimation. The current approach focuses on estimating the process noise covariance by sequentially updating weights associated with parameter elements through the calculation of the likelihood function of the measurement-minusestimate residuals, which also incorporates correlations between various measurement times. For linear Gaussian measurement processes the likelihood function is easily determined. For nonlinear Gaussian measurement processes, it is assumed that the linearized output sufficiently captures the statistics of the likelihood function by making the small noise assumption. A proof is provided that shows the convergence properties of the generalized approach versus the traditional multiple-model adaptive estimator (MMAE). Simulation results, involving a two-dimensional target tracking problem ans GPS-based position estimation problem using an extended Kalman filter, indicate that the new approach is able to correctly estimate the noise statistics.

Download or read book An Optimal Parameter Discretization Strategy for Multiple Model Adaptive Estimation and Control written by Stuart N. Sheldon and published by . This book was released on 1989 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method is proposed for designing multiple model adaptive estimators (MMAE) to provide combined state and parameter estimation in the presence of an uncertain parameter vector. It is assumed that the parameter varies over a continuous region and a finite number of constant-gain filters is available for the estimation. The estimator elemental filters are chosen by minimizing a cost functional representing the average state prediction error autocorrelation, with the average taken as the true parameter ranges over the admissible parameter set. A second-order example is used to illustrate the increase in performance over previously accepted filter selection methods. By minimizing a cost functional representing the average parameter prediction error autocorrelation, a parameter estimator is designed which is different from the state estimator. The parameter estimator found with this method provides lower average mean square parameter estimation error than previously accepted design methods. An analogous method is proposed for designing multiple model adaptive controllers to provide stabilizing control in the presence of an uncertain parameter vector. A finite number of constant-gain controllers is used to regulate a system with a parameter vector that varies over a continuous region of the parameter space. The controller elemental filters are chosen by minimizing a cost functional representing the average regulation error autocorrelation, with the average taken as the true parameter ranges over the admissible parameter set. Keywords: Numerical optimization, Adaptive control systems, Theses. (aw).

Download or read book New Variations of Multiple Model Adaptive Estimation for Improved Tracking and Identification written by Christopher K. Nebelecky and published by . This book was released on 2013 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple model adaptive estimation (MMAE) is a recursive algorithm that uses a bank of estimators, each purposefully dependent on a particular hypothesis, to determine an estimate of an uncertain system under consideration while simultaneously tracking the system state. The first generation of MMAE, introduced by Magill in 1965 considered the estimators to act independently and in parallel, determining state estimates conditional with each hypothesis. Through computation of a normalized mode-conditioned likelihood, the conditional probability that each hypothesis correctly models the system is computed. Since Magill's seminal work, many offshoots of MMAE have been developed. Modifications have been reported, but are typically on on an application specific basis which limits their versatility. In this dissertation, two variations of MMAE are considered. The first variation is based on an observed flaw which leads to degenerate tracking performance. The second variation is motivated by previous research which showed improved convergence performance by considering a generalized mode-conditioned likelihood function for determining the hypothesis conditional probabilities. Each estimator, or specifically Kalman filter, is designed around a particular system hypothesis. If the hypothesis is not sufficiently close to the true system, the resulting filter will generally produce erroneous estimates which do not track the system. This is because each filter believes that the hypothesized system is optimal. Further, the state error covariances resulting from such a suboptimal filter will be inconsistent because they have no knowledge of the incorrect hypothesized model. By explicitly accounting for the deviation of the hypothesis, recursions are developed which, when combined with MMAE are shown to provide superior tracking performance over the standard MMAE. Additionally the proposed variation, called model error MMAE, is shown to provide acceptable tracking performance for dynamically switching systems at a fraction of the computational expense of other algorithms specifically developed for that application. The second variation, referred to as generalized multiple model adaptive estimation (GMMAE), uses an augmented vector of current and past residuals to drive the recursion for the hypothesis conditional probabilities. Necessary for that recursion is evaluation of the time-domain autocovariance matrix of the residual sequence. When filtering linear (and linearized) systems, the autocovariance can be analytically expressed as a function of the system matrices, covariances and filter gain. When filtering nonlinear systems using the Unscented filter, analytic expressions for the autocovariance are not possible.^Motivated to include Unscented filters within the GMMAE framework, a method for calculating the time-domain autocovariance of the residual sequence from an Unscented filter is presented. The proposed method is validated analytically on a simplified system and simulation results are presented using the algorithm for process noise estimation in a planar tracking problem.

Download or read book Aeronautical Engineering written by and published by . This book was released on 1993 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International aerospace abstracts (IAA).

Download or read book Government Reports Announcements Index written by and published by . This book was released on 1996 with total page 952 pages. Available in PDF, EPUB and Kindle. Book excerpt: