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A quaternion-based attitude control system is developed for the X-33 in the ascent flight phase. A nonlinear control law commands body-axis rotation rates that align the angular velocity vector with an Euler axis defining the axis of rotation that will rotate the body-axis system into a desired-axis system. The magnitudes of the commanded body rates are determined by the magnitude of the rotation error. The commanded body rates form the input to a dynamic inversion-based adaptive/reconfigurable control law. The indirect adaptive control portion of the control law uses online system identification to estimate the current control effectiveness matrix to update a control allocation module. The control allocation nominally operates in a minimum deflection mode; however, if a fault is detected, it can operate in a null-space injection mode that excites and decorrelates the effectors without degrading the vehicle response to enable online system identification. The overall 5 stem is designed to provide fault and damage tolerance for the X-33 on ascent.
Aircraft Control Allocation Wayne Durham, Virginia Polytechnic Institute and State University, USA Kenneth A. Bordignon, Embry-Riddle Aeronautical University, USA Roger Beck, Dynamic Concepts, Inc., USA An authoritative work on aircraft control allocation by its pioneers Aircraft Control Allocation addresses the problem of allocating supposed redundant flight controls. It provides introductory material on flight dynamics and control to provide the context, and then describes in detail the geometry of the problem. The book includes a large section on solution methods, including 'Banks' method', a previously unpublished procedure. Generalized inverses are also discussed at length. There is an introductory section on linear programming solutions, as well as an extensive and comprehensive appendix dedicated to linear programming formulations and solutions. Discrete-time, or frame-wise allocation, is presented, including rate-limiting, nonlinear data, and preferred solutions. Key features: Written by pioneers in the field of control allocation. Comprehensive explanation and discussion of the major control allocation solution methods. Extensive treatment of linear programming solutions to control allocation. A companion web site contains the code of a MATLAB/Simulink flight simulation with modules that incorporate all of the major solution methods. Includes examples based on actual aircraft. The book is a vital reference for researchers and practitioners working in aircraft control, as well as graduate students in aerospace engineering.
This thesis reports on novel methods for gain-scheduling and fault tolerant control (FTC). It begins by analyzing the connection between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms. This is then followed by a detailed description of the design of robust and shifting state-feedback controllers for these systems. Furthermore, it presents two approaches to fault-tolerant control: the first is based on a robust polytopic controller design, while the second involves a reconfiguration of the reference model and the addition of virtual actuators into the loop. Inaddition the thesis offers a thorough review of the state-of-the art in gain scheduling and fault-tolerant control, with a special emphasis on LPV and TS systems.
This book offers a complete overview of fault-tolerant flight control techniques. Discussion covers the necessary equations for the modeling of small UAVs, a complete system based on extended Kalman filters, and a nonlinear flight control and guidance system.
This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.
This book provides a systematical and comprehensive description of some facets of modeling, designing, analyzing and exploring the control allocation and fault-tolerant control problems for over-actuated spacecraft attitude control system under actuator failures, system uncertainties and disturbances. The book intends to provide a unified platform for understanding and applicability of the fault-tolerant attitude control and control allocation for different purposes in aerospace engineering and some related fields. And it is particularly suited for readers who are interested to learn solutions in spacecraft attitude control system design and related engineering applications.
This book presents selected fault diagnosis and fault-tolerant control strategies for non-linear systems in a unified framework. In particular, starting from advanced state estimation strategies up to modern soft computing, the discrete-time description of the system is employed Part I of the book presents original research results regarding state estimation and neural networks for robust fault diagnosis. Part II is devoted to the presentation of integrated fault diagnosis and fault-tolerant systems. It starts with a general fault-tolerant control framework, which is then extended by introducing robustness with respect to various uncertainties. Finally, it is shown how to implement the proposed framework for fuzzy systems described by the well-known Takagi–Sugeno models. This research monograph is intended for researchers, engineers, and advanced postgraduate students in control and electrical engineering, computer science, as well as mechanical and chemical engineering.
This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30–June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China.
This paper addresses issues related to output feedback control, including sensor placement, for a model of an air-breathing hypersonic vehicle. The model presents a number of control challenges, in particular because of strong couplings between the propulsive and aerodynamic forces. Because of the vehicle's low weight, slenderness, and length, the vehicle's flexibility has a large impact on stability and control of the vehicle. Two output feedback control methods are developed. One applies reconstruction of the flexible body system states, toward applications of state feedback control. The other uses a robust design that does not rely on an observer to ensure stabilization and performance throughout a given flight envelope. A rate gyroscope and an accelerometer have been modeled, incorporating the flexible effects, and strategies for sensor placement have been developed for the hypersonic vehicle model to enhance observability or to preserve certain system structures that are favorable for robust control design. Simulation results are provided to demonstrate the sensor placement strategies and output feedback control performances.
The forces and moments produced by a vehicle's aerodynamic control surfaces are often nonlinear functions of control surface deflection. This phenomenon limits the accuracy of state-of-the-art control allocation algorithms since all of the approaches are based on the assumption that the control variable rates are linear functions of the surface deflections and that control variable rate increments are not produced for zero deflections. The errors introduced by this assumption are currently mitigated by the robustness resulting from feedback control laws. A method for improving the performance of the feedback control/control allocation system is presented that directly attacks the inaccuracies introduced by these linear assumptions.