Fault-Tolerant Flight Control System Design by a Dual-Loop Control Strategy

Considered influence of nonlinear system and disturbance, a new adaptive fault-tolerant control method based on neural network model-following adaptive inversion control is introduced for flight control system in the presence of control surface damage. To restrain modeling uncertainties caused by fault system, neural network PID and inversion controllers are design for fault-tolerant flight control system. It is based on BP (back-propagation) neural network which is designed by applying improved algorithm of on-line training and parameter optimization. Moreover the output of fault aircraft can perfectly track the trajectory of the reference model. The scheme is demonstrated through simulations applying the flight control system of a fighter. The simulation results show fault-tolerant flight control system maintains stability and handling qualities.

Recursive Actuator Fault Detection and Diagnosis for Emergency Landing of UASs

This paper addresses flight control system synthesis and the accommodation of controlled plant variation in an aircraft design envelope by using the frequency domain based quantitative feedback theory robust control system design method. The plant variations considered include varying flight conditions in the flight envelope and damage to aerodynamic control surfaces. A digital flight controller for the aircraft's longitudinal channel is designed and validated with simulations containing nonlinear saturation elements.

This paper discusses the issues of robust control law design for fault-tolerant systems. Based on the assumption that the effects of faults can be expressed in linear-fractional-transformation (LFT) forms, a fault-tolerant control systems design problem is formulated and solved via a linear matrix inequality (LMI)-based synthesis approach. In order to recover the convexity of the design problem whilst considering the robust performance and robust stability against faults and uncertainties simultaneously, a constrained optimisation approach is used. The simulation results of a design example (a longitudinal motion flight control problem for an unmanned aircraft in the case of suffering battle damage on its wing ) show that robust stability and satisfactory performance have been achieved.

This paper presents a fault tolerant flight control system. The Extended Multiple Model Adaptive Estimation EMMAE method is used to design the Fault Detection and Diagnosis FDD process. This process is able to detect, isolate and identify in real time faults that occurs in aircraft actuator. Based on information given by FDD process, a Sliding Mode Controller (SMC) is designed to compensate effects of such faults, and allows the aircraft to accomplish its mission safety with acceptable performances.

In this paper, a robust adaptive sliding mode control strategy of micro electro-mechanical system (MEMS) triaxial gyroscope using radial basis function (RBF) neural network is presented for the system identification of MEMS gyroscope. A key property of this scheme is that the prior knowledge of the upper bound of the system uncertainties is not required. An adaptive RBF neural network controller is used to learn the unknown upper bound of model uncertainties and external disturbances. The adaptive RBF neural network is incorporated into the adaptive sliding mode control in the Lyapunov sense, and the stability of the proposed adaptive neural sliding mode control can be established. The dynamics and angular velocities of gyroscope can be identified in real time. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive neural sliding mode control scheme, showing that the designed control system has better robust performance in its insensitivity to system nonlinearities; moreover, system parameters including angular velocity can be consistently estimated and tracking errors converge to zero asymptotically.

MANAGING PERFORMANCE DEGRADATION IN FAULT TOLERANT CONTROL SYSTEMS

The paper is devoted to the problem of fault-tolerant informational and control systems (ICSs) design. The class of ICSs for the hazardous objects with the criticality of error is considered. An approach to the fault-tolerant ICS design is based on performance redundancy and decentralized monitoring and control. It increases the fault-tolerant possibilities of the system, but requires the design and development of new models, methods and algorithms of system recovery. A new model of the reconfiguration problem and the problem solving algorithm based on cooperative principles of multiagent systems are given. Also some simulation results are represented and discussed briefly.

In this paper we considered the existing stable adaptive fault-tolerant control system design from references [3, 4] for achieving acceptable flight performance in the presence of control effector failures. This controller is developed for the overactuated case, i.e. the case when the number of control effectors exceeds the number of controlled outputs. We have shown that, in some cases, single or multiple effector failures introduce disturbances that are too large to be effectively handled by a single adaptive controller. To address this problem, in this paper we developed an adaptive fault-tolerant flight control system based on the concept of multiple models, switching and tuning from reference [11]. We have shown that such a controller yields a stable overall system, is sufficiently robust in the presence of severe control effector failures, and achieves excellent overall performance as illustrated through simulations of F/A-18A carrier landing maneuver.

Adaptive sliding mode control with hysteresis compensation-based neuroevolution for motion tracking of piezoelectric actuator

Unmanned winged re-entry space vehicles glide without any thrust in their re-entry phase. In this phase, one of the most possible and important faults in the airframe is jamming of the elevon. In order to make control systems tolerant to this failure, the flight control system is required to keep its stability and the performance, even if such a failure occurs. Since this kind of fault can be modeled as a structured parameter deviation from a robust control point of view, this paper presents some new ideas to realize a fault tolerant flight control system based on /spl mu/-synthesis, and apply it to the unmanned winged re-entry space vehicle HOPE-X (H-II Orbiting Plane-Experimental). Simulations are also demonstrated to verify the usefulness of the proposed method.

Fault-tolerant control systems: A comparative study between active and passive approaches

Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems

: This project focused on investigating the potential of on-line learning 'hardware-based' neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures. Following a phase of simulation studies a set of selected architectures for neural estimators and neural controllers were flown on a semi-scale YF-22 aircraft model. The YF-22 model was designed, built, and flown at research facilities at West Virginia University. Additionally, a customized electronic payload featuring these fault tolerant schemes was designed, built, tested and interfaced with the YF-22 flight control system. A series of 33 flight tests were conducted with the aircraft; the flight data confirmed the potential of neural estimators and controllers for fault tolerance purposes. Another research objective was to start addressing system requirements leading to the problem of software validation and verification for this new class of algorithms for fault tolerant flight control systems.

For a research aircraft, "conventional" control laws (CLs) are implemented on a "baseline" flight computer (FC) while research CLs are typically housed on a dedicated research computer. Therefore, for an experimental aircraft used to test specific fault tolerant flight control systems, a safety logic scheme is needed to ensure a safe transition from conventional to research CLs (while at nominal conditions) as well as from research CLs at nominal conditions to conditions with "simulated" failures on specific control surfaces. This paper describes the design of such a safety scheme for the NASA Intelligent Flight Control System (IFCS) F-15 Program. The goals of the IFCS F-15 program are to investigate the performance of a set of fault tolerant CLs based on the use of dynamic inversion with neural augmentation. The different transitions are monitored using information relative to flight conditions and controller-related performance criteria. The testing of the scheme is performed with a Simulink-based flight simulation code and interface developed at West Virginia University for the NASA IFCS F-15 aircraft.