Loss of Control Prevention and Recovery: Onboard Guidance, Control, and Systems Technologies

Loss of control (LOC) is one of the largest contributors to fatal aircraft accidents worldwide. LOC accidents are complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. These LOC hazards include vehicle impairment conditions, external disturbances; vehicle upset conditions, and inappropriate crew actions or responses. Hence, there is no single intervention strategy to prevent these accidents. NASA previously defined a comprehensive research and technology development approach for reducing LOC accidents and an associated integrated system concept. Onboard technologies for improved situation awareness, guidance, and control for LOC prevention and recovery are needed as part of this approach. Such systems should include: LOC hazards effects detection and mitigation; upset detection, prevention and recovery; and mitigation of combined hazards. NASA is conducting research in each of these areas. This paper provides an overview of this research, including the near-term LOC focus and associated analysis, as well as preliminary flight system architecture

Validation of Safety-Critical Systems for Aircraft Loss-of-Control Prevention and Recovery

Validation of technologies developed for loss of control (LOC) prevention and recovery poses significant challenges. Aircraft LOC can result from a wide spectrum of hazards, often occurring in combination, which cannot be fully replicated during evaluation. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of hazardous and uncertain conditions, and the validation framework must provide some measure of assurance that the new vehicle safety technologies do no harm (i.e., that they themselves do not introduce new safety risks). This paper summarizes a proposed validation framework for safety-critical systems, provides an overview of validation methods and tools developed by NASA to date within the Vehicle Systems Safety Project, and develops a preliminary set of test scenarios for the validation of technologies for LOC prevention and recover

Aircraft Loss-of-Control: Analysis and Requirements for Future Safety-Critical Systems and Their Validation

Loss of control remains one of the largest contributors to fatal aircraft accidents worldwide. Aircraft loss-of-control accidents are complex, resulting from numerous causal and contributing factors acting alone or more often in combination. Hence, there is no single intervention strategy to prevent these accidents. This paper summarizes recent analysis results in identifying worst-case combinations of loss-of-control accident precursors and their time sequences, a holistic approach to preventing loss-of-control accidents in the future, and key requirements for validating the associated technologies

Validation and Verification (V&V) of Safety-Critical Systems Operating Under Off-Nominal Conditions

Loss of control (LOC) remains one of the largest contributors to aircraft fatal accidents worldwide. Aircraft LOC accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or more often in combination. Hence, there is no single intervention strategy to prevent these accidents. Research is underway at the National Aeronautics and Space Administration (NASA) in the development of advanced onboard system technologies for preventing or recovering from loss of vehicle control and for assuring safe operation under off-nominal conditions associated with aircraft LOC accidents. The transition of these technologies into the commercial fleet will require their extensive validation and verification (V&V) and ultimate certification. The V&V of complex integrated systems poses highly significant technical challenges and is the subject of a parallel research effort at NASA. This chapter summarizes the V&V problem and presents a proposed process that could be applied to complex integrated safety-critical systems developed for preventing aircraft LOC accidents. A summary of recent research accomplishments in this effort is referenced

Validation and Verification of Future Integrated Safety-Critical Systems Operating under Off-Nominal Conditions

Loss of control remains one of the largest contributors to aircraft fatal accidents worldwide. Aircraft loss-of-control accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents and reducing them will require a holistic integrated intervention capability. Future onboard integrated system technologies developed for preventing loss of vehicle control accidents must be able to assure safe operation under the associated off-nominal conditions. The transition of these technologies into the commercial fleet will require their extensive validation and verification (V and V) and ultimate certification. The V and V of complex integrated systems poses major nontrivial technical challenges particularly for safety-critical operation under highly off-nominal conditions associated with aircraft loss-of-control events. This paper summarizes the V and V problem and presents a proposed process that could be applied to complex integrated safety-critical systems developed for preventing aircraft loss-of-control accidents. A summary of recent research accomplishments in this effort is also provided

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form

A problem formulation for glideslope tracking in wind shear using advanced robust control techniques

A formulation of the longitudinal glideslope tracking of a transport-class aircraft in severe wind shear and turbulence for application to robust control system design is presented. Mathematical wind shear models are incorporated into the vehicle mathematical model, and wind turbulence is modeled as an input disturbance signal. For this problem formulation, the horizontal and vertical wind shear gradients are treated as real uncertain parameters that vary over an entire wind shear profile. The primary objective is to examine the formulation of this problem into an appropriate design format for use in m-synthesis control system design

On the formulation of a minimal uncertainty model for robust control with structured uncertainty

In the design and analysis of robust control systems for uncertain plants, representing the system transfer matrix in the form of what has come to be termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents a transfer function matrix M(s) of the nominal closed loop system, and the delta represents an uncertainty matrix acting on M(s). The nominal closed loop system M(s) results from closing the feedback control system, K(s), around a nominal plant interconnection structure P(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unsaturated uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, but for real parameter variations delta is a diagonal matrix of real elements. Conceptually, the M-delta structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the currently available literature addresses computational methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty, where the term minimal refers to the dimension of the delta matrix. Since having a minimally dimensioned delta matrix would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta would be useful. Hence, a method of obtaining the interconnection system P(s) is required. A generalized procedure for obtaining a minimal P-delta structure for systems with real parameter variations is presented. Using this model, the minimal M-delta model can then be easily obtained by closing the feedback loop. The procedure involves representing the system in a cascade-form state-space realization, determining the minimal uncertainty matrix, delta, and constructing the state-space representation of P(s). Three examples are presented to illustrate the procedure

Future Integrated Systems Concept for Preventing Aircraft Loss-of-Control Accidents

Loss of control remains one of the largest contributors to aircraft fatal accidents worldwide. Aircraft loss-of-control accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents. This paper presents future system concepts and research directions for preventing aircraft loss-of-control accidents

Experimental Validation: Subscale Aircraft Ground Facilities and Integrated Test Capability

Experimental testing is an important aspect of validating complex integrated safety critical aircraft technologies. The Airborne Subscale Transport Aircraft Research (AirSTAR) Testbed is being developed at NASA Langley to validate technologies under conditions that cannot be flight validated with full-scale vehicles. The AirSTAR capability comprises a series of flying sub-scale models, associated ground-support equipment, and a base research station at NASA Langley. The subscale model capability utilizes a generic 5.5% scaled transport class vehicle known as the Generic Transport Model (GTM). The AirSTAR Ground Facilities encompass the hardware and software infrastructure necessary to provide comprehensive support services for the GTM testbed. The ground facilities support remote piloting of the GTM aircraft, and include all subsystems required for data/video telemetry, experimental flight control algorithm implementation and evaluation, GTM simulation, data recording/archiving, and audio communications. The ground facilities include a self-contained, motorized vehicle serving as a mobile research command/operations center, capable of deployment to remote sites when conducting GTM flight experiments. The ground facilities also include a laboratory based at NASA LaRC providing near identical capabilities as the mobile command/operations center, as well as the capability to receive data/video/audio from, and send data/audio to the mobile command/operations center during GTM flight experiments