Artificial Immune System Approach for Airborne Vehicle Maneuvering

A method and system for control of a first aircraft relative to a second aircraft. A desired location and desired orientation are estimated for the first aircraft, relative to the second aircraft, at a subsequent time, t=t2, subsequent to the present time, t=t1, where the second aircraft continues its present velocity during a subsequent time interval, t1.ltoreq.t.ltoreq.t2, or takes evasive action. Action command sequences are examined, and an optimal sequence is chosen to bring the first aircraft to the desired location and desired orientation relative to the second aircraft at time t=t2. The method applies to control of combat aircraft and/or of aircraft in a congested airspace

Aircraft system modeling error and control error

A method for modeling error-driven adaptive control of an aircraft. Normal aircraft plant dynamics is modeled, using an original plant description in which a controller responds to a tracking error e(k) to drive the component to a normal reference value according to an asymptote curve. Where the system senses that (1) at least one aircraft plant component is experiencing an excursion and (2) the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, neural network (NN) modeling of aircraft plant operation may be changed. However, if (1) is satisfied but the error component is returning toward its reference value according to expected controller characteristics, the NN will continue to model operation of the aircraft plant according to an original description

A Proposed Strategy for the U.S. to Develop and Maintain a Mainstream Capability Suite ("Warehouse") for Automated/Autonomous Rendezvous and Docking in Low Earth Orbit and Beyond

The ability of space assets to rendezvous and dock/capture/berth is a fundamental enabler for numerous classes of NASA fs missions, and is therefore an essential capability for the future of NASA. Mission classes include: ISS crew rotation, crewed exploration beyond low-Earth-orbit (LEO), on-orbit assembly, ISS cargo supply, crewed satellite servicing, robotic satellite servicing / debris mitigation, robotic sample return, and robotic small body (e.g. near-Earth object, NEO) proximity operations. For a variety of reasons to be described, NASA programs requiring Automated/Autonomous Rendezvous and Docking/Capture/Berthing (AR&D) capabilities are currently spending an order-of-magnitude more than necessary and taking twice as long as necessary to achieve their AR&D capability, "reinventing the wheel" for each program, and have fallen behind all of our foreign counterparts in AR&D technology (especially autonomy) in the process. To ensure future missions' reliability and crew safety (when applicable), to achieve the noted cost and schedule savings by eliminate costs of continually "reinventing the wheel ", the NASA AR&D Community of Practice (CoP) recommends NASA develop an AR&D Warehouse, detailed herein, which does not exist today. The term "warehouse" is used herein to refer to a toolbox or capability suite that has pre-integrated selectable supply-chain hardware and reusable software components that are considered ready-to-fly, low-risk, reliable, versatile, scalable, cost-effective, architecture and destination independent, that can be confidently utilized operationally on human spaceflight and robotic vehicles over a variety of mission classes and design reference missions, especially beyond LEO. The CoP also believes that it is imperative that NASA coordinate and integrate all current and proposed technology development activities into a cohesive cross-Agency strategy to produce and utilize this AR&D warehouse. An initial estimate indicates that if NASA strategically coordinates the development of a robust AR&D capability across the Agency, the cost of implementing AR&D on a spacecraft could be reduced from roughly $70M per mission to as low as$7M per mission, and the associated development time could be reduced from 4 years to 2 years, after the warehouse is completely developed. Table 1 shows the clear long-term benefits to the Agency in term of costs and schedules for various missions. (The methods used to arrive at the Table 1 numbers is presented in Appendices A and B.

Time Delay Margin Analysis of Modified State Observer based Adaptive Controller

Adaptive control of systems with large uncertainties requires fast adaptation to ensure stability and good tracking performance. A drawback with using high adaptive gains, however, is that high gains could result in high frequency oscillations in the control signal. These oscillations in turn could excite the unmodeled dynamics of the plant and lead to system failure. An adaptive control methodology with a “modified state observer” using a generic observer structure is proposed to tackle the above problem. The use of modified state observer alleviates the oscillations in control signals by separating the design of estimation error dynamics and reference model dynamics. In this paper the effect of using modified state observer for adaptive control of input delay systems is analyzed. The local time delay margins are estimated using bounded linear stability analysis method and compared with that of standard model reference adaptive control. The relationships between estimation error dynamics, tracking error dynamics, adaptation gain and local time delay margin are investigated both analytically and numerically. Based on the analysis, an effective method is proposed for varying the adaptation rate online to ensure stable adaptation. Simulation studies were carried out for a simple scalar problem and also using a longitudinal pitch dynamic model of a Generic Transport aircraft. The results obtained indicate that the modified state observer based adaptive controllers are quite robust compared to MRAC

Robust Adaptive Control of a Structurally Damaged Aircraft

Application of adaptive control for aerospace applications has been a topic of great research interest over the past several decades. The driving force behind it is the enhanced safety that it can provide during adverse flight conditions and aircraft structural damage. Neural network based direct model reference adaptive controllers (MRAC) are particularly proven to be effective in handling such scenarios. But one of the limitations with this methodology is their inability to handle unmodelled dynamics, which severely restricts the adaptation rate of these controllers. This paper uses the recently developed modified state observer (MSO) adaptive control methodology which overcomes the above problem by using an observer controller structure that separates the design of estimation error dynamics from the nominal system dynamics. This allows for designing faster estimation error dynamics which permits the use of large adaptation rate. In this paper the MSO methodology is applied for the adaptive control of a structurally damaged aircraft, which has pitch ,yaw and roll axes dynamically coupled .So the adaptive control problem is to reduce the interactions between these axes and stabilize the aircraft. Simulation results demonstrate the potential of the proposed methodology in solving the above problem. Copyright © 2010 by S.N. balakrishnan

SNAC Convergence and Use in Adaptive Autopilot Design

In this paper, approximate dynamic programming (ADP)based design tools are developed for adaptive control of aircraft control under nominal and damaged conditions. Nominal control of the system is computed with a Single Network Adaptive Critic(SNAC) derived through principles of ADP. Convergence of SNAC training is shown by reducing it to solving a set of nonlinear algebraic equations in weights. Unlike many adaptive control approaches, we develop approximate optimal control expressions to handle uncertainties. Uncertainties are calculated with an online neural network with guaranteed convergence. Longitudinal dynamics of an aircraft is used to illustrate the working of the developed algorithms. ©2009 IEEE

Air Mobility Data & Reasoning Fabric

Throughout the world, especially in dense urban environments, the quality of life is being negatively impacted by ever growing commute time. Travel, beyond commuting, is increasingly driven by door-to-door challenges ? not just gate-to-gate considerations. Air Mobility may be an approach to address these challenges, as it can effectively convert our 2D mobility system to a 3D mobility system, vastly increasing mobility options