Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Flies are among the most agile flying creatures on Earth To mimic this aerial prowess in a similarly sized robot requires tiny, high-efficiency mechanical components that pose miniaturization challenges governed by force-scaling laws, suggesting unconventional solutions for propulsion, actuation, and manufacturing To this end, we developed high-power-density piezoelectric flight muscles and a manufacturing methodology capable of rapidly prototyping articulated, flexure-based sub-millimeter mechanisms We built an 80-milligram, insect-scale, flapping-wing robot modeled loosely on the morphology of flies Using a modular approach to flight control that relies on limited information about the robot's dynamics, we demonstrated tethered but unconstrained stable hovering and basic controlled flight maneuvers The result validates a sufficient suite of innovations for achieving artificial, insect-like flight

http://science.sciencemag.org/content/sci/340/6132/603.full.pdf

Controlled Flight of a Biologically Inspired, Insect-Scale Robot

Recent progress in flapping wing aerodynamics and aeroelasticity

https://www.fossen.biz/home/papers/JohansenFossen%20Automatica%202013.pdf

Control allocation—A survey

This paper describes the design of a nonlinear robust adaptive controller for a flexible air-breathing hypersonic vehicle model. Because of the complexity of a first-principle model of the vehicle dynamics, a control-oriented model is adopted for design and stability analysis. This simplified model retains the dominant features of the higher-fidelity model, including the nonminimum phase behavior of the flight-path angle dynamics, the flexibility effects, and the strong coupling between the engine and flight dynamics. A combination of nonlinear sequential loop closure and adaptive dynamic inversion is adopted for the design of a dynamic state-feedback controller that provides stable tracking of the velocity and altitude reference trajectories and imposes a desired set point for the angle of attack. A complete characterization of the internal dynamics of the model is derived for a Lyapunov-based stability analysis of the closed-loop system, which includes the structural dynamics. The proposed methodology addresses the issue of stability robustness with respect to both parametric model uncertainty, which naturally arises when adopting reduced-complexity models for control design, and dynamic perturbations due to the flexible dynamics. Simulation results from the full nonlinear model show the effectiveness of the controller.

Nonlinear Robust Adaptive Control of Flexible Air-Breathing Hypersonic Vehicles

Much emphasis has been placed on over-actuated systems for air vehicles. Over-actuating an air vehicle provides a certain amount of redundancy for the flight control system, thus potentially allowing for recovery from off-nominal conditions. Due to this redundancy, control allocation algorithms are typically utilized to compute a unique solution to the over-actuated problem. Control allocators compute the commands that are applied to the actuators so that a certain set of forces or moments are generated by the control effectors. Usually, control allocation problems are formulated as optimization problems so that all of the available degrees of freedom can be utilized and, when sufficient control power exists, secondary objectives can be achieved. In this work, a survey of control allocation techniques will be given.

Control Allocation for Over-actuated Systems

A new method of controlling a flapping-wing micro air vehicle by varying the velocity profiles of the wing strokes is presented in this manuscript. An exhaustive theoretical analysis along with simulation results show that this new method, called split-cycle constant-period frequency modulation, is capable of providing independent control over vertical and horizontal body forces as well as rolling and yawing moments using only two physical actuators, whose oscillatory motion is defined by four parameters. An actuated bob-weight is introduced to enable independent control of pitching moment. A general method for deriving sensitivities of cycle-averaged forces and moments to changes in wingbeat kinematic parameters is provided, followed by an analytical treatment for a case where the angle of attack of each wing is passively regulated and the motion of the wing spar in the stroke plane is driven by a split-cycle waveform. These sensitivities are used in the formulation of a cycle-averaged control law that successfully stabilizes and controls two different simulation models of the aircraft. One simulation model is driven by instantaneous aerodynamic forces derived from blade-element theory, while the other is driven by an empirical representation of an unsteady aerodynamic model that was derived from experiments.

Wingbeat Shape Modulation for Flapping-Wing Micro-Air-Vehicle Control During Hover

To enable autonomous operation of future reusable launch vehicles, reconfiguration technologies will be needed to facilitate mission recovery following a major anomalous event. The Air Force’s Integrated Adaptive Guidance and Control program developed such a system for Boeing’s X-40A, and the total in-flight simulator research aircraft was employed to flight test the algorithms during approach and landing. The inner loop employs a modelfollowing/dynamic-inversion approach with optimal control allocation to account for control-surface failures. Further, the reference-model bandwidth is reduced if the control authority in any one axis is depleted as a result of control effector saturation. A backstepping approach is utilized for the guidance law, with proportional feedback gains that adapt to changes in the reference model bandwidth. The trajectory-reshaping algorithm is known as the optimum-path-to-go methodology. Here, a trajectory database is precomputed off line to cover all variations under consideration. An efficient representation of this database is then interrogated in flight to rapidly find the “best” reshaped trajectory, based on the current state of the vehicle’s control capabilities. The main goal of the flight-test program was to demonstrate the benefits of integrating trajectory reshaping with the essential elements of control reconfiguration and guidance adaptation. The results indicate that for more severe, multiple control failures, control reconfiguration, guidance adaptation, and trajectory reshaping are all needed to recover the mission.

Integrated Adaptive Guidance and Control for Re-Entry Vehicles with Flight-Test Results

A wingbeat forcing function and control method are presented that allow six-degree-of-freedom control of a flapping-wing micro air vehicle using only two actuators, each of which independently actuate a wing. Split-cycle constant-period frequency modulation with wing bias is used to produce nonzero cycle-averaged drag. The wing bias provides pitching-moment control and, when coupled with split-cycle constant-period frequency modulation, requires only independently actuated wings to enable six-degree-of-freedom flight. Wing bias shifts the cycle-averaged center-of-pressure locations of the wings, thus providing the ability to pitch the vehicle. Implementation of the wing bias is discussed, and modifications to the wingbeat forcing function are made to maintain wing position continuity. Instantaneous and cycle-averaged forces and moments are computed, cycle-averaged control derivatives are calculated, and a controller is developed. The controller is designed using a simplified aerodynamic model derived with blade-element theory and cycle averaging. The controller is tested using a simulation that includes blade-element-based estimates of the instantaneous aerodynamic forces and moments that are generated by the combined motion of the rigid-body fuselage and the flapping wings. Simulations using this higher-fidelity model indicate that the cycle-averaged blade-element-based controller is capable of achieving controlled flight.

Dynamics and Control of a Biomimetic Vehicle Using Biased Wingbeat Forcing Functions

An aerodynamic model for the forces and moments acting on a minimally actuated flapping wing micro air vehicle (FWMAV) are derived from blade element theory. The proposed vehicle is similar to the Harvard RoboFly that accomplished the first takeoff of an insect scale flapping wing aircraft, except that it is equipped with independently actuated wings and the vehicle center-of-gravity can be manipulated for control purposes. Using a blade element-based approach, both instantaneous and cycle-averaged forces and moments are computed for a specific type of wing beat motion that enables nearly decoupled, multi-degree-of-freedom control of the aircraft. The wing positions are controlled using oscillators whose frequencies change once per wing beat cycle. A new technique is introduced, called Split-Cycle Constant-Period Frequency Modulation, that has the desirable property of providing a high level of control input decoupling for vehicles without active angle-of-attack control. Like the RoboFly, the wing angle-ofattack variation is passive by design, and is a function of the instantaneous angular velocity of the wing in the stroke plane. A control-oriented dynamic model of the vehicle is derived, which is based on a cycle-averaged � Senior Aerospace Engineer, Control Design and Analysis Branch, 2210 Eighth Street, Ste. 21, Air Force

Michael W. Oppenheimer

Papers

Control Allocation for Over-actuated Systems

Wingbeat Shape Modulation for Flapping-Wing Micro-Air-Vehicle Control During Hover

Integrated Adaptive Guidance and Control for Re-Entry Vehicles with Flight-Test Results

Dynamics and Control of a Biomimetic Vehicle Using Biased Wingbeat Forcing Functions

Dynamics and Control of a Minimally Actuated Biomimetic Vehicle: Part I - Aerodynamic Model