A high-precision position-based calibration table as the reference for angular accelerometer calibration experiment

With the role of angular accelerometers in future fault-tolerant flight control systems, an in-depth evaluation of their performance then becomes a critical issue from the perspective of control system design. In this paper, a position-based calibration table is utilized to provide a sufficiently accurate angular acceleration reference in the...

Nonlinear and fault-tolerant flight control using multivariate splines

This paper presents a study on fault tolerant flight control of a high performance aircraft using multivariate splines. The controller is implemented by making use of spline model based adaptive nonlinear dynamic inversion (NDI). This method, indicated as SANDI, combines NDI control with nonlinear control allocation based on an onboard...

A sparse collocation method for solving time-dependent HJB equations using multivariate B-splines

This paper presents a sparse collocation method for solving the time-dependent Hamilton–Jacobi–Bellman (HJB) equation associated with the continuous-time optimal control problem on a fixed, finite timehorizon with integral cost functional. Through casting the problem in a recursive framework using the value iteration procedure, the value...

Determination of trim curves for a flapping-wing MAV

This paper presents the results of a series of flight tests conducted in order to assess the steady-state flight characteristics and basic control behaviour of the DelFly, a flapping-wing micro aerial vehicle (FWMAV). Flights were conducted in an indoor motion tracking facility and included steady-level flight at a range of different velocities...

An optimal control framework for estimating autopilot safety margins

This paper presents an optimal control framework to determine a collection of open-loop command signals that mathematically guarantees operation of an aircraft within certain prescribed state constraints. The framework is specifically applied to estimate margins for the reference command inputs of aircraft autopilot systems, so that safe...

Nonlinear Multivariate Spline-Based Control Allocation for High-Performance Aircraft

High performance flight control systems based on the nonlinear dynamic inversion (NDI) principle require highly accurate models of aircraft aerodynamics. In general, the accuracy of the internal model determines to what degree the system nonlinearities can be canceled; the more accurate the model, the better the cancellation, and with that, the...

A Hybrid Sensor Based Backstepping Control Approach with its Application to Fault-Tolerant Flight Control

Recently, an incremental type sensor based backstepping (SBB) control approach, based on singular perturbation theory and Tikhonov’s theorem, has been proposed. This Lyapunov function based method uses measurements of control variables and less model knowledge, and it is not susceptible to the model uncertainty caused by fault scenarios. In this...

Near-Hover Flapping Wing MAV Aerodynamic Modelling: A linear model approach

Online Aerodynamic Model Identification using a Recursive Sequential Method for Multivariate Splines

Avoiding high computational loads is essential to online aerodynamic model identi- fication algorithms, which are at the heart of any model-based adaptive flight control system. Multivariate simplex B-spline (MVSB) methods are excellent function approximation tools for modeling the nonlinear aerodynamics of high performance aircraft. However,...

Wavefront reconstruction in adaptive optics systems using nonlinear multivariate splines

This paper presents a new method for zonal wavefront reconstruction (WFR) with application to adaptive optics systems. This new method, indicated as Spline based ABerration REconstruction (SABRE), uses bivariate simplex B-spline basis functions to reconstruct the wavefront using local wavefront slope measurements. The SABRE enables WFR on...

A novel adaptive kernel method with kernel centers determined by a support vector regression approach

The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an algorithm, namely improved recursive reduced least...

Validating the Multidimensional Spline Based Global Aerodynamic Model for the Cessna Citation II

The validation of aerodynamic models created using flight test data is a time consuming and often costly process. In this paper a new method for the validation of global nonlinear aerodynamic models based on multivariate simplex splines is presented. This new method uses the unique properties of the multivariate simplex splines, a recent type of...

Global Nonlinear Model Identification with Multivariate Splines

At present, model based control systems play an essential role in many aspects of modern society. Application areas of model based control systems range from food processing to medical imaging, and from process control in oil refineries to the flight control systems of modern aircraft. Central to a model based control system is a mathematical...

Differential constraints for bounded recursive identification with multivariate splines

The ability to perform online model identification for nonlinear systems with unknown dynamics is essential to any adaptive model-based control system. In this paper, a new differential equality constrained recursive least squares estimator for multivariate simplex splines is presented that is able to perform online model identification and...

A Multidimensional Spline Based Global Nonlinear Aerodynamic Model for the Cessna Citation II

A new method is proposed for the identification of global nonlinear models of aircraft non-dimensional force and moment coefficients. The method is based on a recent type of multivariate spline, the multivariate simplex spline, which can accurately approximate very large, scattered nonlinear datasets in any number of dimensions. The new...

A new approach to linear regression with multivariate splines

A new methodology for creating highly accurate, static nonlinear maps from scattered, multivariate data is presented. This new methodology uses the B-form polynomials of multivariate simplex splines in a new linear regression scheme. This allows the use of standard parameter estimation techniques for estimating the B-coefficients of the...