Aerospace and Electrical Engineering

This paper proposes a novel sampling algorithm for digital signal processing (DSP) controlled 2 kW power factor correction (PFCs) converters, which can improve switching noise immunity greatly in average-current-control power supplies. Based on the newly developed DSP chip TMS320F240, a 2 kW PFC stage is implemented. The novel sampling algorithm shows great advantages when the converter operates at a frequency above 30 kHz.

A novel online-modeling scheme for the switched reluctance motor (SRM) using a B-spline neural network (BSNN) is proposed in this paper. A 2-D BSNN is designed to learn the nonlinear-flux-linkage characteristic of an SRM online and in real-time. Torque, incremental inductance, and back-emf estimates can be derived from the BSNN after training. The scheme does not require a priori knowledge of the SRM electromagnetic characteristics. Simulation and experimental results show that the scheme has a good estimation performance and robustness at low to medium motor speed.

A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme.

This paper describes alternative winding configurations of a short-stroke, single phase tubular permanent magnet motor for linear compressor applications. Three design variants are considered and analyzed, and their relative merits are evaluated. The open-circuit magnetic field distribution, backemf and thrust force are established analytically, and the results are compared and validated by finite element analysis and experimental measurement on a prototype motor.

To reduce torque ripple in a switched reluctance motor (SRM) by current profiling, a high-performance current controller is necessary. This study presents a high-performance current controller for SRM drives. A Bspline neural network is used to model the non-linearity of the SRM and estimate back electromotive force (EMF) and incremental inductance on-line in real time. The on-line modelling scheme does not require a priori knowledge of the machine's electromagnetic characteristics. Based on the on-line estimated parameters, a current controller with adjustable PI gains and back-EMF decoupling is implemented. The performance of the current controller has been demonstrated in simulation and experimentally using a four-phase 8/6 550 W SRM drive system.

This paper describes a design methodology to achieve optimal performance for a short-stroke, single phase tubular permanent magnet motor which drives a reciprocating vapor compressor. The steady-state characteristic of the directdrive linear motor-compressor system is analyzed, and a motor design procedure which takes into account of the effect of compressor loads under nominal operating condition is formulated. It is shown that the motor efficiency can be optimized with respect to two leading dimensional ratios. Experimental results validate the proposed design methodology.

The project dissertation is submitted in partial fulfilment of academic requirements for M.Sc. [Engg.] Degree of Coventry University in Rotating Machinery Design. This dissertation is a result of my own investigation. All sections of the text and results, which have been obtained from other sources, are fully referenced. I understand that cheating and plagiarism constitute a breach of University regulations and will be dealt with accordingly. S Si ig gn na at tu ur re e: : N Na am me e o of f t th he e S St tu ud de en nt t: : L Lo ok ke es sh h K Ku um ma ar r S So ol la an nk ki i R Re eg gi is st tr ra at ti io on n N No o: : B BS SB B0 09 91 10 00 00 02 2 D Da at te e: : 3 31 1 M Ma ar rc ch h 2 20 01 12 2 M.S Ramaiah School of Advanced Studies -Postgraduate Engineering and Management Programme (PEMP)

The capabilities of microsatellite attitude control hardware have considerably evolved during the last two decades. However, three axis attitude control software is still predominantly based on the conservative use of standard flight proven PD type controllers, which are known to be limited in terms of rapidity for a prescribed level of energy consumption. Microsatellites are therefore typically not as agile as they could be. This conservatism is due to the complexity of implementing global numerical optimisation techniques to satellite attitude control. In this paper, we consider the model of a low earth orbiting microsatellite with a four wheel configuration, where the speed of one of the wheels is kept constant to provide a momentum bias and guarantee gyroscopic stiffness to disturbances. A geometric optimal control approach is presented, which circumvents the tedious tasks of numerically solving online the nonlinear optimisation problem. The approach is based on the design of suboptimal phase space trajectories. The phase space trajectory of a standard linear controller, typically a PD law with gyro-compensation, is used as a benchmark. The proposed inverse optimal control technique is then used to enforce higher convergence rate constraints than the benchmark law, without increasing the total energy consumption. The convergence rate of a Lyapunov function under the effect of the optimal controller outperforms the convergence rate of the same function under PD control and keeps increasing until a design settling time limit is reached. Guidelines are given for the tuning of the controller. The optimal attitude control algorithms are validated on a microsatellite software simulator in collaboration with the space company Surrey Satellite Technology Limited (SSTL). The software simulator incorporates a precise model of the effects of estimation errors, noise, external disturbances, sampling and actuator dynamics. The software is similar to the flight software of typical Surrey microsatellites. The proposed techniques are characterised by low implementation complexity because the difficulty is confined to the theoretical design stage. Settling time is significantly enhanced for the same level of energy consumed as the PD type law, which was used as a benchmark without loss of generality.

The problem of conducting an inspection mission from a chaser satellite orbiting a target spaceraft is considered. It is assumed that both satellites follow nearly circular orbits. The relative orbital motion is described by the Hill-Clohessy-Wiltshire equation.

Despite the theoretical advances in optimal control, satellite attitude control is still typically achieved with linear state feedback controllers, which are less efficient but easier to implement. A switched controller is proposed, based on inverse optimal control theory, which circumvents the complex task of numerically solving online the Hamilton-Jacobi-Bellman (HJB) partial differential equation of the global nonlinear optimal control problem. The inverse optimal controller is designed to minimize the torque consumption pointwise, while imposing the stabilization rate of a linear benchmark controller. The controller is then modified by gain scheduling to achieve a tradeoff enhancement compared with the benchmark controller, while maintaining torque saturation limits. The extent to which performance can be enhanced is shown to be dependent on the controller parameters. A controller tuning analysis shows how a design settling time limit can be achieved, within the problem's constraints on the maximum torque and the total integrated torque. The proposed optimization approach is globally stabilizing and presents low implementation complexity, which is highly desirable given the limited resources onboard satellites.

Attitude control of operational satellites is still predominantly performed by standard controllers such as Proportional plus Derivative (PD) control laws, which are still preferred for implementation to the computationally intensive nonlinear optimal control techniques, representing higher implementation complexity. In this paper, an inverse optimal control approach based on phase space geometry is presented, which is easy to implement and free from numerical and computational issues. The optimal control objective is to minimize a norm of the control torque subject to a rapidity constraint on the convergence rate of a Lyapunov function, under the effect of a benchmark controller. The proposed optimization method is shown to significantly enhance the torque-rapidity trade-off compared to the benchmark controller, chosen to be a PD law then a sliding mode controller. The inverse optimal control scheme is implemented on an air bearing table experimental platform.

Failure of mechanical controllers onboard a satellite is a well-known phenomenon that has already been disastrous for several space missions. In the case studied here, we take as an example the mini-satellite UoSat-12 built by SSTL at University of Surrey. The Zaxis reaction wheel of this satellite has failed and the 3-axis control performance using magnetorquing is being very limited. The use of thrusters would involve undesired fuel consumption. As an alternative, we present here some latest theory, which shows how full 3-axis control can still be achieved, using the two remaining reaction wheels from a standard orthogonal 3-wheel configuration. Using a novel nonlinear time invariant and discontinuous approach, we show that the attitude is precisely and rapidly altered, without transient oscillations, to the required earth pointing. The case of a small nonzero total momentum is illustrated. One consequence of these results is that a fully redundant 3-axis control can be envisaged using a 3-wheel configuration.

This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

A method requiring low-computational overhead is presented which generates low-torque reference motions between arbitrary orientations for spin-stabilized spacecraft. The initial stage solves a constrained optimal control problem deriving analytical solutions for a class of smooth and feasible reference motions. Specifically, for a quadratic cost function an application of Pontryagin's maximum principle leads to a completely integrable Hamiltonian system that is, exactly solvable in closed-form, expressed in terms of several free parameters. This is shown to reduce the complexity of a practical motion planning problem from a constrained functional optimization problem to an unconstrained parameter optimization problem. The generated reference motions are then tracked using an augmented quaternion feedback law, consisting of the sum of a proportional plus derivative term and a term to compensate nonlinear dynamics. The method is illustrated with an application to re-point a spin-stabilized agile micro-spacecraft using zero propellant. The low computational overhead of the method enhances its suitability for on-board motion generation.

The first stage in any control system is to be able to accurately estimate the system's state. However, some types of measurements are ambiguous (non-injective) in terms of state. Existing algorithms for such problems, such as Monte Carlo methods, are computationally expensive or not robust to such ambiguity. We propose the Box Regularized Particle Filter (BRPF) to resolve these problems. Based on previous works on box particle filters, we present a more generic and accurate formulation of the algorithm, with two innovations: a generalized box resampling step and a kernel smoothing method, which is shown to be optimal in terms of Mean Integrated Square Error. Monte Carlo simulations demonstrate the efficiency of BRPF on a severely ambiguous and non-linear estimation problem, that of Terrain Aided Navigation. BRPF is compared to the Sequential Importance Resampling Particle Filter (SIR-PF), Monte Carlo Markov Chain (MCMC), and the original Box Particle Filter (BPF). The algorithm outperforms existing methods in terms of Root Mean Square Error (e.g., improvement up to 42% in geographical position estimation with respect to the BPF) for a large initial uncertainty. The BRPF reduces the computational load by 73% and 90% for SIR-PF and MCMC, respectively, with similar RMSE values. This work offers an accurate (in terms of RMSE) and robust (in terms of divergence rate) way to tackle state estimation from ambiguous measurements while requiring a significantly lower computational load than classic Monte Carlo and particle filtering methods.

Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.

In this paper a continuous attitude tracking control law is derived directly on the rotation group SO(3). The proposed control law is shown to reduce the closed-loop attitude dynamics to a linear oscillator description of the eigen-axis error, without the need for a small angle approximation. The main practical benefit of this is that the gains can be easily tuned to drive this eigen-axis error to zero exponentially fast and with a damped response without oscillations. The approach uses geodesic error metrics on the rotation group and the angular velocity to construct a Lyapunov function. The time-derivative of this Lyapunov function is control dependent and a continuous control is selected to guarantee asymptotic tracking of the reference motion. Furthermore, the closed-loop system, with this rotation-matrix based feedback control applied, is converted to its quaternion form and further reduced to an eigen-axis error description of the dynamics. This reduction reveals a simple meth...

GNSS denied IMU correction is a practical challenge in aerospace vehicle navigation. In the context of several vehicles flying in formation, navigation accuracy can be enhanced by communication between the vehicles. In this paper, a collaborative navigation strategy is presented to deal with coarse and ambiguous measurements. An absolute navigation filter provides a first estimate of the navigation solution, while a relative observer rebuilds the neighbors relative states from embedded seekers. A high-level Master Filter fuses information provided by those two low-level filters to enhance the navigation solution. Absolute navigation measurements are terrain elevation data correlated with a Digital Elevation Model map. Since they are highly ambiguous and nonlinear, they are processed by a Box Regularized Particle Filter. The relative measurements under consideration suffer a high level of uncertainty, especially on the relative distance between vehicles. By fusing all uncertain data,...

Failure of mechanical controllers onboard a satellite is a well-known phenomenon that has already been disastrous for several space missions. In the case studied here, we take as an example the mini-satellite UoSat-12 built by SSTL at University of Surrey. The Zaxis reaction wheel of this satellite has failed and the 3-axis control performance using magnetorquing is being very limited. The use of thrusters would involve undesired fuel consumption. As an alternative, we present here some latest theory, which shows how full 3-axis control can still be achieved, using the two remaining reaction wheels from a standard orthogonal 3-wheel configuration. Using a novel nonlinear time invariant and discontinuous approach, we show that the attitude is precisely and rapidly altered, without transient oscillations, to the required earth pointing. The case of a small nonzero total momentum is illustrated. One consequence of these results is that a fully redundant 3-axis control can be envisaged ...

Future space telescopes with diameter over 20 m will require in-space assembly. High-precision formation flying has very high cost and may not be able to maintain stable alignment over long periods of time. We believe autonomous assembly is a key enabler for a lower cost approach to large space telescopes. To gain experience, and to provide risk reduction, we propose a demonstration mission to demonstrate all key aspects of autonomous assembly and reconfiguration of a space telescope based on multiple mirror elements. The mission will involve two 3U CubeSat-like nanosatellites (“MirrorSats”) each carrying an electrically actuated adaptive mirror, and each capable of autonomous un-docking and re-docking with a small central “9U” class nanosatellite core, which houses two fixed mirrors and a boom-deployed focal plane assembly. All three spacecraft will be launched as a single ~40kg microsatellite package.