Application of robust control in unmanned vehicle flight control system design

The robust loop-shaping control methodology is applied in the flight control system design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle. Detailed linear models for the full operational flight envelope of the air vehicle are developed. The nominal and worst-case models are determined using the v-gap metric. The effect of neglecting subsystems such as actuators and/or computation delays on modelling uncertainty is determined using the v-gap metric and shown to be significant. Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF controllers were carried out. The Hanus command signal conditioning technique is also implemented to overcome actuator saturation and windup. The robust control system is then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its capability of launch stabilization in extreme cross-wind conditions, control effectiveness in climb, and navigation precision through the prescribed 3D flight path in level cruise. Robust performance and stability of the single-point non-scheduled control law is also demonstrated throughout the full operational flight envelope the air vehicle is capable of and for all flight phases and beyond, to severe launch conditions, such as 33knots crosswind and exaggerated CG shifts. The robust TDF control law is finally compared with the classical PMC law where the actual number of variables to be manipulated manually in the design process are shown to be much less, due to the scheduling process elimination, although the size of the final controller was much higher. The robust control law performance superiority is demonstrated in the non-linear simulation for the full flight envelope and in extreme flight conditions

Geometric algorithms for input constrained systems with application to flight control.

In this thesis novel numerical algorithms are developed to solve some problems of analysis and control design for unstable linear dynamical systems having their input constrained by maximum amplitude and rate of the control signals. Although the results obtained are of a general nature, all the problems considered are induced by flight control applications. Moreover, all these problems are stated in terms of geometry, and because of this their solution in the thesis was effectively achieved by geometrically-oriented methods. The problems considered are mainly connected with the notions of the controllable and stability regions. The controllable region is defined as the set of states of an unstable dynamical system that can be stabilized by some realizable control action. This region is bounded due to input constraints and its size can serve as a controllability measure for the control design problem. A numerical algorithm for the computation of two-dimensional slices of the region is proposed. Moreover, the stability region design is also considered. The stability region of the closed-loop system is the set of states that can be stabilized by a particular controller. This region generally utilizes only a part of the controllable region. Therefore, the controller design objective may be formulated as maximizing this region. A controller that is optimal in this sense is proposed for the case of one and two exponentially unstable open-loop eigenvalues. In the final part of the thesis a linear control allocation problem is considered for overactuated systems and its real-time solution is suggested. Using the control allocation, the actuator selection task is separated from the regulation task in the control design. All fault detection and reconfiguration capabilities are concentrated in one special unit called the control allocator, while a general control algorithm, which produces 'virtual' input for the system, remains intact. In the case of an actuator fault, only the control allocation unit needs to be reconfigured and in many cases it can generate the same 'virtual' input using a different set of control effectors. A novel control allocation algorithm, which is proposed in the thesis, is based on multidimensional interval bisection techniques

Test-bed for feedback control of color of light of LED lamps

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia de Controle e Automação.O presente projeto foi desenvolvido no Departamento de Física e Engenharia Óptica do Rose-Hulman Institute of Technology, em Terre Haute, estado de Indiana, Estados Unidos da América. O instituto é um parceiro do Smart Lighting Engineering Research Center (SLERC - Centro de Pesquisa em Iluminação Inteligente), um dos centros de excelência do National Science Foundation (NSC – Fundação Nacional de Ciência dos Estados Unidos), liderado pelo Rensselaer Polytechnic Institute (RPI), de Nova Iorque. Motivados pelos recentes descobrimentos sobre o impacto da iluminação artificial, onipresente no cotidiano do homem moderno, na saúde humana, notadamente sobre os ritmos circadianos, buscamos desenvolver nesse projeto um sistema que seja capaz de fornecer luz com cor controlável. O objetivo desse sistema é facilitar os estudos sendo feitos sobre os efeitos que a cor da iluminação tem sobre a saúde e o humor do ser humano. Este projeto também busca comprovar que tal obetivo pode ser alcançado com tecnologias que já possuam um custo relativamente baixo, que permita que no futuro o conceito seja aplicado a sistemas de iluminação ordinários. Para isso, usaremos lampadas construídas com tecnologia baseada em LEDs (Diodos Emissores de Luz), que possui várias vantagens como maior eficiência energética e tamanho reduzido, além de ser a mais apropriada para o controle de cor. Diferentemente do que tem sido feito em projetos semelhantes, utilizaremos controladores dinamicos em malha fechada para garantir que a cor da luz emitida se mantenha dentro das especificações, mesmo com a presença de perturbações, como a luz solar.One of the many radical changes that took place in the last century was the spread of artificial lighting. This enabled society to carry out activities that were previously restricted to day time and open environments, such as social and economic, indoors and throughout night. Recent discoveries, however, have shown that the exposure to artificial light for abnormal periods may have negative impacts on health. One of the fields that have drawn the attention is how color of light plays a role on human health and mood, notably on the circadian rhythms. This project aims to develop a system that is able to source light with controllable color and study the best ways to achieve that, using LEDs lamps, which, in addition to being suitable to such control, have many other advantages, mainly higher energy efficacy. It was developed in the context of the Smart Lighting Engineering Research Center (SLERC), a center of excellence of the US National Science Foundation, led by Rensselaer Polytechnic Institute (RPI). It is dedicated to “The holistic integration of advanced light sources, sensors, and adaptive control architectures”. Student and faculty at Rose-Hulman are participating in smart lighting research as an outreach partner with the SLERC. The final concept innovates by performing the light control using dynamic closed loop controller, instead of lookup tables, strategy that has been used in similar projects. It also must be composed of inexpensive technologies

Application of robust control in unmanned vehicle flight control system design

The robust loop-shaping control methodology is applied in the flight control system design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle. Detailed linear models for the full operational flight envelope of the air vehicle are developed. The nominal and worst-case models are determined using the v-gap metric. The effect of neglecting subsystems such as actuators and/or computation delays on modelling uncertainty is determined using the v-gap metric and shown to be significant. Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF controllers were carried out. The Hanus command signal conditioning technique is also implemented to overcome actuator saturation and windup. The robust control system is then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its capability of launch stabilization in extreme cross-wind conditions, control effectiveness in climb, and navigation precision through the prescribed 3D flight path in level cruise. Robust performance and stability of the single-point non-scheduled control law is also demonstrated throughout the full operational flight envelope the air vehicle is capable of and for all flight phases and beyond, to severe launch conditions, such as 33knots crosswind and exaggerated CG shifts. The robust TDF control law is finally compared with the classical PMC law where the actual number of variables to be manipulated manually in the design process are shown to be much less, due to the scheduling process elimination, although the size of the final controller was much higher. The robust control law performance superiority is demonstrated in the non-linear simulation for the full flight envelope and in extreme flight conditions.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Adaptation and Learning for Manipulators and Machining

This thesis presents methods for improving the accuracy and efficiency of tasks performed using different kinds of industrial manipulators, with a focus on the application of machining. Industrial robots offer a flexible and cost-efficient alternative to machine tools for machining, but cannot achieve as high accuracy out of the box. This is mainly caused by non-ideal properties in the robot joints such as backlash and compliance, in combination with the strong process forces that affect the robot during machining operations. In this thesis, three different approaches to improving the robotic machining accuracy are presented. First, a macro/micro-manipulator approach is considered, where an external compensation mechanism is used in combination with the robot, for compensation of high-frequency Cartesian errors. Two different milling scenarios are evaluated, where a significant increase in accuracy was obtained. The accuracy specification of 50 μm was reached for both scenarios. Because of the limited workspace and the higher bandwidth of the compensation mechanism compared to the robot, two different mid-ranging approaches for control of the relative position between the robot and the compensator are developed and evaluated. Second, modeling and identification of robot joints is considered. The proposed method relies on clamping the manipulator end effector and actuating the joints, while measuring joint motor torque and motor position. The joint stiffness and backlash can subsequently be extracted from the measurements, to be used for compensation of the deflections that occur during machining. Third, a model-based iterative learning control (ILC) approach is proposed, where feedback is provided from three different sensors of varying investment costs. Using position measurements from an optical tracking system, an error decrease of up to 84 % was obtained. Measurements of end-effector forces yielded an error decrease of 55 %, and a force-estimation method based on joint motor torques decreased the error by 38 %. Further investigation of ILC methods is considered for a different kind of manipulator, a marine vibrator, for the application of marine seismic acquisition. A frequency-domain ILC strategy is proposed, in order to attenuate undesired overtones and improve the tracking accuracy. The harmonics were suppressed after approximately 20 iterations of the ILC algorithm, and the absolute tracking error was r educed by a factor of approximately 50. The final problem considered in this thesis concerns increasing the efficiency of machining tasks, by minimizing cycle times. A force-control approach is proposed to maximize the feed rate, and a learning algorithm for path planning of the machining path is employed for the case of machining in non-isotropic materials, such as wood. The cycle time was decreased by 14 % with the use of force control, and on average an additional 28 % decrease was achieved by use of a learning algorithm. Furthermore, by means of reinforcement learning, the path-planning algorithm is refined to provide optimal solutions and to incorporate an increased number of machining directions

Flight testing a V/STOL aircraft to identify a full-envelope aerodynamic model

Flight-test techniques are being used to generate a data base for identification of a full-envelope aerodynamic model of a V/STOL fighter aircraft, the YAV-8B Harrier. The flight envelope to be modeled includes hover, transition to conventional flight and back to hover, STOL operation, and normal cruise. Standard V/STOL procedures such as vertical takeoff and landings, and short takeoff and landings are used to gather data in the powered-lift flight regime. Long (3 to 5 min) maneuvers which include a variety of input types are used to obtain large-amplitude control and response excitations. The aircraft is under continuous radar tracking; a laser tracker is used for V/STOL operations near the ground. Tracking data are used with state-estimation techniques to check data consistency and to derive unmeasured variables, for example, angular accelerations. A propulsion model of the YAV-8B's engine and reaction control system is used to isolate aerodynamic forces and moments for model identification. Representative V/STOL flight data are presented. The processing of a typical short takeoff and slow landing maneuver is illustrated