In this thesis, a new guidance method for fighter aircrafts and a new guidance method for missiles are developed. Also, guidance and control systems of the aircraft and the missile used are designed to simulate the generic engagement scenarios between the missile and the aircraft. Suggested methods have been tested under excessive simulation studies. The aircraft guidance method developed here is a rule based missile evasion method. The main idea to develop this method stems from the maximization of the miss distance for an engagement scenario between a missile and an aircraft. To do this, an optimal control problem with state and input dependent inequality constraints is solved and the solution method is applied on different problems that represent generic scenarios. Then, the solutions of the optimal control problems are used to extract rules. Finally, a method that uses the interpolation of the extracted rules is given to guide the aircraft. The new guidance method developed for missiles is formulated by modifying the classical proportional navigation guidance method using the position estimates. The position estimation is obtained by utilization of a Kalman based filtering method, called interacting multiple models.

No / This paper presents an investigation into the challenges in implementing a hard real-time optimal non-stationary system using general regression neural network (GRNN). This includes investigation into the dynamics of the problem domain, discretisation of the problem domain to reduce the computational complexity, parameters selection of the optimization algorithm, convergence guarantee for real-time solution and off-line optimization for real-time solution. In order to demonstrate these challenges, this investigation considers a real-time optimal missile guidance algorithm using GRNN to achieve an accurate interception of the maneuvering targets in three-dimension. Evolutionary Genetic Algorithms (GAs) are used to generate optimal guidance training data set for a large missile defense space to train the GRNN. The Navigation, Constant of the Proportional Navigation Guidance and the target position at launching are considered for optimization using GAs. This is achieved by minimizing the. miss distance and missile flight time. Finally, the merits of the proposed schemes for real-time accurate interception are presented and discussed through a set of experiments. (C) 2012 Elsevier Ltd. All rights reserved.

Ce mémoire de thèse traite du développement des dynamiques et des lois de commande de vol d’un projectile d’artillerie gyrostabilisé guidé par une tête découplée. Un modèle non linéaire du projectile est proposé, et sert à calculer un modèle linéarisé de la dynamique de roulis du nez et un modèle q-LPV des chaînes de tangage et de lacet à paramètres fortement variants. Les incertitudes de modélisation sont prises en compte pour concevoir l’autopilote. Des propriétés importantes des projectiles gyrostabilisés, qui sont liées au couplage dynamique tangage/lacet, aux modes internes et à la stabilité, sont mises en valeur grâce au modèle q-LPV. En vue de l’utiliser pour calculer une loi de commande, la dimension de son vecteur des paramètres est réduite et la position des capteurs intégrés dans le nez est considérée. Un seul correcteur linéaire est suffisant pour la dynamique de l’angle de roulis du nez alors qu’une stratégie systématique de commande par séquencement de gains basée sur une linéarisation est élaborée séparément pour générer un correcteur séquencé des facteurs de charge de tangage et de lacet. Des structures de commande fixées d’ordre réduit sont conçues en appliquant la même approche de synthèse linéaire H∞ par façonnage de gain de boucle pour les axes de roulis et de tangage/lacet. De très bonnes propriétés de performance et de robustesse en boucle fermée, comparables à celles fournies par des correcteurs d’ordre plein, sont obtenues. Finalement, l’efficacité de l’autopilote augmenté d’une loi de guidage par navigation proportionnelle pure est vérifiée via de nombreuses simulations non linéaires de trajectoires. Ces dernières correspondent à des scénarios de vol nominaux d’interception de cibles balistiques, non balistiques immobiles, ou manœuvrantes, ainsi qu’à des scénarios considérant des perturbations sur les conditions de tir ou sur les dynamiques du projectile guidé / This thesis addresses the development of the flight dynamics and control laws for an artillery spin-stabilized projectile equipped with a decoupled guidance nose. A projectile nonlinear model is discussed, and it is used for computing a linearized model of the nose roll dynamics along with a q-LPV model of the highly parameter-varying pitch/yaw-dynamics. Modeling uncertainty is taken into account for autopilot design. Important properties specific to spin-stabilized projectiles, which are relevant to pitch/yaw-channel cross-coupling, internal modes and stability, are highlighted using the q-LPV model. In order to use the latter for calculating a control law, the dimension of its parameter vector is reduced and the position of the nose-embedded sensors is considered. A single linear controller is sufficient for the nose roll angle dynamics whereas a systematic linearization-based gain-scheduled control strategy is separately devised to provide a pitch/yaw-axis load factor gain-scheduled controller. Controllers of reduced-order fixed structures are computed by applying the same H∞ linear design loop-shaping approach for the roll and pitch/yaw-axes. Very good closed-loop performance and robustness properties, which are similar to those provided by full order controllers, are obtained. Finally, the effectiveness of the autopilot augmented by a pure proportional navigation guidance law is verified through a variety of nonlinear trajectory simulations. The latter correspond to nominal flight scenarios with ballistic, non-ballistic stationary, and maneuvering interception points, and to scenarios with perturbed launch conditions or guided projectile dynamics

The ability to gather and process information regarding the condition of forest fires is essential to cost-effective, safe, and efficient fire fighting. Advances in sensory and autopilot technology have made miniature unmanned aerial systems (UASs) an important tool in the acquisition of information. This thesis addresses some of the challenges faced when employing UASs for forest-fire perimeter surveillance; namely, perimeter tracking, cooperative perimeter surveillance, and path planning. Solutions to the first two issues are presented and a method for understanding path planning within the context of a forest-fire environment is demonstrated. Both simulation and hardware results are provided for each solution.