Model Predictive Control (MPC) is an application of control that is highly popular due to its sensible approach and its ease of implementation. These qualities give MPC an advantage over Linear Quadratic (LQ) control, even though LQ will result in the optimal result where feasible. Recent advancements have resulted in greater computational power, which has given rise to the development of more complicated MPC algorithms, but there are instances when the complexity of the calculations involved will result in the amount of computations involved or ill-conditioning of the problem.

This thesis describes the design and implementation of a positional-control scheme for a limited angle torque motor, using a digital signal processor (DSP).

Les systèmes à grande échelle intégrées qui travaillent ensemble pour une mission commune sont connus sous le nom de Systèmes de Systèmes (SdS). Ce travail propose une méthode de modélisation pour une classe de SdS, à savoir, les systèmes mécatronique, en utilisant l’approche de Bond graph. Cette approche est appliquée à un Système de Transport Intelligent par la modélisation de la dynamique du trafic de véhicules autonomes intelligent; où les communications de véhicule à véhicule et de véhicule à infrastructure sont considérées. Un tel ensemble de véhicules autonomes décrit l'organisation d'un SdS. La dynamique du trafic est modélisée sur trois niveaux d'abstraction, à savoir: sous-microscopique, microscopique, et macroscopique. Par la suite, les trois niveaux sont combinés pour développer un modèle multi-niveaux de la dynamique du trafic en utilisant la même approche du Bond graph. Le modèle est simulé dans des scénarios normaux et défectueux. Ensuite, le modèle est validé sur un simulateur en temps réel de la dynamique du véhicule. En plus, des expériences réelles sur véhicules autonomes intelligent sont effectuées pour valider le modèle. Enfin, le modèle est utilisé pour développer une stratégie de supervision du SdS de trafic basé sur l'analyse comportementale et structurelle du modèle bond graph. / Large-scale integrated systems working collectively for a common mission are known as Systems of Systems (SoS). In the present work, we propose a modeling method for a class of SoS, namely mechatronic systems, based on the Bond graph modeling approach. The proposed approach is applied to an Intelligent Transportation System (ITS) by modeling the traffic dynamic of Intelligent Autonomous Vehicles (IAVs); where Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications are considered. Such set of autonomous vehicles describe the organization of a SoS. The traffic dynamic is modeled at three abstraction levels namely: submicroscopic, microscopic, and macroscopic levels. Subsequently, the three levels are combined to develop a multilevel model of the traffic dynamic using the same Bond graph approach. The model is simulated for normal and faulty scenarios. Then, the model is validated on a real-time simulator of vehicle dynamics. In addition, real experiments on IAVs are performed to validate the model. Finally, the model is used to develop a supervision strategy for the traffic SoS based on the behavioral and structural analysis of the Bond graph model.

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This thesis investigates the concept and design of a portable on-line transfer function analyser (TFA). It is eminently suitable for the identification of plants and other controlled feedback systems in which normal operating records are available. A point by point representation in the frequency domain, requiring a maximum of three records, allows Nyquist plots to be carried out, either visually or by plotter facilities. The basic theory relies heavily upon statistical concepts whereby, least squares estimates of the transfer function are obtained from a combination of heterodyning, exact filtering and adaptive loops. The resultant output, on both channels (real and imaginary), is the culmination of the solution to two linear differential equations with stochastic coefficients, so mechanised when the adaptive loops reach a stable equilibrium. Throughout, emphasis is placed upon the electronics combining the best of analog and digital techniques, in order that six parallel paths may be analysed in similar mode. This is especially true of the heterodyning and filtering operations. Practical shortcomings of the instrument noted by comparing estimates with those from the best currently available commercial apparatus, operating on deterministic signals. Examples of a feedback loop, subjected to both deterministic and random stimuli, with and without the presence of extraneous noise sources, are used to illustrate the ease and simplicity by which the instrument can be used in place of complex computing schemes, which tend, in consequence, to be solely of local academic interest. The practical features of the thesis have led to the submission of four papers to the technical press. Two of them deal, exclusively, with a capacitor ratio commutated filter – not apparently described in publications to date - which is also the subject of a proposed patent application in conjunction with NRDC. It is intended, in the near future, to submit the complete instrument as the basis for a second patent proposal.

Two major issues in the design of multi-robot systems are those of communication and co-ordination. Communication ithin real world environments cannot always be guaranteed. A multi-robot system must, therefore, be able to continue with its task in the absence of communication between team members. Co-ordination of multiple robots to perform a specific task involves team members being able to make decisions as a single entity and as a member of a team. The co-ordination needs to be robust enough to handle failures within the system and unknown phenomena within the environment. In this thesis, the problems of communication and co-ordination are discussed and a new type of multi-robot system is introduced in an effort to solve the inherent difficulties within communication and co-ordination of multi-robot systems. The co-ordination and communication strategy is based upon the concept of sharing potential field information within dynamic local groups. Each member of the multi-robot system creates their own potential field based upon individual sensor readings. Team members that are dynamically assigned to local groups share their individual potential fields, in order to create a combined potential field which reduces the effect of sensor noise. It is because of this, that team members are able to make better decisions. A number of experiments, both in simulation and in laboratory environments, are presented. These experiments compare the performance of the system against a nonsharing control and a hybrid system made up of a global path planner and a reactive motor controller. It is demonstrated that the new system significantly outperforms these other methods in a search type problem. From this, it is concluded that the novel system proposed in this thesis successfully tackled the search problem, and that it should also be possible for the system to be applied to a number of other common multi-robot problems.

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