To control the speed of an overactuated vehicle there may be many possible ways to use the actuators of the car achieving the same outcome. The actuators in an ordinary car is a combustion engine and a friction brake. In some cases it is trivial how to coordinate actuators for the optimal result, but in many cases it is not. The goal with the thesis is to investigate if it is possible to achieve the same or improved performance with a more sophisticated control structure than today's, using a model predictive controller. A model predictive controller combines the possibility to predict the outcome through an open-loop controller with the stability of a closed loop controller and gives the optimal solution for a finite horizon optimization problem. A simple model of the longitudinal dynamics of a car is developed and used in the model predictive controller framework. This is then used in simulations and in a real car. It is shown that it is possible to replace the current controller structure with a model predictive controller, but there are advantages and disadvantages with the new control structure.

The work presented in the thesis concerns the design and development of a novel thruster fault diagnosis and accommodation system (PDAS) for overactuated, open-frame underwater vehicles. The remotely operated vehicles (ROVs) considered in this thesis have four thrusters for motion in the horizontal plane with three controllable degrees of freedom (DoF). Due to the redundancy resulting from this configuration, for the case of a partial fault or a total fault in a single thruster it is possible to reallocate control among operable thrusters in order that the ROV pilot is able to maintain control of the faulty ROV and to continue with missions. The proposed PDAS consists of two subsystems: a fault diagnosis subsystem (FDS) and a fault accommodation subsystem (FAS). The FDS uses fault detector units to monitor thruster states. Robust and reliable interrogation of thruster states, and subsequent identification of faults, is accomplished using methods based on the integration of selforganising maps and fuzzy logic clustering. The FAS uses information provided by the FDS to perform an appropriate redistribution of thruster demands in order to accommodate faults. The FAS uses a hybrid approach for control allocation, which integrates the pseudoinverse method and the fixed-point iterations method. A control energy cost function is used as the optimisation criteria. In fault-free and faulty cases the FAS finds the optimal solution, which minimises this criteria. The concept of feasible region is developed in order to visualise thruster velocity saturation bounds. The PDAS provides a dynamic update of saturation bounds using a complex three-dimensional visualisation of the feasible region (attainable command set), such that the ROV pilot is informed with the effects of thruster fault accommodation, incorporated in the new shape of the attainable command set. In this way the ROV pilot can easy adapt to newly created changes and continue the mission in the presence of a fault. The prototype of the PDAS was developed in the MATLAB environment as a Simulink model, which includes a nonlinear model of an ROV with 6 DOF, propulsion system and a hand control unit. The hand control unit was simulated in hardware using a joystick as input device to generate command signals. Different fault conditions are simulated in order to investigate the performance of the PDAS. A virtual underwater world was developed, which enabled tuning, testing and evaluation of the PDAS using simulations of two underwater vehicles (FALCON, Seaeye Marine Ltd. and URIS, University of Girona) in a 'realistic' underwater environment. The performance of the PDAS was demonstrated and evaluated via tank trials of the FALCON ROV in QinetiQ Ocean Basin Tank at Haslar, where the existing control software was enhanced with the PDAS algorithm. The results of real-world experiments confirmed the effectiveness of the PDAS in maintaining vehicle manoeuvrability and in preserving the vehicle mission in the presence of thruster faults.