Autonomous mining machines can provide improvements in several desired aspects of the mining industry, ranging from improved safety and personnel expenses to machine utilization and fleets of machines working together. For these autonomous machines, control systems are essential. This thesis examines three different control strategies, PD, LQ, and PID, for a Boomer E drill rig from Epiroc. In order to develop control systems without spending valuable time on real world implementation and testing, simulations of control strategies are common. If a system is to be simulated, a model of the system is required which captures the dynamics of interest. The thesis examines different polynomial models for modeling of the dynamics of a SmartROC D65 drill rig from Epiroc.

Gas turbines are widely used as power sources in many industrial and transportation applications. This kind of engine is the most preferred prime movers in aircrafts, power plants and some marine vehicles. They have different configurations according to their mechanical constructions such as turbo-prop, turbo-shaft, turbojet, etc. These engines have different efficiencies and specifications and some advantages and disadvantages compared to Otto-Cycle engines. In this thesis, a small turbojet engine is investigated in order to find different control algorithms. AMT Olympus HP small turbojet engine has been used to determine the mathematical model of a gas turbine engine. Some important experimental data were taken from AMT Olympus engine by making many experiments. All components of the engine have been modeled by using laws of thermodynamics and some arithmetic calculations such as numerical solution of nonlinear differential equations, digitizing compressor and turbine map etc. This mathematical model is employed to create control algorithm of the engine. At first, standard control strategies had been considered such as P (proportional), PI (proportional integral), and PID (proportional-integral-differential) controllers. Because of the nonlinearities in gas turbines, standard control algorithms are not commonly used in literature. At the second stage fuzzy logic controllers have been designed to control the engine efficiently. This control algorithm was combined with mathematical of the engine in MATLAB environment and input-output relations were investigated. Finally, fuzzy logic control algorithm was embedded into an electronic controller.

The increasing penetration of renewable energy in the power system grid makes it one of the most important topics in electricity generation, now and into the future. Tidal current energy is one of the most rapidly growing technologies for generating electric energy. Within that frame, tidal current energy is surging to the fore. Forecasting is the first step in dealing with future generations of the tidal current power systems. The doubly-fed induction generator (DFIG) and the direct drive permanent magnet synchronous generator (DDPMSG) are the most commonly used generators associated with tidal current turbines. The aim of the present work is to propose a forecasting technique for tidal current speed and direction and to develop dedicated control strategies for the most commonly used generators, enabling the turbines to act as an active component in the power system. This thesis is divided into two parts. The first part proposes a hybrid model of an artificial neural network (ANN) and a Fourier series model based on the least squares method (FLSM) for monthly forecasting of tidal current speed magnitude and direction. The proposed hybrid model is highly accurate and outperforms both the ANN and the FLSM alone. The model is validated and shown to perform better than other models currently in use. This study was done using data collected from the Bay of Fundy, Nova Scotia, Canada, in 2008. The second part of the thesis describes the overall dynamic models of the tidal current turbine driving either a DFIG or a DDPMSG connected to a single machine infinite bus system, including controllers used to improve system stability. Two models are tested and validated, and two proportional integral (PI) controllers are proposed for each machine to control the output power of the tidal current turbine. The controllers are tested using a small signal stability analysis method for the models, and prove the robustness of the tidal current turbine using two different types of generators over those without controllers. The controller gain ranges are also investigated to establish zones of stability. Overall results show the advantages of using a DDPMSG over a DFIG.

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Unmanned Underwater Vehicles (UUV) in open-seas are highly nonlinear with system motions. Because of the complex interaction of the body with environment it is difficult to control them efficiently. Linearization is applied to system in order to design controllers developed for linear systems. To overcome the effects of disturbances, a mathematical model which will compensate all disturbances and effects of linearization is required. In this study first a mathematical model is formed wherein the linear and nonlinear hydrodynamic coeffi- cients are calculated with strip theory. After the basic mathematical model is developed, it is simplified and decoupled into speed, steering and diving subsystems. Consequently PID (Proportional Derivative Integral), SMC (SlidingMode Control) and LQR (Linear Quadratic Regulator)/LQG (Linear Quadratic Gaussian) control methods can be applied on each subsystem to design controllers. Some of the system parameters can be estimated from state vector data based on measurements using the methods of linear sequential estimation and genetic algorithms. As for the final part of the study, an online obstacle avoidance algorithm which avoids local optimums using Boolean operators is presented. In addition a simple guidance algorithm is suggested for waypoint navigation. Due to the fact that ULISAR UUV is still on construction phase, we were unable to test our algorithms. But in the near future, we plan to study all these algorithms on the UUV ULISAR.

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This thesis aims to propose multiple methods for performing a hardware-in-the-loop simulation, providing the hardware and software tools necessary for design and execution. For this purpose, methods of modeling commonly encountered dynamical system components are explored and techniques suitable for calculating the states of the modeled system are presented. Modules and subsystems that enable the realization of a hardware-in-the-loop simulation application and its interfacing with external controller hardware are explained. The thesis also presents three different simulation scenarios. Solutions suitable for these scenarios are provided along with their implementations. The details and specifications of the developed software packages and hardware platforms are given. The provided results illustrate the advantages and disadvantages of the approaches used in these solutions.

<p>Soft pneumatic actuators allow compliant force application and movement for a variety of tasks. While most soft actuators have compliance in directions perpendicular to their direction of force application, they are most often analyzed only in their direction of actuation. In this work, we show a characterization of a soft 3D printed bellows actuator that considers shear and axial deformations, modeling both active and passive degrees of freedom. We build a model based on actuator geometry and a parallel linear and torsional spring system which we fit to experimental data in order to obtain the model constants. We demonstrate this model on two complex parallel networks, a delta mechanism and a floating actuator mechanism, and show how this single actuator model can be used to better predict movements in parallel structures of actuators. These results verify that the presented model and modeling approach can be used to speed up the design and simulation of more complex soft robot models by characterizing both active and passive forces of their one degree-of-freedom soft actuators.<br> </p>