In this thesis, a set of sufficient conditions that guarantee consensus towards a pre-specified target state in double-integrator leader-follower networks are derived. Since only the leader agents are aware of the global objective and proximity based communication between all agents is considered, the follower agents must not lose contact to the leaders. In a first step, it is shown that such consensus seeking networks converge to the leader induced target state, as long as the interconnection graph is connected. A connectivity analysis framework is then established to make statements on the interconnection of any two initially connected agents during evolution of the system. This framework is subsequently used to state conditions which ensure preservation of all inter-agent links – and thus keeping the graph connected. These sufficient conditions put constraints on the magnitude of the goal attraction force experienced by the leaders as well as on the ratio of leader and follower agents in the network. Various different network topologies are examined, starting from an initially complete graph structure and extending to incomplete graphs. The theoretical results are illustrated by numerous computer simulations highlighting the relevance and effectiveness of the presented conditions.

Autonomous driving has been an important topic of research in recent years. In this thesis we study its application to Heavy Duty Vehicles, more specically, vehicles consisting of a truck and a trailer. An overview study is done on three fundamental steps of an autonomous driving system, planning, trajectory tracking and obstacle avoidance. In the planning part, we use RRT, and two other variants of the algorithm to nd trajectories in an unstructured environment, e.g., a mining site. A novel path optimization post-processing technique well suited for use with RRT solutions was also developed. For the trajectory tracking task several well-known controllers were tested, and their performance compared. An extension is proposed to one of the controllers in order to take into account the trailer. The performance evaluation was done on scaled truck systems in the Smart Mobility Lab at KTH. The obstacle avoidance is done with the aid of a simple, yet functional Model Predictive Controller. For this purpose, we developed dierent formulations of the optimization problem, corresponding to distinct optimization goals and vehicle models, in order to assess both the quality of the MPC, and of the assumed truck model. The outcome of this thesis is a fully autonomous system, able to plan and move in constrained environments, while avoiding unpredicted obstacles. It was implemented using a 1:32 scale remote controlled truck, commanded by a desktop computer.

This is a master thesis on the subject of navigation and control using reinforcementlearning, more specifically discrete Q-learning. The Q-learning algorithmis used to develop a steer policy from training inside of a simulation environment.The problem is to navigate a steel ball through a maze made from walls and holes. This thesis is the third thesis made revolving around this problem which allows for performance comparison with more classical control algorithms. The most successful of which is the gain scheduled LQR used to follow a splined path. The reinforcement learning derived steer policy managed at best 68 % success rate when navigating the ball from start to finish. Key features that had large impacton the policy performance when implemented in the simulation environment were response time of the physical servos and uncertainty added to the modelled forces. Compared to the performance of the LQR, which managed 46 % success rate, the reinforcement learning derived policy performs well. But with high fluctuation in performance policy to policy the control method is not a consistent solution to the problem. Future work is needed to perfect the algorithm and the resulting policy. A few interesting issues to investigate could be other formulations of disturbance implementation and training online on the physical system. Training online could allow for fine tuning of the simulation derived policy and learning how to compensate for disturbances that are difficult to model, such as bumps and warping in the labyrinth surface.

The purpose of the project is the development and study of guidance algorithms of missiles in the particular configuration of the simultaneous use of two pursuers to intercept one evader. The profits of this configuration are applied to allocation in a three missiles – two targets scenario. The implemented techniques deal with optimal control theory, more particularly with differential game theory, mainly the linear and linear quadratics, which are commonly used in guidance law. Differential game theory allows determining the optimal commands of the players of one pursuer - one evader game with the minimization of the miss distance for the pursuer and maximization of the same miss distance for the evader as criteria of this optimal problem. A new optimal command law for the evader is developed in the two pursuers against one evader game (called 2x1 games) with the same time-to-go as well as with different time-togo. These new optimal commands are implemented and validates in two 2D simulations: a linear one, developed in Matlab script, and a non linear one, based on a Simulink model. An extension of the capture zones of each missile is demonstrated and tested in simulations. The 2x1 game and the induced no-escape-zone extension are finally integrated and verified in realistic simulation with a 6 d.o.f missile Simulink model. The 2x1 configuration’s use is applied to allocation on 3 pursuers - 2 evaders scenarios based on the same 3D missile model and the benefits are analysed. / Le but de ce rapport et le développement et l'étude d'un algorithme de guidage missile dans le cas particulier de l'utilisation simultanée de deux missiles pour intercepter une cible. L'avantage de cette configuration est utilisé pour l'allocation des missiles dans un scenario de trois missiles contre deux cibles. Les techniques mises en oeuvre sont issues de la théorie du control optimal et plus particulièrement de la théorie des jeux différentiels linéaire et quadratique linéaire, qui sont couramment utilisés dans les lois de guidage. La théorie des jeux différentiels permet de déterminer les commandes optimales des joueurs d'un jeu un missile-une cible avec comme critère optimal la minimisation de la distance de passage finale pour le missile et la maximisation de cette même distance pour la cible. Une nouvelle loi de commande optimale pour la cible est établie pour le jeu de deux missiles – une cible (appelé jeu 2x1) avec aussi bien des time-to-go identiques que des time-to-go différents. Ces lois de commande optimales sont implémentées et validées dans deux simulations en 2D: une linéaire, développé en script Matlab, et une non-linéaire, développé sous Simulink. Une extension des zones de captures (no-escape-zone) de chacun des missiles est démontrée et testée avec les simulations. Le jeu 2x1 et l'extension des no-escape-zone qui en découle est finalement intégré et vérifié dans une simulation 3D sous Simulink plus réaliste, basé sur un modèle de missile à six degrés de libertés. L'utilisation d'une configuration 2x1 pour de l'allocation est appliqué à un scenario de trois missiles contre deux cibles basé sur les même modèle de missile à six degrés de libertés.

ZigBee is an emerging wireless technology for low-power, low data rate and short range communications between wireless nodes, which is showing a promising future. This research provides an overview of 802.15.4 and ZigBee standard. A test bench was created to evaluate the performance of ZigBee network for electricity meters applications. The results from the test show that ZigBee supports a large network size, a range of 75m within line of sight, a fairly large effective data rate that is enough for metering traffic and very low power consumption devices. These characteristics are very suitable for electricity meters applications where cost and power consumption is the major concern.

Traditionally direct integration of the measurements from an IMU (inertial measuring unit), measuring the acceleration and inertial angular velocity of the missile, is used to determine a missiles position and state. However, if some prior information about the missile dynamics is known, this method should be suboptimal. Combining the knowledge of the missile dynamics with the measurements should improve performance. Of course, the complete missile dynamics are not known. A few model uncertainties are therefore added and these uncertainties are estimated by the estimator. The measurements from the IMU are not perfect and these measurement errors are also estimated. This method is called model based parameter estimation. The problem is non linear and therefore estimators for non linear systems have been studied. The Extended Kalman filter and the Unscented Kalman filter were considered for this problem. It was shown that using this method the performance of the position estimate compared to the traditional method, was increased. The performance gain is mainly decided by the size of the model uncertainties compared to the size of the measurement errors. All states used in the model was not observable but only jointly observable meaning that all states did not converge to their true value. Instead the error was caught in other states and the position estimate was still quite good. Different trajectories for the missile excites different states. The trajectory both affects the impact of the IMU-errors and on the observability. The best performance was achieved for the sinus trajectory because of its excitation of the states. This knowledge might be used to improve the performance for all trajectories. An position sensor was also added and the affects were studied. It was shown that it is possible to increase the estimation performance even if the position is measured only for a short period of time in the beginning of the trajectory. The states converged much better using the position sensor than without and this method could be used in the evaluation of fired missiles in controlled circumstances. The Extended Kalman filter and the Unscented Kalman filter gave approximately the same estimation performance but the Extended Kalman filter was considerably faster and used in most of the analysis of the system. From this it was concluded that the performance of the position estimate is not estimator dependent but is more about the basic observability of the system.

Conventional (passive) headsets used in propeller aircrafts are reasonably good at attenuating mid to high frequency noise, but fail to achieve good attenuation in the low frequency region (below approximately 300 Hz). Active Noise Reduction (ANR) improves the low frequency attenuation by introducing an anti-noise signal creating destructive interference thus decreasing the residual noise level. The aim of this thesis is to develop and implement a digital narrowband active noise reduction headset that works properly in aircrafts and not only in a laboratory environment. The implementation is based on a narrowband ltered-X least mean squares (FXLMS) algorithm where the tonal components in the noise spectrum are synthesized for use as reference signals to the algorithm. The controller is implemented in a parallel fashion where each tonal component is handled separately. The system is built into a headset and laboratory tests show that the algorithm can handle ve simultaneous tonal components with an adaptation time of less than one second. Aircraft tests show peak attenuation of 17 dB in both singleand twin-engine aircrafts thus fullling the requirements. Simulations and true performance show some minor discrepancies which are explained and discussed.

This master’s thesis is part of a cooperation between BMW AG and Technische Universitat Munchen, in order to design a road simulator for Squeak and Rattle studies based on electromagnetic actuators. The study covers the field of decoupling control and adaptive inverse control, applied to a multi-post road simulator with electromagnetic actuators. The objective is to derive a controller which is robust and stabilizes the system without disturbances, thereto it is important to strive for a suitable bandwidth. At first the different control theory areas are covered and divided into the main problem groups, stabilization through state-feedback and bandwidth-adjustment measures through feedforward-filters. This is followed by the system modelling, where an actuator model is designed, with separate modelling steps for the electric, magnetic and mechanical parts. A rigid body vehicle model is derived and connected to four actuators. This leads to the complete system model, which is balanced and analyzed in terms of stability, controllabilityand observability. The model is a prerequisite for the design of the controller. Next the control theory presented is applied to the derived model in terms of a decoupling controller and a reduced observer to stabilize the system. The stabilized system is attenuated with adaptive multi input multi output invserse control concepts, as well as static feedforward-filters. The finished control structure is simulated for a two actuator and a four actuator rig. Furthermore, tests are made on an actual two-post road simulator with electromagnetic actuators, verifying the simulations. The objectives stated in the project are achieved on the actual test rig, and proved to be robust enough for the purposes of this and future experiments. The design goals for the rig in the scope of this study were achieved with a combination of state-space decoupling controller, reduced observer, tracking error estimator and time waveform replication.

The communication rate between the sensor and the supervisor in computer controlled systems is often limited. If multiple sensors are using the same communication link the limitation can compromise the control of the system, especially when wireless technology is used. To lower the communication rate new sampling methods have been evaluated. Event-triggered sampling has shown to give good results when it comes to sampling for control. This thesis presents a redundancy solution when a first order water tank plant is controlled by the use event-triggered sampling and the communication link between the sensor and the control algorithm is exposed to packet losses. The redundancy solution is constructed to give good performance in the tradeoff between low sampling rate and high quality of control. First, a deterministic sampled PID controller is developed and implemented on the plant. The PID controller is used as a reference solution in a comparison. Then, an event-triggered sampling and control solution is developed and implemented. The reference signal is distributed to the sensor and the event-triggered policy uses fresh level crossings in the control error to trigger samples. The event-triggered control algorithm uses proportional control to give fast responses to changes in the reference signal. Measurement losses are simulated to act as packet losses between the sensor and the supervisor. The redundancy solution is implemented and performances of the different cases are compared. The event-triggered solution shows good results compared to the PID solution, especially when the reference signal changes rarely. The results shows that the effects of measurement losses are an increased communication cost and a decreased tracking performance. More interesting, the effect of the redundancy solution is a restored tracking performance compared to when no losses occur. The negative effect is an increased communication cost compare to when no redundancy solution is used.

This thesis project is about the search and secure problem for mobile robots. The search and secure problem refers to the problem where possible moving intruders have to be detected in a given area with obstacles that are represented as polygons. The solution to this problem is given by deploying robots in a proper way so that no intruder can remain undetected or sneak back to a secured area. An intruder is considered detected when he/she is in the field of view of the robots’ on-board cameras. As a first step, in the algorithm that solves the search and secure problem, the area is divided into triangles. The resulting triangles are then merged in order to form convex polygons. The next step is to abstract the actual regions into a topological graph where each polygon is represented by its centroid and the neighboring polygons are connected by edges. At this point, blocking robots are used to break the loops in the graph and prevent the intruders from escaping from the searchers. Then the number of the searchers is determined and their paths are created. Two solutions are proposed, one that requires more searchers but less time and one that requires the minimum number of searchers but more time. The last step is to create the trajectories that the robots have to follow. The functionality and the efficiency of the algorithm is verified through simulations and the results are visualized using Matlab and the AURES simulator and controller. The demonstration that was held at SAAB facilities in Linköping is also described.