In this thesis the problem of trajectory planning for automatic machines is addressed, considering in particular the problem of vibration suppression and perfect tracking. Two different trajectory generators based on dynamic filters are developed and implemented. These novel trajectory planners are designed respectively for residual vibrations suppression and perfect tracking of periodic trajectories. Both solutions are very effective and easy to implement, exploiting the realization of dynamic filters by means of FIR filters. In the first part of the thesis the problem of residual vibrations in motion control of robots is addressed. In a review fashion the most widespread feed-forward techniques for residual vibration suppression are analyzed in detail and implemented in simulation. Moreover all the analysis are performed with a control system perspective in order to give a unified point of view allowing to compare all the solutions despite their differences. In Chapter 5 a novel trajectory generator based on Exponential Filters is presented, analyzed and compared with the most commonly used feed-forward techniques for vibration suppression, proving comparable performances with the state of the art. The analysis and comparison procedure is performed both in simulation and in experimental activities. This new method is developed first for simple SISO LTI systems and then extended to MIMO systems. In Chapter 6 a new repetitive control scheme based on B-Spline Trajectory Generator that exploits dynamic filters is presented. The novel scheme integrates the trajectory generator and the repetitive controller in a single discrete time feedback loop achieving perfect tracking for periodic motions. In appendix, the development of a 6-axis Force/Torque sensor for underwater activities based on optoelectronic components is reported. The description covers the entire process from the concept to the development of a simulation model and finally to the prototype realization, along with an extensive experimental activity.

This work presents developments of Guidance, Navigation and Control (GNC) systems with application to autonomous Unmanned Aerial Vehicle (UAV). Precisely, this work shows the development of navigation system based on nonlinear complementary filters for position, velocity and attitude estimation using low-cost sensors. The proposed filtering method provides attitude estimates in quaternion representations and position and velocity estimates by fusing measurements from Inertial Measurement Unit (IMU), GPS, and a barometer. Least Square Method (LSM) was used in gains tuning to find the best-fitting of the estimated states with precise measurements obtained by a vision based motion capture system. A complete navigation system was produced by integrating both the attitude and the position filters. The integration of the filtering approach based primarily on the ease of design and computational load. Furthermore, the structure of the filtering design allow for straightforward implementation without a need of high performance signal processing. Moreover, the filters can be tuned totally independent of each other. This work also introduces a nonlinear flight controller for stability and trajectory tracking that is practical for real-time implementation. This controller is also demonstrated the ability of a supervisory controller to provide effective waypoint navigation capabilities in autonomous UAV. The implementation of the guidance, navigation, and control algorithms were adopted in the design of a novel smartphone based autopilot for particular quadrotor aerial platforms. The performances of the proposed work are then evaluated by means of several flight tests. The work also includes a design of advanced navigation and guidance systems based on Robot Operating System (ROS) for Search And Rescue (SAR) missions. Primarily, the performance of the navigation and guidance systems were tested in laboratory by simulating GPS measurements in Linux computer mounted on the top of a quadrotor. This activity facilitates moving by the experiments from indoor to outdoor.

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

Mobile robots gained lots of attention in the last decades. Because of its flexibility and increased capabilities of automation, mobile robots are used in many applications: from domotic, to search and rescue missions, to agriculture, environment protection and many more. The main capability of mobile robots to accomplish a mission is the mobility in the work environment. To move in a certain environment the robots should achieve: guidance, navigation and control. This thesis focuses on guidance and control of mobile robots, with application to certain classes of robots: Vertical Take Off and Landing Unmanned Aerial Vehicles (VTOL UAV) and Differential Wheel robots (DWR). The contribution of this thesis is on modeling and control of the two classes of robots, and on novel strategies of combined control and motion planning for kinodynamic systems. A new approach to model a class of multi-propeller VTOL is proposed, with the aim of generating a general model for a system as a composition of elementary modules such as actuators and payloads. Two control law for VTOL vehicles and DWR are proposed. The goal of the first is to generate a simple yet powerful control to globally asymptotically stabilize a VTOL for acrobatic maneuvers. The second is a simple saturated input control law for trajectory tracking of a DWR model in 2D. About planning, a novel approach to generate non-feasible trajectories for robots that still guarantees a correct path for kinodynamic planning is proposed. The goal is to reduce the runtime of planners to be used in real-time and realistic scenario. Moreover an innovative framework for mobile robots motion planning with the use of Discrete Event Systems theory is introduced. The two proposed approaches allow to build a global, robust, real-time, quasi-optimal, kinodynamic planner suitable for replanning.

Over the last years, consensus and synchronization problems have been a popular topic in the systems and control community. This interest is motivated by the fact that, in several fields of application, a certain number of agents is interacting or has to cooperate to achieve a certain task. Robotic swarms, sensor networks, power networks, biological networks are only few outstanding examples where networks of agents displays behaviors which can be modeled and studied by means of consensus and synchronisation techniques. In this thesis we consider a general class of networked nonlinear systems in different operating frameworks and design control architecture to force the systems to reach synchronization and consensus on a target behavior. In particular, we consider the case of homogeneous and heterogeneous nonlinear agents with a static communication topology and design a static high-gain-based diffusive coupling and an internal model-based regulator respectively, to solve the problem of consensus. Then, we analyze the case of dynamical links and show under which conditions, synchronization for homogeneous nonlinear systems can be achieved. Depending on the structure of the dynamic links at hand, static and dynamic regulators (based on the concept extended state observers) are proposed. Furthermore, we address the problem of disconnected topology and switching topology and derive under which conditions agents reach cluster synchronization and synchronization respectively. Last, we consider the problem of a sampled exchange of information between the agents and design a triggering rule locally at each agent such that the overall network reaches synchronization.

The objective of this thesis is twofold: on one hand, the design of nonliner observers, on the other, the design of internal-model regulators to solve the robust output regulation problem. In the observer theory a key role is played by the so called high-gain observers. The purpose of the first part of the thesis is to propose novel techniques which allow to overcome or at least to mitigate some of the main drawbacks characterizing this class of observers. Firstly, we study the possibility of writing an observer for multi-input multi-output observable systems in the original coordinates. Then, we propose a novel class of high-gain observers, denoted as ``low-power'', which allows to overcome numerical problems, to avoid the peaking phenomenon and to improve the sensitivity properties to high-frequency measurement noise. The second part of the thesis addresses the output regulation problem, solved for linear systems during the 70's by Francis and Wonham who coined the celebrated ``internal model principle''. Constructive solutions have also been proposed in the nonlinear framework but under restrictive assumptions that reduce the class of systems to which this methodology can be applied. In this thesis we focus on the output regulation problem in presence of periodic disturbances and we propose a novel approach which allows to consider a broader class of nonlinear systems. With the proposed design the stabilization problem and the regulation problem are substantially decoupled and output regulation is achieved in presence of uncertainties or disturbances, as long as the trajectories of the resulting closed-loop system are bounded.

No description available.

The use of tendons for the transmission of the forces and the movements in robotic devices has been investigated from several researchers all over the world. The interest in this kind of actuation modality is based on the possibility of optimizing the position of the actuators with respect to the moving part of the robot, in the reduced weight, high reliability, simplicity in the mechanic design and, finally, in the reduced cost of the resulting kinematic chain. After a brief discussion about the benefits that the use of tendons can introduce in the motion control of a robotic device, the design and control aspects of the UB Hand 3 anthropomorphic robotic hand are presented. In particular, the tendon-sheaths transmission system adopted in the UB Hand 3 is analyzed and the problem of force control and friction compensation is taken into account. The implementation of a tendon based antagonistic actuated robotic arm is then investigated. With this kind of actuation modality, and by using transmission elements with nonlinear force/compression characteristic, it is possible to achieve simultaneous stiffness and position control, improving in this way the safety of the device during the operation in unknown environments and in the case of interaction with other robots or with humans. The problem of modeling and control of this type of robotic devices is then considered and the stability analysis of proposed controller is reported. At the end, some tools for the realtime simulation of dynamic systems are presented. This realtime simulation environment has been developed with the aim of improving the reliability of the realtime control applications both for rapid prototyping of controllers and as teaching tools for the automatic control courses.

No description available.

No description available.