Récemment, le robot dirigeable a attiré l'attention de plus en plus des chercheurs grâce à ses avantages par rapport à d'autres aéronefs, tels que la capacité de VTOL, le vol stationnaire et à basse vitesse, une grande autonomie, et une interaction Homme-Robot sûre, etc. Ainsi c'est une plate-forme idéale pour diverses applications d'intérieur. Dans cette thèse, nous étudions la modélisation et le contrôle du mouvement d'un robot dirigeable d'intérieur et développons un prototype pour les opérations intérieures comme la surveillance. Le travail est composé de parties théoriques et pratiques. Concernant la partie théorique, d’abord, sous des hypothèses raisonnables, le modèle dynamique à 6-DOF est simplifié et divisé en deux parties indépendantes: le mouvement de l’altitude et le mouvement dans le plan horizontal. Ensuite, à fin d'assurer la précision de la modélisation et du contrôle, le modèle nominal est complété par des termes de perturbation qui sont estimés en temps réel et compensés dans les contrôleurs conçus. Des simulations sont effectuées pour vérifier les performances et la robustesse des contrôleurs. Pour la partie pratique du travail, basée sur l'analyse des fonctionnalités du robot afin de réaliser les applications intérieures souhaitées, le matériel du robot dirigeable est conçu et créé. Enfin, de vrais tests sont effectués sur la plate-forme de robot dirigeable pour la validation des lois de contrôle de mouvement conçues, et des résultats satisfaisants sont obtenus. / Recently, the blimp robot has attracted more and more attentions of the researchers for its advantages compared to other aircrafts, such as ability for VTOL, stationary and low speed flight, long endurance in air and safe Human-Robot interaction, etc. Therefore it is an ideal platform for various indoor applications. In this thesis, we study the modeling and motion control of an indoor blimp robot, and develop a real robot for indoor operations such as the long-term surveillance. The work is composed of both theoretical and practical parts. For the theoretical part, first, under reasonable assumptions, the 6-DOF dynamic model is simplified and divided into two independent parts: the altitude motion and the horizontal plane movement. Then, to ensure the accuracy of modeling and control, the nominal model is complemented with disturbance terms which are estimated in real-time and compensated in the designed controllers. Simulations are carried out to verify the performance and robustness of the controllers. For the practical part of the work, based on the functionality analysis of the robot to achieve desired indoor applications, the hardware of the blimp robot is conceived and created. Finally, real tests are made on the blimp robot platform for the validation of the designed motion control laws, and satisfying results are obtained.

The work in this dissertation concerns the construction of a robust iterative learning control (ILC) algorithm for a class of systems characterized by measurement delays, parametric uncertainty, and linear parameter varying (LPV) dynamics. One example of such a system is the twin roll strip casting process, which provides a practical motivation for this research. I propose three ILC algorithms in this dissertation that advance the state of the art. The first algorithm compensates for measurement delays that are longer than a single iteration of a periodic process. I divide the delay into an iterative and residual component and show how each component effects the asymptotic stability properties of the ILC algorithm. The second algorithm is a coupled delay estimation and ILC algorithm that compensates for time-varying measurement delays. I use an adaptive delay estimation algorithm to force the delay estimate to converge to the true delay and provide stability conditions for the coupled delay estimation and ILC algorithm. The final algorithm is a norm optimal ILC algorithm that compensates for LPV dynamics as well as parametric uncertainty and time delay estimation error. I provide a tuning method for the cost function weight matrices based on a sufficient condition for robust convergence and an upper bound on the norm of the error signal. The functionality of all three algorithms is demonstrated through simulated case studies based on an identified system model of the the twin roll strip casting process. The simulation testing is also augmented with experimental testing of select algorithms through collaboration with an industrial sponsor.

In this dissertation the problem of recognising vehicle licence plates of which the sym¬bols can not be segmented by standard image processing techniques is addressed. Most licence plate recognition systems proposed in the literature do not compensate for dis¬torted, obscured and damaged licence plates. We implemented a novel system which uses a neural network/ hidden Markov model hybrid for licence plate recognition. We implemented a region growing algorithm, which was shown to work well when used to extract the licence plate from a vehicle image. Our vertical edges algorithm was not as successful. We also used the region growing algorithm to separate the symbols in the licence plate. Where the region growing algorithm failed, possible symbol borders were identified by calculating local minima of a vertical projection of the region. A multilayer perceptron neural network was used to estimate symbol probabilities of all the possible symbols in the region. The licence plate symbols were the inputs of the neural network, and were scaled to a constant size. We found that 7 x 12 gave the best character recognition rate. Out of 2117 licence plate symbols we achieved a symbol recognition rate of 99.53%. By using the vertical projection of a licence plate image, we were able to separate the licence plate symbols out of images for which the region growing algorithm failed. Legal licence plate sequences were used to construct a hidden Markov model contain¬ing all allowed symbol orderings. By adapting the Viterbi algorithm with sequencing constraints, the most likely licence plate symbol sequences were calculated, along with a confidence measure. The confidence measure enabled us to use more than one licence plate and symbol segmentation technique. Our recognition rate increased dramatically when we com¬bined the different techniques. The results obtained showed that the system developed worked well, and achieved a licence plate recognition rate of 93.7%. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002. / Electrical, Electronic and Computer Engineering / unrestricted

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In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine.

<p dir="ltr">Engine downsizing with the assistance of turbomachinery and/or energy storage system has been realized to be one of the most promising and cost-effective solutions in pursuit of cleaner and more efficient engine products. Fundamental challenges however, exist in terms of control and energy management of advanced powertrain featuring turbocharged engines due to their complex dynamics, inherent coupling nature, and strict emission regulations concerning environmental preservation. For the purpose of addressing those challenges, this dissertation develops an integrated framework for modeling, robust coordinated control, and power management of advanced powertrains featuring turbocharged engines.</p><p dir="ltr">This dissertation first studies an advanced turbocharged lean-burn SI natural gas engine manufactured by Caterpillar, and develops an intuitive physics-based, control-oriented model. The obtained control-oriented model is validated against a high-fidelity truth-reference model and serves as the basis on which a robust coordinated control system is developed. The dissertation then proposes a comprehensive procedure for synthesizing a robust coordinated control system applying optimization-based H_infinity control theory. Specifically, this framework outlines a methodology of modeling uncertainties to account for system robustness, and providing valuable insights into the tuning of general coordinated control system design. For performance testing, the synthesized robust coordinated control system is implemented on the high-fidelity truth-reference model. A parallel closed-loop simulation strategy is adopted so that direct comparison between the robust coordinated control system and benchmark production control system (composed of multiple fine-tuned PID controllers) developed by Caterpillar can be carried out. Simulation results manage to demonstrate the merit of utilizing the robust coordinated control system, with better performances observed in terms of steady-state tracking, transient response, and disturbance attenuation.</p><p dir="ltr">The second part of this dissertation focuses on the development of a proposed novel hybrid electric wheel loader which features a downsized engine assisted by turbocharger and an energy storage system. Research efforts documented in this dissertation involve system configuration, controller design (both component-level and supervisory-level), simulation development (both software-in-the-loop and hardware-in-the-loop) and simulated validation for the proposed novel wheel loader. Inspired by the successful simulation results, John Deere assembled a real demo vehicle with the proposed powertrain and conducted some in-field testing, from which encouraging experimental results are observed.</p>

The overall objective of the Wallenberg Laboratory for Information Technology and Autonomous Systems (WITAS) at Linköping University is the development of an intelligent command and control system, containing vision sensors, which supports the operation of a unmanned air vehicle (UAV) in both semi- and full-autonomy modes. One of the UAV platforms of choice is the APID-MK3 unmanned helicopter, by Scandicraft Systems AB. The intended operational environment is over widely varying geographical terrain with traffic networks and vehicle interaction of variable complexity, speed, and density. The present version of APID-MK3 is capable of autonomous take-off, landing, and hovering as well as of autonomously executing pre-defined, point-to-point flight where the latter is executed at low-speed. This is enough for performing missions like site mapping and surveillance, and communications, but for the above mentioned operational environment higher speeds are desired. In this context, the goal of this thesis is to explore the possibilities for achieving stable ‘‘aggressive’’ manoeuvrability at high-speeds, and test a variety of control solutions in the APID-MK3 simulation environment. The objective of achieving ‘‘aggressive’’ manoeuvrability concerns the design of attitude/velocity/position controllers which act on much larger ranges of the body attitude angles, by utilizing the full range of the rotor attitude angles. In this context, a flight controller should achieve tracking of curvilinear trajectories at relatively high speeds in a robust, w.r.t. external disturbances, manner. Take-off and landing are not considered here since APIDMK3 has already have dedicated control modules that realize these flight modes. With this goal in mind, we present the design of two different types of flight controllers: a fuzzy controller and a gradient descent method based controller. Common to both are model based design, the use of nonlinear control approaches, and an inner- and outer-loop control scheme. The performance of these controllers is tested in simulation using the nonlinear model of APID-MK3. / <p>Report code: LiU-Tek-Lic-2002:11. The format of the electronic version of this thesis differs slightly from the printed one: this is due mainly to font compatibility. The figures and body of the thesis are remaining unchanged.</p>

Ensuring constraint satisfaction in large-scale systems with hard constraints is vital in many safety critical systems. The challenge is to design controllers that are efficiently synthesized offline, easily implementable online, and provide formal correctness guarantees. We take a divide and conquer approach to design controllers for reachability and infinite-time/finite-time constraint satisfaction control problems given large-scale interconnected linear systems with polyhedral constraints on states, controls, and disturbances. Such systems are made of small subsystems with coupled dynamics. Our goals are to design controllers that are i) fully compositional and ii) decentralized, such that online implementation requires only local state information. We treat the couplings among the subsystems as additional disturbances and use assume-guarantee (AG) contracts to characterize these disturbance sets. For each subsystem, we design and implement a robust controller locally, subject to its own constraints and contracts. Our main contribution is a method to derive the contracts via a novel parameterization, and a corresponding potential function that characterizes the distance to the correct composition of controllers and contracts, where all contracts are held. We show that the potential function is convex in the contract parameters. This enables the subsystems to negotiate the contracts with the gradient information from the dual of their local synthesis optimization problems in a distributed way, facilitating compositional control synthesis that scales to large systems. We then incorporate Signal Temporal Logic (STL) specifications into our formulation. We develop a decentralized control method for a network of perturbed linear systems with dynamical couplings subject to STL specifications. We first transform the STL requirements into set containment problems, then we develop controllers to solve these problems. The set containment requirements and parameterized contracts are added to the subsystems’ constraints. We introduce a centralized optimization problem to derive the contracts, reachability tubes, and decentralized closed-loop control laws. We show that, when the STL formula is separable with respect to the subsystems, the centralized optimization problem can be solved in a distributed way, which scales to large systems. We present formal theoretical guarantees on robustness of STL satisfaction. We present numerical examples, including scalability studies on systems with tens of thousands of dimensions, and case studies on applying our method to a distributed Model Predictive Control (MPC) problem in a power system. / 2024-01-16T00:00:00Z

Soft robots have been used in a wide range of applications from robotic and mechanical engineering to medicine and biomededical field. The growing interest in soft robots comes from their good performance in environments which is not best suited for conventional rigid bodies. Soft robots utilize the compliance, adaptability and flexibility of soft materials and actuation methods to develop highly adaptive structures. Among the soft materials, elastomers are specially popular due to their wide range of elasticity and viscoelasticity. Along with elastomers, textile fabrics are also of high interest for soft robotic applications due to their bendable, flexible, and often stretchable nature. The reinforcement of elastomers with textile fibers results in so-called integrated fiber-elastomer composites (IFEC) which offer a wide variety of properties such as flexibility, strength, fracture toughness and damage resistance. The elastic properties of textile reinforced composites require smart actuators which possess adaptability and deformability. Among existing smart actuators, shape memory alloys (SMA) have been frequently adopted in flexible structures including soft robots. SMAs have sensing and actuation capabilities and are characterized by flexibility and lightness which facilitates their integration into these structures. In this dissertation, the modeling and control of soft prototypes made of IFEC are presented. Shape memory alloys are embedded in the composites for the system actuation. First, the mechanical design and production of three IFEC prototypes are described. For each prototype, a test bench including power and control electronics set-up is designed. Next, mathematical models are developed to analyze the dynamic behavior of the prototypes. The IFEC systems exhibit highly nonlinear behaviour due to SMA hysteresis. For modeling, two different approaches, namely physical modelling and system identification are adopted. In physical modeling, the SMA constitutive and heat transfer equations are incorporated with the composite deflection model. To fully develop the equations, thermal and mechanical parameters of SMA wires are identified experimentally. In the second approach, the mathematical model of the systems is derived from experimental identification and unstructured uncertainty models. Two different control techniques are proposed to compensate the nonlinear behavior of the systems and ensure a robust, fast and precise position tracking. In the first control technique, a proportional integral (PI) controller is designed through robust stability analysis. The second controller is a multivariable PI control which is designed for the prototypes that can move in more than one direction. The performance of the controllers are examined experimentally.

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