Táto práca sa zaoberá vývojom, testovaním a implementáciou adaptívneho riadiaceho systému pre dvojkolesové samobalancujúce vozidlo. Adaptácia parametrov vozidla sa uskutoční na základe parametrov vodiča. Parametre sústavy sa nemerajú priamo, ale sú odhadované na základe priebehu stavových premenných a odozvy sústavy. Medzi odhadované parametre patrí hmotnosť a poloha ťažiska vodiča. Cieľom práce je zabezpečiť adaptáciu jazdných vlastností vozidla k rôznym vodičom s rôznou hmotnosťou, kvôli zlepšeniu stability vozidla. Táto práca je pokračovaním predchádzajúcich projektov z roku 2011 a 2015.

Master thesis is focused on the philosophy of design adaptive controller. In the theoretic part are described parts of the adaptive controller, which belongs parts as online identification by recursive least-squares method and PSD controller, which can set its parameters according to identified system (use Z-N method). The part of control system with transport delay is situated at the conclusion of the theoretic part, there are focused on Smith predictor. Practical part is focused on verification of all algorithms, which was performed on models and real systems.

Master thesis is focused on the philosophy of design adaptive controller. In the theoretic part are described parts of the adaptive controller, which belongs parts as online identification by recursive least-squares method and PSD controller, which can set its parameters according to identified system (use Z-N method). The part of control system with transport delay is situated at the conclusion of the theoretic part, there are focused on Smith predictor. Practical part is focused on verification of all algorithms, which was performed on models and real systems.

Ce travail s’inscrit dans le cadre de la commande d’un système multi agents/ multi véhicules. Cette thèse traite en particulier le cas de la commande d’un système multi-robots mobiles non-holonomes. L'objectif est de concevoir des lois de commandes appropriées pour chaque robot de sorte que l’ensemble des robots puisse exécuter des tâches spécifiques, de suivre des trajectoires désirées tout en maintenant des configurations géométriques souhaitées. L’approche leadeur-suiveur pour la commande d’un groupe de robots mobiles non-holonomes est étudiée en intégrant la technologie backstepping, avec une approche basée sur les neurodynamiques bioinspirées. Le problème de commande distribuée d’un système multi robots sur le consensus est également étudié. Des lois de commandes cinématiques distribuées sont développés afin de garantir au système multi-robots la convergence exponentielle vers une configuration géométrique souhaitée. Afin de tenir compte de la dynamique des paramètres inconnus, des commandes adaptatives de couple sont développés pour que le système multi-robots puisse converger asymptotiquement vers le modèle géométrique souhaité. Lorsque la dynamique est inconnue, des commandes à base de réseaux de neurones sont proposées / This work is based on the multi-agent system / multi-vehicles. This thesis especially focuses on formation control of multiple nonholonomic mobile robots. The objective is to design suitable controllers for each robot according to different control tasks and different constraint conditions, such that a group of mobile robots can form and maintain a desired geomantic pattern and follow a desired trajectory. The leader-follower formation control for multiple nonholonomic mobile robots is investigated under the backstepping technology, and we incorporate a bioinspired neurodynamics scheme in the robot controllers, which can solve the impractical velocity jumps problem. The distributed formation control problem using consensus-based approach is also investigated. Distributed kinematic controllers are developed, which guarantee that the multi-robots can at least exponentially converge to the desired geometric pattern under the assumption of "perfect velocity tracking". However, in practice, "perfect velocity tracking" doesn’t hold and the dynamics of robots should not be ignored. Next, in consideration of the dynamics of robot with unknown parameters, adaptive torque controllers are developed such that the multi-robots can asymptotically converge to the desired geometric pattern under the proposed distributed kinematic controllers. Furthermore, When the partial knowledge of dynamics is available, an asymptotically stable torque controller has been proposed by using robust adaptive control techniques. When the dynamics of robot is unknown, the neural network controllers with the robust adaptive term are proposed to guarantee robust velocity tracking

The master’s thesis deals with method of adaptive control of electrical drives. It aims at control of DC motor with using self tunning controller (STC) and gain-schedulink in simulative enviroment of MATLAB. The first part of the thesis deals with of basic methods adaptive control of electrical drives and with of basic identification methods, computation of controller parameters and control laws of controllers. The second part of the thesis is aimed at applying adaptive controllers to mathematical model of controlled system. Include monitoring parameters of identification The thesis contains originate programs include source files.

This master's thesis considers adaptive optimal controllers. It shows principles of optimal controllers, recursive identification using least-mean squares method and identification based on neural network.

This thesis deals with implementation of industrial used controlling block into Power Panel equipment of B&R in integrated development environment Automation Studio 3.0.71. It is PID controller with autotuner and visualization, which allowed bumpless transfer among controlling algorithms and manual control. PID and I-PD controllers with filtering of derivative action and dynamic antiwindup were implemented. Parameters of PID controller is possible to tune with the aid of ultimate gain and ultimate period according rules of Ziegler-Nichols. Ultimate parameters of controlled plant is possible to acquire with the aid of two identification methods, recursive least squares method and relay feedback. Recursive least squares method was implemented with directional forgetting. For relay feedback were used two types of relays: ideal and saturation relay for improving accuracy of searched ultimate values. The whole solution is programmed in ANSI C which Automation Studio supports. Created controller is control with the aid of touchscreen which is integrated in Power Panel. Trends of process values are viewed on the screen too. For comparison adaptive controller by B&R was implemented. This contoller is standardly supplied with Automation Studio in LoopConR library. All created algorithms were first validated on mathematical model of plant and then on real model in laboratory. The first part of thesis deals with theoretic analysis of used methods. The practical realization is described in the second part of this diploma thesis.