This thesis presents an approach towards experimental realization of underactuated bipedal robotic walking using human data. Human-inspired control theory serves as the foundation for this work. As the name, "human-inspired control," suggests, by using human walking data, certain outputs (termed human outputs) are found which can be represented by simple functions of time (termed canonical walking functions). Then, an optimization problem is used to determine the best fit of the canonical walking function to the human data, which guarantees a physically realizable walking for a specific bipedal robot. The main focus of this work is to construct a control scheme which takes the optimization results as input and delivers human-like walking on the real-world robotic platform - AMBER. To implement the human-inspired control techniques experimentally on a physical bipedal robot AMBER, a simple voltage based control law is presented which utilizes only the human outputs and canonical walking function with parameters obtained from the optimization. Since this controller does not require model inversion, it can be implemented efficiently in software. Moreover, applying this methodology to AMBER, experimentally results in robust and efficient "human-like" robotic walking.

Abstract Drying, especially rotary drying, is without doubt one of the oldest and most common unit operations in the process industries. Rotary dryers are workhorses which are easy and reliable to operate, but neither energy-efficient nor environmentally friendly. In order to conform better to the requirements of modern society concerning working conditions, safety practices and environmental aspects, the development of control systems can provide opportunities for improving dryer operation and efficiency. Our in depth understanding of rotary drying is poor, because it is a very complex process that includes the movement of solids in addition to thermal drying. Thus even today rotary dryers are controlled partly manually, based on the operator's "eye" and experience, and partly relying on conventional control methods. The control of a rotary dryer is difficult due to the long time delay, which means that accidental variations in the input variables can disturb the process for long periods of time before they are reflected in the output variables. To eliminate such disturbances at an early stage, increasing interest has been shown in more sophisticated control systems such as model-based constructs, fuzzy logic and neural nets in recent years. Although it has proved difficult and time-consuming to develop model-based control systems, due to the complexity of the process, intelligent control methods based on fuzzy logic and neural nets offer attractive solutions for improving dryer control. These methods make it possible to utilize experience, knowledge and historical data, large amounts of which are readily available. The aim of this research was to improve dryer control by developing new hybrid control systems, one consisting of a fuzzy logic controller (FLC) and PI controller and the other of a three-layer neural network (NN) and PI controller. The FLC and NN act as supervisory controllers giving set points for the PI controllers. The performance of each was examined both with simulations and in pilot plant experiments. The pilot plant dryer at the University of Oulu closely resembles a real industrial situation, so that the results are relevant. Evaluation of these results showed that the intelligent hybrid controllers are well suited for the control of a rotary dryer, giving a performance in which disturbances can be eliminated rapidly and operation of the dryer can thereby be improved, with the aim of enhancing its efficiency and environmental friendliness.

Telerobotics are becoming increasingly more prevalent in the medical field due to the many advantages they have over standard methods. In particular, their use in surgical procedures provides benefits such as safer operations and greater health care access, among others. However, there are drawbacks that dissuade telerobotic usage and aspects that can still be improved upon. Examples of these include the inevitable impact of time delay and the existence of disturbances, such as patient-manipulator contact. These factors can result in system destabilization and ultimately task failure, discouraging the usage of telerobotics in these settings. This thesis investigates the effects of time delay and contact disturbances on telerobotic performance in a surgical setting. In this work, different methods of improving telerobotic performance such as using hybrid controllers and predictive technology are explored. The goal is to investigate options for mitigating the negative effects of these elements while improving overall telerobotic performance.

Rotary Cranes (Tower Cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became dicult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under dierent operating conditions, which makes closed-loop control preferable. In this work, two types of controllers are studied: fuzzy logic and time-delayed position feedback controllers. The fuzzy logic controller is introduced first with the idea of split-horizon; that is, to use some fuzzy engines for tracking position and others for damping load oscillations. Then the time-delayed position feedback method is applied. Finally, an attempt to combine these two controllers into a hybrid controller is introduced. Computer simulations are used to verify the performance of these controllers. An experimental setup was built on which the time-delayed position feedback controller was tested. The results showed good performance. / Master of Science

We extend the application of the substructure synthesis method to more complex structures, and establish a design methodology for base isolation and active control in a distributed model of a building under seismic excitation. Our objective is to show that passive and active control complement each other in such an advantageous manner for the case at hand, that simple devices for both types of control are sufficient to achieve excellent response characteristics with very low control forces. The Rayleigh-Ritz based substructure synthesis method proved to be highly successful in analyzing a structure more complex than the ones previously analyzed with it. Comparing the responses of the hybridly controlled building and the conventional fixed building under El Centro excitation, we conclude that the stresses are reduced by 99.6 %, the base displacement is reduced by 91.7 % and the required control force to achieve this is 1.1 % of the building weight. / Ph. D.

Esta dissertação estuda a otimização da capacidade de interação de manipuladores robôs com o meio externo através do controle das forças e torques envolvidas no contato. Os modelos adotados para as análises levam em consideração a interação entre a extremidade do manipulador e uma superfície. Neste trabalho, são investigadas diferentes metodologias para controle de forças, assim como as vantagens e desvantagens de cada método estudado para comparar e desenvolver um controle adequado das forças de contato. Devido às divergências encontradas na literatura, foram implementadas experimentalmente duas abordagens distintas conhecidas por controle cinestático e controle híbrido. Também, como parte do ambiente experimental, foi desenvolvido um protótipo de um micro manipulador com um grau de liberdade instalado na extremidade do robô. O micro manipulador simplifica a implementação de controle de força ativo, pois trabalha de forma independente do acionamento \"fechado\" dos robôs industriais abordados no trabalho. Assim é possível manter uma força arbitraria desejada no contato com a superfície. O controlador de força se sobrepõe ao controlador de posições convencional do manipulador para produzir o comportamento desejado na interação com o meio externo. / The optimization of a conventional industrial robot manipulator capacity to interact with the surrounding environment is analyzed in this work. The models adopted for the analysis take into account the contact between the robot and an external surface. Different force control approaches are analyzed regarding their implementation advantages and disadvantages. Due to the well known contradictions in the literature experiments were carried out using the kinestatic control and the hybrid control. A micro manipulator with one degree of freedom was developed and installed at the end effector in association with the tool tester. With this system it is possible change the contact force on the surface. The simultaneous coordinate work of the robot position control and the micro manipulator system force control are use to produce a desired behavior in the interaction with the external surface.

Esta dissertação estuda a otimização da capacidade de interação de manipuladores robôs com o meio externo através do controle das forças e torques envolvidas no contato. Os modelos adotados para as análises levam em consideração a interação entre a extremidade do manipulador e uma superfície. Neste trabalho, são investigadas diferentes metodologias para controle de forças, assim como as vantagens e desvantagens de cada método estudado para comparar e desenvolver um controle adequado das forças de contato. Devido às divergências encontradas na literatura, foram implementadas experimentalmente duas abordagens distintas conhecidas por controle cinestático e controle híbrido. Também, como parte do ambiente experimental, foi desenvolvido um protótipo de um micro manipulador com um grau de liberdade instalado na extremidade do robô. O micro manipulador simplifica a implementação de controle de força ativo, pois trabalha de forma independente do acionamento \"fechado\" dos robôs industriais abordados no trabalho. Assim é possível manter uma força arbitraria desejada no contato com a superfície. O controlador de força se sobrepõe ao controlador de posições convencional do manipulador para produzir o comportamento desejado na interação com o meio externo. / The optimization of a conventional industrial robot manipulator capacity to interact with the surrounding environment is analyzed in this work. The models adopted for the analysis take into account the contact between the robot and an external surface. Different force control approaches are analyzed regarding their implementation advantages and disadvantages. Due to the well known contradictions in the literature experiments were carried out using the kinestatic control and the hybrid control. A micro manipulator with one degree of freedom was developed and installed at the end effector in association with the tool tester. With this system it is possible change the contact force on the surface. The simultaneous coordinate work of the robot position control and the micro manipulator system force control are use to produce a desired behavior in the interaction with the external surface.

The use of teams of coordinated mobile robots in industrial settings such as underground mining, toxic waste cleanup and material storage and handling, is a viable and reliable approach to solving such problems that require or involve automation. In this thesis, abilities a team of mobile robots should demonstrate in order to successfully perform a mission in industrial settings are identified as a set of functional components. These components are related to navigation and obstacle avoidance, localization, task achieving behaviors and mission planning. The thesis focuses on designing and developing functional components applicable to diverse missions involving teams of mobile robots; in detail, the following are presented: 1. A navigation and obstacle avoidance technique to safely navigate the robot in an unknown environment. The technique relies on information retrieved by the robot's vision system and sonar sensors to identify and avoid surrounding obstacles. 2. A localization method based on Kalman filtering and Fuzzy logic to estimate the robot's position. The method uses information derived by multiple robot sensors such as vision system, odometer, laser range finder, GPS and IMU. 3. A target tracking and collision avoidance technique based on information derived by a vision system and a laser range finder. The technique is applicable in scenarios where an intruder is identified in the patrolling area. 4. A limited lookahead control methodology responsible for mission planning. The methodology is based on supervisory control theory and it is responsible for task allocation between the robots of the team. The control methodology considers situations where a robot may fail during operation. The performance of each functional component has been verified through extensive experimentation in indoor and outdoor environments. As a case study, a warehouse patrolling application is considered to demonstrate the effectiveness of the mission planning component.

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Cyber-Physical Systems (CPS) are systems of collaborating computational elements controlling physical entities via communication. Such systems involve control processes of physical entities and computational processes. The control complexities originated from the physical dynamics and systematic constraints are difficult for traditional control approaches (e.g., PID control) to handle without an exponential increase in design/test etc. costs. Model predictive control (MPC) predicts and produces optimized control inputs based on its predictive model according to a cost function under given constraints. This control scheme has some attractive features for CPSs: it handles constraints systematically, and generates behavior prediction with respective control inputs simultaneously. However, MPC approaches are computationally intensive, and the computation burden generally grows as a predictive model more closely approximates a nonlinear plant (in order to achieve more accurate behavior). The computational burden of predictive methods can be addressed through model reduction at the cost of higher divergence between prediction and actual behavior. This work introduces a metric called uncontrollable divergence, and proposes a mechanism using the metric to select the model to use in the predictive controller (assuming that a set of predictive models are available). The metric reveals the divergence between predicted and true states caused by return time and model mismatch. More precisely, a map of uncontrollable divergence plotted over the state space gives the criterion to judge where a specific model can outperform others. With this metric and the mechanism, this work designs a controller that switches at runtime among a set of predictive controllers in which respective models are deployed. The resulting controller is a hybrid predictive controller. In addition to design and runtime tools, this work also studies stability conditions for hybrid model predictive controllers in two approaches. One is average dwell time based, and it does not rely on the offline computation that studies the system properties. The other one uses a reference Lyapunov function instead of multiple Lyapunov functions derived from multiple predictive controllers. This approach implicitly depends on the offline numerical solutions of certain systematic properties. The term "boundedness" is preferable in this context since it accepts numerical error and approximations. Two examples, vertical takeoff and landing aerial vehicle control and ground vehicle control, are used to demonstrate the approach of hybrid MPC.