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Distributed Fuzzy and Stochastic Observers for Nonlinear Systems

Lendek, Z. (author)

Many problems in decision making, control, and monitoring require that all variables of interest, usually states and parameters of the system, are known at all times. However, in practical situations, not all variables are measurable or they are not measured due to technical or economical reasons. Therefore, these variables need to be estimated...

doctoral thesis 2009

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Soft Computing Methods in Flight Control System Design

Oosterom, M.L.J. (author)

doctoral thesis 2005

document

Bioprocess modeling and optimization: Fed-batch clavulanic acid production by streptomyces clavuligerus

Roubos, J.A. (author)

doctoral thesis 2002

document

Distributed Estimation and Control for Robotic Networks

Simonetto, A. (author)

Mobile robots that communicate and cooperate to achieve a common task have been the subject of an increasing research interest in recent years. These possibly heterogeneous groups of robots communicate locally via a communication network and therefore are usually referred to as robotic networks. Their potential applications are diverse and...

doctoral thesis 2012

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Efficient optimization methods for freeway management and control

Cong, Z. (author)

Due to the rapid growth of human population, and jobs being distributed unevenly in different locations, daily commuting is required more than ever, which in its turn is creating a huge socio-economic issue: traffic congestion. In order to prevent, or at least to alleviate this problem, trafficmanagement and control is urgently required. This...

doctoral thesis 2015

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Nonlinear State and Parameter Estimation for Hopper Dredgers

Stano, P.M. (author)

A Trailing Suction Hopper Dredger (TSHD) is a ship that excavates sediments from the sea bottom while sailing. In situ material is excavated with a special tool called the Drag-Head, then it is hydraulically transported through a pipe to the hopper where it is temporarily stored. After the dredging is completed the collected material is...

doctoral thesis 2013

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Complexity Reduction in Fuzzy Systems

Setnes, M. (author)

doctoral thesis 2001

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Model-based Feedforward Control for Inkjet Printheads

Khalate, A.A. (author)

In recent years, inkjet technology has emerged as a promising manufacturing tool. This technology has gained its popularity mainly due to the facts that it can handle diverse materials and it is a non-contact and additive process. Moreover, the inkjet technology offers low operational costs, easy scalability, digital control and low material...

doctoral thesis 2013

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Reinforcement Learning on autonomous humanoid robots

Schuitema, E. (author)

Service robots have the potential to be of great value in households, health care and other labor intensive environments. However, these environments are typically unique, not very structured and frequently changing, which makes it difficult to make service robots robust and versatile through manual programming. Having robots learn to solve...

doctoral thesis 2012

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Fuzzy Control of Multiple-Input Multiple-Output Processes

Mollov, S. (author)

doctoral thesis 2002

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Model-Based Control of Drinking-Water Treatment Plants

Van Schagen, K.M. (author)

The drinking water in the Netherlands is of high quality and the production cost is low. This is the result of extensive research in the past decades to innovate and optimise the treatment processes. The processes are monitored and operated by motivated and skilled operators and process technologists, which leads to an operator-dependent,...

doctoral thesis 2009

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Ant Colony Optimization for Control

Van Ast, J.M. (author)

The very basis of this thesis is the collective behavior of ants in colonies. Ants are an excellent example of how rather simple behavior on a local level can lead to complex behavior on a global level that is beneficial for the individuals. The key in the self-organization of ants is communication through pheromones. When an ant forages for...

doctoral thesis 2010

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Model-based control of hopper dredgers

Braaksma, J. (author)

The modern trailing suction hopper dredgers are advanced ships that are equipped with many automation systems that can be controlled with integrated computer systems from the bridge. From the operators it is expected that they generate the right set-points for all these systems. The latest ships are designed such that one operator is responsible...

doctoral thesis 2008

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Online Model Learning Algorithms for Actor-Critic Control

Grondman, I. (author)

Classical control theory requires a model to be derived for a system, before any control design can take place. This can be a hard, time-consuming process if the system is complex. Moreover, there is no way of escaping modelling errors. As an alternative approach, there is the possibility of having the system learn a controller by itself while...

doctoral thesis 2015

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Knowledge Discovery and Pavement Performance: Intelligent Data Mining

Miradi, M. (author)

The main goal of the study was to discover knowledge from data about asphalt road pavement problems to achieve a better understanding of the behavior of them and via this understanding improve pavement quality and enhance its lifespan. Four pavement problems were chosen to be investigated; raveling of Porous Asphalt Concrete (PAC), cracking of...

doctoral thesis 2009

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Probabilistic Motion Planning for Multi-Robot Systems

Zhu, H. (author)

Planning safe motions for multi-robot systems is crucial for deploying them in real-world applications such as target tracking, environmental monitoring, and multi-view cinematography. Traditional approaches mainly solve the multi-robot motion planning problem in a deterministic manner, where the robot states and system models are perfectly...

doctoral thesis 2022

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Interaction-Aware Motion Planning in Crowded Dynamic Environments

Ferreira de Brito, B.F. (author)

Autonomous robots will profoundly impact our society, making our roads safer, reducing labor costs and carbon dioxide (CO2) emissions, and improving our life quality. However, to make that happen, robots need to navigate among humans, which is extremely difficult. Firstly, humans do not explicitly communicate their intentions and use intuition...

doctoral thesis 2022

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Sample effficient deep reinforcement learning for control

de Bruin, T.D. (author)

The arrival of intelligent, general-purpose robots that can learn to perform new tasks autonomously has been promised for a long time now. Deep reinforcement learning, which combines reinforcement learning with deep neural network function approximation, has the potential to enable robots to learn to perform a wide range of new tasks while...

doctoral thesis 2020

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Automatic synthesis of supervisory control systems

Najafi, E. (author)

Sequential composition is an effective supervisory control method for addressing control problems in nonlinear dynamical systems. It executes a set of controllers sequentially to achieve a control specification that cannot be realized by a single controller. Sequential composition focuses on the interaction between a collection of pre-designed...

doctoral thesis 2016

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Reinforcement learning in continuous state and action spaces

Busoniu, I.L. (author)

The framework of dynamic programming (DP) and reinforcement learning (RL) can be used to express important problems arising in a variety of fields, including e.g., automatic control, operations research, economy, and computer science. From the perspective of automatic control, DP/RL expresses an optimal control problem for general, nonlinear,...

doctoral thesis 2009