Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Tuning algorithm"”.
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Investigations into implementation of an iterative feedback tuning algorithm into microcontroller
Implementation of an Iterative Feedback Tuning (IFT) and Myopic Unfalsified Control (MUC) Algorithm into microcontroller is investigated in this dissertation. Motivation in carrying out this research emanates from successful results obtained in application of IFT algorithm to various physical …
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An Investigation of the Feasibility of Microscale Adaptive Passive Vibration Neutralizers
… derived and compared to experimental results. A tuning algorithm is derived from a curve-fit of experimental tests on the specific neutralizer. A more generic tuning algorithm is also developed, which does not require testing of the neutralizer for optimal control. Both tuning algorithms are …
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Efficient Algorithms, Hardware Architectures and Circuits for Deep Learning Accelerators
… energy efficiency. Second, we propose a weight tuning algorithm and accelerator co-design, which optimizes the bit representation of weights for energy reduction. Last, we present VideoTime3, an algorithm and accelerator co-design for efficient real-time video understanding with temporal …
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Solver Tuning with Genetic Algorithms
… efficient and automatic mechanism of parameters tuning for a constraint solver is a step towards making constraint programming a more widely accessible technology. Two types of tuning algorithms are discussed in this thesis: single instance tuning algorithms and instance-based tuning algorithms. …
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Robust self-tuning predictive control for industrial applications
The recently introduced self-tuning Generalized Predictive Control (GPC) algorithm based on long range prediction, has been successfully tested in a wide range of industrial control applications. The complicated nature of the GPC algorithm, however, makes it very difficult to apply to it the …
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Optimisation of Smart Grid performance using centralised and distributed control techniques
… part of the Nordic power grid. Finally, a novel tuning algorithm is proposed for iterative distributed MPC which simultaneously optimises both the closed loop performance and the communication overhead associated with the desired control.
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Design of a state-based nonlinear controller
… of thermofluid simulation software requires algorithms which are used to design and implement PI controllers at some operating points of nonlinear industrial processes. In general, the algorithm should be applicable to multivariable plant models which may be nonlinear. In some areas there is …
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Automated Unit Test Generation for the Python Programming Language
… libraries using state-of-the-art evolutionary algorithms. We provide an up-to-date description of the Pynguin framework reflecting its recent advances. Furthermore, we target two previously identified open research problems: (1) The used evolutionary algorithms provide many hyperparameters that …
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Storage management for large scale systems
… up the access to them. Buffer cache management algorithms used in real systems often have many parameters that require careful hand-tuning to get good performance. A self-tuning algorithm is proposed to automatically tune the page cleaning activity in the buffer cache management algorithm by …
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Feedback control of analog neurons and shunting inhibition in dendrites for bio-inspired neuromorphic systems.
… neural mechanisms. The work explores a tuning approach for analog neuron circuits based on the Izhikevich model and advances the use of dendritic circuits implemented with subthreshold MOSFET transistors. A key contribution is the development of a calibration technique for an analog …
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The status and productivity of the Cape hake stock off the west coast of South Africa based on an age-structured production model with different stock-recruitment and fishing selectivity-at-age relationships
… ad hoc tuned VPA is based on the Laurec-Shepherd tuning algorithm and utilizes catch-at-age and effort information. Applications of an age-structured model, which takes both CPUE and catch-at-age data into account, provides similar results to the production model if more weight is given to the …
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Optimising the Optimiser: Meta NeuroEvolution for Artificial Intelligence Problems
Since reinforcement learning algorithms have to fully solve a task in order to evaluate a set of hyperparameter values, conventional hyperparameter tuning methods can be highly sample inefficient and computationally expensive. Many widely used reinforcement learning architectures originate from …
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Development and experimental validation of direct controller tuning for spaceborne telescopes
… Two principal tools are developed: an analysis algorithm that quantifies each sensor/actuator combination's effectiveness for control, and a design engine which tunes a baseline controller to improve performance and/or stability robustness. The sensor/actuator effectiveness indexing tool …
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Intelligent control of a class of nonlinear systems
… is to improve and propose new fuzzy control algorithms for a class of nonlinear systems. In order to achieve the objectives, novel stability theorems as well as modeling techniques are also investigated. Fuzzy controllers in this work are designed based on the fuzzy basis function neural …
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The constrained discrete-time state-dependent Riccati equation technique for uncertain nonlinear systems
… filter (PF), named the combined D-SDRE/PF. Two algorithms for the filtering techniques are provided. Several filtering techniques are compared with challenging numerical examples to show the reliability and efficacy of the proposed D-SDREF and the combined D-SDRE/PF.