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 “"Neural Network Control"”.
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Adaptive neural network control of discrete-time nonlinear systems
In this thesis, adaptive neural network control schemes are investigated for five classes of discrete-time nonlinear systems in affine/non-affine form. The systems studied include single-input single-output nonlinear systems, multi-input multi-output nonlinear systems. For affine systems, the …
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Intelligent Neural Network Control System Design and FPGA Based Implementation
<p>This work documents a study of intelligent neural network control system design and implementation for engineering applications. In this study, the effectiveness of single multiplicative neuron (SMN) in place of traditional multi-layer perceptron (MLP) is investigated. The objectives were to (i) …
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Neural network control of space vehicle orbit transfer, intercept, and rendezvous maneuvers
The feasibility of neural networks to control dynamic systems is examined. Control of a one-dimensional problem is initially investigated to develop an understanding of the structure and simulation of the neural networks. A nondimensional problem is also explored to apply a single neural network …
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Neural network control of nonstrict feedback and nonaffine nonlinear discrete-time systems with application to engine control
"In this dissertation, neural networks (NN) approximate unknown nonlinear functions in the system equations, unknown control inputs, and cost functions for two different classes of nonlinear discrete-time systems. Employing NN in closed-loop feedback systems requires that weight update algorithms …
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Comparison of neural and control theoretic techniques for nonlinear dynamic systems
This thesis compares classical nonlinear control theoretic techniques with recently developed neural network control methods based on the simulation and experimental results on a simple electromechanical system. The system has a configuration-dependent inertia, which contributes a substantial …
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Emulating human process control functions with neural networks
This investigation demonstrates that neural networks can perform some of the tasks in controlling complex systems that have been traditionally reserved for humans. Neural networks can be used to fuse different types of knowledge from many sources into a general process model. This technique allows …
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Development of direct torque control with neural network for speed change in 3-phase induction motor
… a technique to develop an improved direct torque control (DTC) with neural network in order to control the speed of the three-phase induction motor. This project will developed using MATLAB software to simulate the outcome for the module designed. The NN controller have to be designed and tuned …
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Neural network applications in the control of power electronic converters
Attempts have recently been made to apply Neural Networks to control systems where they are to deal with any modeling uncertainties that may exist. This thesis proposes the Neural Network controller as a viable alternative to the conventional and widely used PI regulator for the regulation of Power …
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Real time hardware implementation of power converters for grid integration of distributed generation and statcom systems
… and security. This thesis investigates advanced control technology for grid integration of renewable energy sources and STATCOM systems by verifying them on real time hardware experiments using two different systems: d SPACE and OPAL RT. Three controls: conventional, direct vector control and the …
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Nonlinear Control and Robust Observer Design for Marine Vehicles
… and uncertainties. A direct adaptive neural network controller is developed for a model of an underwater vehicle. Radial basis neural network and multilayer neural network are used in the closed-loop to approximate the nonlinear vehicle dynamics. No prior off-line training phase and no …
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A thesis on the application of neural network computing to the constrained flight control allocation problem
The feasibility of utilizing a neural network to solve the constrained flight control allocation problem is investigated for the purposes of developing guidelines for the selection of a neural network structure as a function of the control allocation problem parameters. The control allocation …
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Time-Domain Simulations of Aerodynamic Forces on Three-Dimensional Configurations, Unstable Aeroelastic Responses, and Control by Neural Network Systems
… including structural models, aerodynamics, and control systems, in the time domain. An elastic beam model coupled with rigid-body rotation is developed for the wing structure, and the natural frequencies and mode shapes are found by the finite-element method. A general unsteady vortex-lattice …
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Observer-based event-triggered and set-theoretic neuro-adaptive controls for constrained uncertain systems
… observer-based event-triggered and set-theoretic control schemes are presented to advance the state of the art in neuro-adaptive controls. In the first part, six new event-triggered neuro-adaptive control (ETNAC) schemes are presented for uncertain linear systems. These comprehensive designs offer …
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Neural networks in control engineering
… is to investigate the viability of integrating neural networks into control structures. These networks are an attempt to create artificial intelligent systems with the ability to learn and remember. They mathematically model the biological structure of the brain and consist of a large number of …