Browsing Engineering (Faculty of) by Subject "Nonlinear Model Predictive Control"
Now showing items 1-6 of 6
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Automatic Code Generation of Real-Time Nonlinear Model Predictive Control for Plug-in Hybrid Electric Vehicle Intelligent Cruise Controllers
(University of Waterloo, 2016-08-30)Control systems have always been a vital part of the novel technological advancements of human being in any industry, especially transportation. With the introduction of the idea of autonomous driving, classical control ... -
Fast Nonlinear Model Predictive Control of Quadrotors: Design and Experiments
(University of Waterloo, 2020-01-21)Quadrotor (or quadcopter) is a type of Unmanned Aerial Vehicles (UAVs). Due to the quadrotors simple and inexpensive design, they have become popular platforms. This thesis proposes a computationally fast scheme for ... -
Model-based Control of Upper Extremity Human-Robot Rehabilitation Systems
(University of Waterloo, 2017-12-14)Stroke rehabilitation technologies have focused on reducing treatment cost while improving effectiveness. Rehabilitation robots are generally developed for home and clinical usage to: 1) deliver repetitive and stimulating ... -
Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles
(University of Waterloo, 2017-01-24)The objective of this thesis is to propose a real-time model predictive control (MPC) scheme for the battery thermal management system (BTMS) of given plug-in hybrid electric and electric vehicles (PHEV/EVs). Although ... -
Robust Empirical Model-Based Algorithms for Nonlinear Processes
(University of Waterloo, 2010-07-27)This research work proposes two robust empirical model-based predictive control algorithms for nonlinear processes. Chemical process are generally highly nonlinear thus predictive control algorithms that explicitly account ... -
Robust Nonlinear Model Predictive Control using Polynomial Chaos Expansions
(University of Waterloo, 2015-08-13)The performance of model predictive controllers (MPCs) is largely dependent on the accuracy of the model predictions as compared to the actual plant outputs. Irrespective of the model used, first-principles (FP) or empirical, ...