Controls and Control Theory Commons^™

Trajectory-Based Model Predictive Control For Rotary Crane Sway Suppression With Only Horizontal Boom Actuation, Haryson J. Nyobuya

Tanzania Journal of Engineering and Technology (TJET)

Safety is of biggest importance in construction and industrial activities involving rotary cranes. These cranes are huge and responsible of moving large parts or/and materials from different positions. Now operating these cranes tend to be subdue to pay load oscillations when moving the load for which is extremely dangerous when not suppressed. This study proposes the generation of trajectory using Model predictive control approach with reduced control horizon compared to state horizon. Reduced control horizon design reduces computational time for trajectory generation while maintaining the pay-load sways to a minimum. In this approach the complex dynamic model is reduced to …

A Dynamically Efficient Predictive Controller For Voltage Stability In A Dc To Dc Boost Converter, Giovanni Reyna

Electrical and Computer Engineering ETDs

Reliable voltage regulation has become a critical issue with increase demand in modern power electronic applications. This study presents a Model Predictive Controller (MPC) for voltage regulation in DC-to-DC boost converters. A closed loop analytical MPC framework is created with the purpose of computing optimal duty cycles to maintain a stable output voltage under varying load conditions, input changes, and disturbances.

To evaluate the performance of the MPC we set the controller against a comparative analyzing with a traditional cascading proportional integral (PI) controller. The proposed controller design is specifically targeted to improve dynamic efficiency during the converter’s transient events. …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

Model Predictive Control Of Energy Systems For Heat And Power Applications, Chethan Ramakrishna Reddy

Dissertations, Master's Theses and Master's Reports

Building and transportation sectors together account for two-thirds of the total energy consumption in the US. There is a need to make these energy systems (i.e., buildings and vehicles) more energy efficient. One way to make grid-connected buildings more energy efficient is to integrate the heating, ventilation and air conditioning (HVAC) system of the building with a micro-scale concentrated solar power (MicroCSP) sys- tem. Additionally, one way to make vehicles driven by internal combustion engine (ICE) more energy efficient is by integrating the ICE with a waste heat recovery (WHR) system. But, both the resulting energy systems need a smart …

Learning-Based Predictive Control Approach For Real-Time Management Of Cyber-Physical Systems, Roja Eini

Theses and Dissertations

Cyber-physical systems (CPSs) are composed of heterogeneous, and networked hardware and software components tightly integrated with physical elements [72]. Large-scale CPSs are composed of complex components, subject to uncertainties [89], as though their design and development is a challenging task. Achieving reliability and real-time adaptation to changing environments are some of the challenges involved in large-scale CPSs development [51]. Addressing these challenges requires deep insights into control theory and machine learning. This research presents a learning-based control approach for CPSs management, considering their requirements, specifications, and constraints. Model-based control approaches, such as model predictive control (MPC), are proven to be …

Development Of Autonomous Vehicle Motion Planning And Control Algorithm With D* Planner And Model Predictive Control In A Dynamic Environment, Somnath Mondal

Dissertations, Master's Theses and Master's Reports

The research in this report incorporates the improvement in the autonomous driving capability of self-driving cars in a dynamic environment. Global and local path planning are implemented using the D* path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm is tested using Model-In-the-Loop (MIL) method with the help of MATLAB® Driving Scenario Designer and Unreal Engine® Simulator by Epic Games®. Different …

Real-Time Predictive Control Of Connected Vehicle Powertrains For Improved Energy Efficiency, Joseph Oncken

Dissertations, Master's Theses and Master's Reports

The continued push for the reduction of energy consumption across the automotive vehicle fleet has led to widespread adoption of hybrid and plug-in hybrid electric vehicles (PHEV) by auto manufacturers. In addition, connected and automated vehicle (CAV) technologies have seen rapid development in recent years and bring with them the potential to significantly impact vehicle energy consumption. This dissertation studies predictive control methods for PHEV powertrains that are enabled by CAV technologies with the goal of reducing vehicle energy consumption.

First, a real-time predictive powertrain controller for PHEV energy management is developed. This controller utilizes predictions of future vehicle velocity …

Modeling And Control Of Maximum Pressure Rise Rate In Rcci Engines, Aditya Basina

Dissertations, Master's Theses and Master's Reports

Low Temperature Combustion (LTC) is a combustion strategy that burns fuel at lower temperatures and leaner mixtures in order to achieve high efficiency and near zero NOx emissions. Since the combustion happens at lower temperatures it inhibits the formation of NOx and soot emissions. One such strategy is Reactivity Controlled Compression Ignition (RCCI). One characteristic of RCCI combustion and LTC com- bustion in general is short burn durations which leads to high Pressure Rise Rates (PRR). This limits the operation of these engines to lower loads as at high loads, the Maximum Pressure Rise Rate (MPRR) hinders the use of …

Intelligent Transportation Systems, Hybrid Electric Vehicles, Powertrain Control, Cooperative Adaptive Cruise Control, Model Predictive Control, Hadi Kazemi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Information obtainable from Intelligent Transportation Systems (ITS) provides the possibility of improving the safety and efficiency of vehicles at different levels. In particular, such information has the potential to be utilized for prediction of driving conditions and traffic flow, which allows us to improve the performance of the control systems in different vehicular applications, such as Hybrid Electric Vehicles (HEVs) powertrain control and Cooperative Adaptive Cruise Control (CACC). In the first part of this work, we study the design of an MPC controller for a Cooperative Adaptive Cruise Control (CACC) system, which is an automated application that provides the drivers …

Model-Based Control Of An Rcci Engine, Akshat Abhay Raut

Dissertations, Master's Theses and Master's Reports

Reactivity controlled compression ignition (RCCI) is a combustion strategy that offers high fuel conversion efficiency and near zero emissions of NOx and soot which can help in improving fuel economy in mobile and stationary internal combustion engine (ICE) applications and at the same time lower engine-out emissions. One of the main challenges associated with RCCI combustion is the difficulty in simultaneously controlling combustion phasing, engine load, and cyclic variability during transient engine operations.

This thesis focuses on developing model based controllers for cycle-to-cycle combustion phasing and load control during transient operations. A control oriented model (COM) is developed by using …

Predictive Control Of Power Grid-Connected Energy Systems Based On Energy And Exergy Metrics, Meysam Razmara

Dissertations, Master's Theses and Master's Reports

Building and transportation sectors account for 41% and 27% of total energy consumption in the US, respectively. Designing smart controllers for Heating, Ventilation and Air-Conditioning (HVAC) systems and Internal Combustion Engines (ICEs) can play a key role in reducing energy consumption. Exergy or availability is based on the First and Second Laws of Thermodynamics and is a more precise metric to evaluate energy systems including HVAC and ICE systems. This dissertation centers on development of exergy models and design of model-based controllers based on exergy and energy metrics for grid-connected energy systems including HVAC and ICEs.

In this PhD dissertation, …