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Implementation Of A Brassboard Prototype Of A Collision Avoidance System For Use In Ground Vehicles, Tyler James Hannis
Implementation Of A Brassboard Prototype Of A Collision Avoidance System For Use In Ground Vehicles, Tyler James Hannis
Theses and Dissertations
Accidental collisions involving wheeled industrial ground vehicles can be costly to repair, cause serious (even fatal) human injury, and lead to setbacks with tight operation schedules. Reduction of vehicle collisions carries numerous safety and financial incentives. In this work, an integrated collision avoidance package is developed to reduce the number of vehicle collisions. Utilizing feedback from on-board sensing devices, a model predictive control (MPC) algorithm predicts control options and paths, then disallows drivers to accelerate and/or induces braking of the vehicle if a collision is imminent. A prototype system is developed, implemented, and tested on an industrial vehicle to mitigate …
Large-Scale Non-Linear Dynamic Optimization For Combining Applications Of Optimal Scheduling And Control, Logan Daniel Beal
Large-Scale Non-Linear Dynamic Optimization For Combining Applications Of Optimal Scheduling And Control, Logan Daniel Beal
Theses and Dissertations
Optimization has enabled automated applications in chemical manufacturing such as advanced control and scheduling. These applications have demonstrated enormous benefit over the last few decades and continue to be researched and refined. However, these applications have been developed separately with uncoordinated objectives. This dissertation investigates the unification of scheduling and control optimization schemes. The current practice is compared to early-concept, light integrations, and deeper integrations. This quantitative comparison of economic impacts encourages further investigation and tighter integration. A novel approach combines scheduling and control into a single application that can be used online. This approach implements the discrete-time paradigm from …
State Measurement Spoofing Prevention Through Model Predictive Control Design, Helen Durand
State Measurement Spoofing Prevention Through Model Predictive Control Design, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
Security of chemical process control systems against cyberattacks is critical due to the potential for injuries and loss of life when chemical process systems fail. A potential means by which process control systems may be attacked is through the manipulation of the measurements received by the controller. One approach for addressing this is to design controllers that make manipulating the measurements received by the controller in any meaningful fashion very difficult, making the controllers a less attractive target for a cyberattack of this type. In this work, we develop a model predictive control (MPC) implementation strategy that incorporates Lyapunov-based stability …
A Python-Based Toolbox For Model Predictive Control Applied To Buildings, Javier Arroyo, Bram Van Der Heijde, Alfred Spiessens, Lieve Helsen
A Python-Based Toolbox For Model Predictive Control Applied To Buildings, Javier Arroyo, Bram Van Der Heijde, Alfred Spiessens, Lieve Helsen
International High Performance Buildings Conference
A PYTHON-BASED TOOLBOX FOR MODEL PREDICTIVE CONTROL APPLIED TO BUILDINGS Javier Arroyoa,b, Bram van der Heijdea,b,c, Lieve Helsena,b, Alfred Spiessensb,c a University of Leuven (KU Leuven), Department of Mechanical Engineering, Leuven, Belgium b EnergyVille, Thor Park, Waterschei, Belgium c VITO NV, Boeretang 200, Mol, Belgium The use of Model Predictive Control (MPC) in Building Management Systems (BMS) has proven to outperform the traditional Rule-Based Controllers (RBC). These optimal controllers are able to minimize the energy use within buildings by taking into account the weather forecast and occupancy profiles. To this end, they anticipate the dynamic behaviour based on a mathematical …
Optimal Dispatch Controller For Fuel Cell Integrated Building, Yashen Lin, Dustin Mclarty, Annabelle Pratt, Brian Ball, Gregor Henze, Genevieve Saur
Optimal Dispatch Controller For Fuel Cell Integrated Building, Yashen Lin, Dustin Mclarty, Annabelle Pratt, Brian Ball, Gregor Henze, Genevieve Saur
International High Performance Buildings Conference
Buildings contribute to around 40% of the total energy consumption in the US. Improvements to building operation offer substantial economic benefits and emissions reductions. Opportunities arise as more renewable energy sources are integrated into the power grid, where the inherent flexibility that buildings can provide become valuable assets for grid services. Stationary fuel cells providing combined heat and power (CHP) add more flexibility to building operation, where both significant electrical and thermal loads need to be met. As the technology matures, improved fuel cell responsiveness allows for advanced dynamic applications to maximize their utility within the building system. The integration …
Preliminary Assessment Of A Weather Forecast Tool For Building Operation, José Agustín Candanedo, Jean-Marc Hardy, Étienne Saloux, Radu Platon, Vahid Raissi-Dehkordi, Alexandre Côté
Preliminary Assessment Of A Weather Forecast Tool For Building Operation, José Agustín Candanedo, Jean-Marc Hardy, Étienne Saloux, Radu Platon, Vahid Raissi-Dehkordi, Alexandre Côté
International High Performance Buildings Conference
Although the potential of model predictive control (MPC) for the operation of buildings is widely recognized, as of today its adoption has been rather limited. This is partly due to the lack of user-friendly software tools for MPC, such as tools to facilitate the incorporation of forecast information in building automation systems. In view of this, CanmetENERGY, a research centre of Natural Resources Canada, has developed CanMETEO, a software tool free of charge aimed at obtaining weather forecast data and make it available in a useful and practical format for building operators. CanMETEO, which was released officially in August 2017, …
Model Predictive Control Of Inverter Air Conditioners Responding To Real-Time Electricity Prices In Smart Grids, Maomao Hu, Fu Xiao
Model Predictive Control Of Inverter Air Conditioners Responding To Real-Time Electricity Prices In Smart Grids, Maomao Hu, Fu Xiao
International High Performance Buildings Conference
Real-time electricity prices provide great opportunities for residential consumers to participate in demand response (DR) programs in smart grids. One of the biggest challenges faced by the DR program participants are the lack of advanced DR-enabled residential appliances which can automatically respond to real-time electricity prices, especially the lack of DR-enabled air conditioners which are the major contributors to electricity bills. In this paper, we aim to use model predictive control (MPC) techniques to control the inverter air conditioners. Instead of simply adjusting temperature set-points in the conventional DR control strategies, the MPC controllers are used to directly control the …
Gekko Optimization Suite, Logan Beal, Daniel Hill, Ronald Abraham Martin, John Hedengren
Gekko Optimization Suite, Logan Beal, Daniel Hill, Ronald Abraham Martin, John Hedengren
Faculty Publications
This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic equations (DAE) problems. By blending the approaches of typical algebraic modeling languages (AML) and optimal control packages, GEKKO greatly facilitates the development and application of tools such as nonlinear model predicative control (NMPC), real-time optimization (RTO), moving horizon estimation (MHE), and dynamic simulation. GEKKO is an object-oriented Python library that offers model construction, analysis tools, and visualization of simulation and optimization. In a single package, GEKKO provides model reduction, an object-oriented library for data reconciliation/model predictive control, and …
Smart Technologies For Oil Production With Rod Pumping, Brigham Wheeler Hansen
Smart Technologies For Oil Production With Rod Pumping, Brigham Wheeler Hansen
Theses and Dissertations
This work enables accelerated fluid recovery in oil and gas reservoirs by automatically controlling fluid height and bottomhole pressure in wells. Several literature studies show significant increase in recovered oil by determining a target bottomhole pressure but rarely consider how to control to that value. This work enables those benefits by maintaining bottomhole pressure or fluid height. Moving Horizon Estimation (MHE) determines uncertain well parameters using only common surface measurements. A Model Predictive Controller (MPC) adjusts the stroking speed of a sucker rod pump to maintain fluid height. Pump boundary conditions are simulated with Mathematical Programs with Complementarity Constraints (MPCCs) …
Integrated Scheduling And Control In Discrete-Time With Dynamic Parameters And Constraints, Logan Beal, Damon Petersen, David R. Grimsman, Sean Warnick, John Hedengren
Integrated Scheduling And Control In Discrete-Time With Dynamic Parameters And Constraints, Logan Beal, Damon Petersen, David R. Grimsman, Sean Warnick, John Hedengren
Faculty Publications
Integrated scheduling and control (SC) seeks to unify the objectives of the various layers of optimization in manufacturing. This work investigates combining scheduling and control using a nonlinear discrete-time formulation, utilizing the full nonlinear process model throughout the entire horizon. This discrete-time form lends itself to optimization with time-dependent constraints and costs. An approach to combined SC is presented, along with sample pseudo-binary variable functions to ease the computational burden of this approach. An initialization strategy using feedback linearization, nonlinear model predictive control, and continuous-time scheduling optimization is presented. The formulation is applied with a generic continuous stirred tank reactor …
Adaptive Control For Inflatable Soft Robotic Manipulators With Unknown Payloads, Jonathan Spencer Terry
Adaptive Control For Inflatable Soft Robotic Manipulators With Unknown Payloads, Jonathan Spencer Terry
Theses and Dissertations
Soft robotic platforms are becoming increasingly popular as they are generally safer, lighter, and easier to manufacture than their more rigid, heavy, traditional counterparts. These soft platforms, while inherently safer, come with significant drawbacks. Their compliant components are more difficult to model, and their underdamped nature makes them difficult to control. Additionally, they are so lightweight that a payload of just a few pounds has a significant impact on the manipulator dynamics. This thesis presents novel methods for addressing these issues. In previous research, Model Predictive Control has been demonstrably useful for joint angle control for these soft robots, using …
Constrained Multiobjective Pso And T-S Fuzzy Models For Predictive Control, Ali Thamallah, Anis Sakly, Faouzi M'Sahli
Constrained Multiobjective Pso And T-S Fuzzy Models For Predictive Control, Ali Thamallah, Anis Sakly, Faouzi M'Sahli
Turkish Journal of Electrical Engineering and Computer Sciences
Multiobjective optimization problems are still a challenging area in the field of control system engineering. In this context, the current study describes a new multivariable predictive control scheme formulated by using the T-S fuzzy modeling method and a new constrained multiobjective PSO algorithm. The T-S fuzzy modeling technique is applied to forecast the behaviors of the nonlinear system. It also aims at establishing some conditions so that the proposed control loop is asymptotically stable. The obtained experimental results show that the combination of the philosophy of the T-S fuzzy model and multiobjective PSO is very good in the controlling of …
Damping Wide-Area Oscillations In Power Systems: A Model Predictive Controldesign, Emrah Biyik, Munir Husein
Damping Wide-Area Oscillations In Power Systems: A Model Predictive Controldesign, Emrah Biyik, Munir Husein
Turkish Journal of Electrical Engineering and Computer Sciences
Electromechanical oscillations in power systems have been observed ever since synchronous generators were interconnected to provide reliability and higher generation capacity, and they have become a severe threat for the safe and economic operation of modern interconnected power grids. To dampen these oscillations, wide-area damping controllers (WADCs) have been introduced by utilizing wide-area measurement systems and synchronized phasor measurement units. In this paper, we present a systematic approach for designing WADCs using a model predictive control (MPC) technique to damp interarea oscillations in the power system. The MPC controller computes optimal control signals for the excitation system of a remote …