Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Mathematical models of vapor-compression systems for multivariable control of the refrigerant dynamics and indoor air conditions

Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.Detailed steady and transient state models of vapor compression (VC) systems have been suggested in this work so that the governing parameters of the refrigerant dynamics such as pressure, enthalpy and temperature could be predicted at different operating conditions. The steady and transient state models were validated with experimental data collected during startup and steady state operations. The experimental setup was equipped with a thermostatic expansion valve, a reciprocal compressor and plate heat exchangers for the condenser and evaporator. Recirculated water was adopted as secondary fluid for heat transfer with R-134a refrigerant. The steady state model was developed from first principles with the refrigerant conditions being determined at each junction between the components of the VC system. A steady state matrix was built to determine the model outputs and it could be adopted for similar problems such as steady state modelling of single-condenser-and-multi-evaporators systems. The refrigerant pressures through the evaporator and condenser were in agreement with experiments. Other refrigerant conditions such as enthalpy and temperature through the components were also validated with experiments. The evaporator and condenser modelling in transient state required special attention and Navier-Stokes equations were adopted for this purpose along with a finite volume scheme for discretization of the condenser and evaporator into 3 and n-control volumes. A transient state matrix was also built for outputs’ prediction in transient operating conditions such as startup and shutdown. The refrigerant conditions namely pressure and enthalpy through the evaporator and condenser were validated with experiments. The transient state model was then improved and converted into a control-oriented model with 12 state variables. The control-oriented model considered phase change in the condenser and evaporator namely, superheat, two-phase and subcooling. Model predictive control (MPC) was implemented on the control-oriented model after a model linearization around a steady state point carefully selected from the steady state experiments performed for validation of the steady state modelling. MPC implementation enabled to control superheat and evaporating pressure simultaneously with consideration of the coupling effect between superheat and capacity regulation. MPC was integrated in Simulink with satisfactory performances regarding disturbance rejection and reference tracking. Building up on satisfactory MPC performance for multivariable control of the refrigerant dynamics, a proportional integral derivative (PID)-MPC controller was implemented on a Chiller-Fan coil unit (FCU) to control simultaneously, indoor temperature, humidity and CO2 level with the coupling effect between humidity and temperature taken into consideration. PID was implemented on a sub layer control loop located at the first heat exchanger and fresh air temperature was maintained within settings to level-out with room temperature to prevent from imbalanced loads. Disturbance rejection and set point tracking were satisfactory without necessarily increasing the supply fan and compressor speeds. MPC was implemented on an upper layer control loop located at a secondary heat exchanger to regulate simultaneously indoor humidity, temperature and CO2 level. The coupling effect between humidity and temperature was well taken care of by the MPC loop and CO2 level regulation was performed without additional load as fresh air intake was carefully pre-cooled using the primary heat exchanger controlled with a PID loop. The performance of the sub layer PID was satisfactory with regards to stability, maximum overshoot and settling time whilst reference tracking and disturbance rejection were satisfactory with the upper layer MPC.Electrical, Electronic and Computer EngineeringPhD (Electronic Engineering)Unrestricte

Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization

In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

Defense Technical Information Center thesaurus

This DTIC Thesaurus provides a basic multidisciplinary subject term vocabulary used by DTIC to index and retrieve scientific and technical information from its various data bases and to aid DTIC`s users in their information storage and retrieval operations. It includes an alphabetical posting term display, a hierarchy display, and a Keywork Out of Context (KWOC) display

Time Localization of Abrupt Changes in Cutting Process using Hilbert Huang Transform

Cutting process is extremely dynamical process influenced by different phenomena such as chip formation, dynamical responses and condition of machining system elements. Different phenomena in cutting zone have signatures in different frequency bands in signal acquired during process monitoring. The time localization of signal’s frequency content is very important. An emerging technique for simultaneous analysis of the signal in time and frequency domain that can be used for time localization of frequency is Hilbert Huang Transform (HHT). It is based on empirical mode decomposition (EMD) of the signal into intrinsic mode functions (IMFs) as simple oscillatory modes. IMFs obtained using EMD can be processed using Hilbert Transform and instantaneous frequency of the signal can be computed. This paper gives a methodology for time localization of cutting process stop during intermittent turning. Cutting process stop leads to abrupt changes in acquired signal correlated to certain frequency band. The frequency band related to abrupt changes is localized in time using HHT. The potentials and limitations of HHT application in machining process monitoring are shown