Browsing by Subject "GUI"
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Item An automated virtual tool to compute the entire set of proportional integral derivative controllers for a continuous linear time invariant system(2009-05-15) Narasimhan, BharatThis thesis presents the very practical and novel approach of using the Graphical User Interface (GUI) to compute the entire set of Proportional Integral Derivative (PID) controllers given the transfer function or the frequency response of the system under consideration. Though there is a wide spread usage of PID controllers in the industry, until recently no formal algorithm existed on determining a set of PID values that will stabilize the given system. The industry still relies on algorithms like the Ziegler- Nicholas or ad-hoc approaches in determining the value of PID controllers. Also when it comes to model free approaches, the use of Fuzzy logic and Neural network do not guarantee stability of the system. For a continuous Linear Time Invariant system Bhattacharyya and others have developed an algorithm that determines the entire set of PID controllers given the transfer function or just the frequency response of the system. The GUI has been developed based on this theory. The GUI also evaluates the user input performance specifications and generates a subset of stable controllers given the performance criteria for the system. This thesis presents an approach of automating the computation of entire set of stabilizing Proportional Integral Derivative (PID) controllers given the system transfer function or the frequency response data of the system. The Graphical User Interface (GUI) developed bridges the gap between the developed theory and the industry.Item Improving RNA folding prediction algorithms with enhanced interactive visualization software(2016-08) Grant, Kevin Marcus; Markey, Mia Kathleen; Gutell, RobinSoftware improvements from this project will enable new algorithms for RNA folding prediction to be explored. Issues with capacity, extensibility, multi-tasking, usability, efficiency, accuracy and testing in the original program have been addressed, and the corresponding software architecture changes are discussed herein. Previously limited to just hundreds of helices, the software can now display and manipulate million-helix RNAs. Actions on large data sets are now feasible, such as continuous zooming. A new scripting interface adds flexibility and is especially useful for repetitive tasks and software testing. Structural analysis of RNA can be streamlined using the new mechanisms for organizing experiments, running other programs and displaying results (helices, or arbitrary text and images such as statistics). Finally, usability has been enhanced with more documentation, controls and settings.Item Modest : Modeling, Debugging, and Testing distributed programs(2016-12) Rosales, David Andrew; Garg, Vijay K. (Vijay Kumar), 1963-Modest (Modeling, Debugging, and Testing) is a graphical modeling and testing environment for simulating the execution of distributed systems. Its objective is to assist as a learning tool but more importantly to aid in the design and implementation of distributed algorithms. It builds the simulation environment which means that only the algorithm is required from the user to perform testing. Logging and message animations help understand what events have occurred. Modest has the ability to replicate real life scenarios by inflicting network latency, network failures, and server failures. With the ability to quickly customize environment configuration and options, custom algorithm simulation can be initiated in minimal amounts of time. The concept of distributed computing can be complicated and Modest helps to simplify it with a modern user interface design.Item Multi-state PLS based data-driven predictive modeling for continuous process analytics(2012-05) Kumar, Vinay; Flake, Robert H.; Edgar, Thomas F.Today’s process control industry, which is extensively automated, generates huge amounts of process data from the sensors used to monitor the processes. These data if effectively analyzed and interpreted can give a clearer picture of the performance of the underlying process and can be used for its proactive monitoring. With the great advancements in computing systems a new genre of process monitoring and fault detection systems are being developed which are essentially data-driven. The objectives of this research are to explore a set of data-driven methodologies with a motive to provide a predictive modeling framework and to apply it to process control. This project explores some of the data-driven methods being used in the process control industry, compares their performance, and introduces a novel method based on statistical process control techniques. To evaluate the performance of this novel predictive modeling technique called Multi-state PLS, a patented continuous process analytics technique that is being developed at Emerson Process Management, Austin, some extensive simulations were performed in MATLAB. A MATLAB Graphical User Interface has been developed for implementing the algorithm on the data generated from the simulation of a continuously stirred blending tank. The effects of noise, disturbances, and different excitations on the performance of this algorithm were studied through these simulations. The simulations have been performed first on a steady state system and then applied to a dynamic system .Based on the results obtained for the dynamic system, some modifications have been done in the algorithm to further improve the prediction performance when the system is in dynamic state. Future work includes implementing of the MATLAB based predictive modeling technique to real production data, assessing the performance of the algorithm and to compare with the performance for simulated data.Item P2VSIM: A SIMULATION AND VISUALIZATION TOOL FOR THE P2V COMPILER(2010-07-14) Almeida, OscarThe Property Specification Language (PSL) is an IEEE standard which allows developers to specify precise behavioral properties of hardware designs. PSL assertions can be embedded within code written in hardware description languages (HDL) such as Verilog to monitor signals of interest. Debugging simulations at the register transfer level (RTL) is often required to verify the functionality of a design before synthesis. Traditional methods of RTL debugging can help locate failures, but do not necessarily immediately help in discovering the reasons for the failures. The P2VSim tool presents the ability to combine multiple Verilog signals not only instantaneously, but also across multiple clock cycles, producing a graphical display of the state of active PSL assertions in a given RTL simulation. When using the P2VSim tool, users will write PSL assertions directly into their Verilog source files. After the tool searches for and loads the embedded assertions, execution trace monitors for the relevant Verilog signals are dynamically generated and written back into the Verilog source code. P2VSim then invokes an RTL simulator, Modelsim, to generate a simulation execution trace, requiring that the designer has some hardware or software testbench already in place. Next, the input PSL assertions are parsed into time intervals that have logical and temporal properties. These intervals are to be displayed graphically when PSL property checking is performed. Finally, the user is allowed to step through simulation one cycle at a time, while the tool applies the simulation execution trace to the instantiated time intervals, performing PSL property checking at each clock cycle. From this, the user can witness the exact clock cycles when PSL assertions are satisfied or violated, along with the causes of such results.