Feedback Control Design Assignment help

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• Motivation, differential equations, complex variables,  matrix methods, Block diagrams, dynamic systems, Linearization of nonlinear equations, State-space description, Response of dynamic systems: transfer functions, pole and zero, locations on dynamic behavior, Stability, More effects of feedback, Frequency response of open loop systems, Designing feedback compensation using frequency response, Root locus technique.
•  ziegler-nichols tuning, feedforward block diagrams, Feedback control, dynamic models, Laplace, LTI properties, In state variable form, Linearization, Pole-zero locations & time response, Stability, routh criteria, Root loci examples, Dynamic compensation,  bode plots, Nyquist stability criterion, Stability margins, Lead-lag compensation
• State space: analysis & equations, transfer function, Controllability, observability, State feedback, Pole placement, Observer design, Linear quadratic regulator, Discrete time control, Control systems, Modeling, Laplace transforms, Modeling of op-amps and electric motors, State space representation, Transfer functions and block diagram algebra, Time response, Rise time, settle time, overshoot,  Steady state error.
• Design via root locus, Frequency response techniques, Bode plots, Design via frequency response, Difference equations and the z-transform, Discrete-time controller design, Modeling dynamic systems, Laplace transforms and solving for system response , Transfer functions, Poles and zeros and system response, Final Value Theorem, Block diagrams, Response to sinusoidal inputs, Closed-loop system, Performance criteria, System type tracking errors disturbance rejection
• The Routh array PID control, controllers from a root locus perspective, compensators, Lead lag and notch compensators, Frequency domain analysis and Bode plots , Frequency domain analysis and controller synthesis, Nyquist stability
  Design engineering, Spacetechnology, Shape, MIMO, Uncertainty, Stabilization, Design Constraints, Loopshaping, Advanced Loopshaping, Model Matching, Design for Performance, Flexible Beam, Norm Minimization, Stability Margin Optimization, Optimal Robust Stability, Conformal Mapping Gain Margin Optimization, Phase Margin Optimization, Spectral Factorization

Low Dimensional Modeling Assignment help

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Development and analysis of such models for problems arising in neuroscience and, as time permits, fluid dynamics mathematical modeling and analysis techniques which can be applied to problems from engineering, physics, chemistry, and biology.

• Neuroscience Modeling
• conductance-based neuron models, such as the Hodgkin-Huxley equations
• simple reductions of conductance-based neuron models
• nullcline analysis of neuron models
• integrate-and-fire neuron models
• phase response curves and isochrons for periodically firing neurons
• dynamics of coupled neurons
• reduction of coupled neuron systems to phase models
• analysis of phase-locked solutions for coupled neuron systems
• analysis of bursting neuron models
• Fluid Dynamics Modeling
• basics of fluid dynamics
• derivation of low-dimensional models using Galerkin projection
• analysis of the Lorenz equations for fluid convection, a prototypical chaotic system
• analysis of a model for shear flow turbulence derived using Galerkin projection
• basics of center manifold reduction
• derivation of low-dimensional models using symmetry methods
• analysis of a model for binary fluid convection derived using symmetry methods
• derivation of low-dimensional models using the proper orthogonal decomposition
• analysis of a model for shear flow turbulence derived using the proper orthogonal decomposition
• pseudospectra analysis of linear models for shear flow turbulence
•  Classifier Type: Decision Trees, Discriminant Analysis, Logistic Regression, SVM Support Vector Machines, Nearest Neighbor, Ensembles

Matlab HDL Code Generation and Verification Assignment help

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Matlab HDL Code Generation and Verification Homework help & Matlab HDL Code Generation and Verification tutors offer 24*7 services . Send your Matlab HDL Code Generation and Verification assignments at support@globalwebtutors.com or else upload it on the website. Instant Connect to us on live chat for Matlab HDL Code Generation and Verification assignment help & Matlab HDL Code Generation and Verification Homework help.

Topics for HDL Code Generation and verification  

• Preparing Simulink Models for HDL Code Generation, Generating: HDL code & test bench, generated HDL code with an HDL simulator, Interfacing external HDL code, Interfacing vendor party IP.
• Preparing a multirate model for generating HDL code, Generating HDL code with single clock pins, multiple clock pins, speed optimizations, area optimizations, hardware description languages, VHDL fundamentals.
• behavioral model, structural models, syntax , basic rules, design entry, behavioral simulation, logic synthesis , synthesizeable code development, design mapping to standard cells , field programmable gate array.
•  FPGA or ASIC implementation, Perform design iterations, target-independent VHDL or Verilog code for FPGAs and ASICs.
• Generating HDL code and testbench for a compatible Simulink model, Performing speed and area optimizations, Integrating handwritten code and existing IP, Verifying generated HDL code using testbench and cosimulation and HDL simulator, Synthesizing the generated HDL code using a HDL synthesis tool, Documenting and Tracing HDL Code, HDL Coding Standard.

Desktop and Web Deployment using Matlab Assignment Help

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Desktop and Web Deployment using Matlab Homework help & Desktop and Web Deployment using Matlab tutors offer 24*7 services . Send your Desktop and Web Deployment using Matlab assignments at support@globalwebtutors.com or else upload it on the website. Instant Connect to us on live chat for Desktop and Web Deployment using Matlab assignment help & Desktop and Web Deployment using Matlab Homework help.

MATLAB based programs can be deployed as standalone applications, add-ins for Microsoft Excel, and software components that can be integrated into web and enterprise applications. You can deploy any MATLAB program covering a range of industries and applications such as data analytics, semiconductor/electronics, manufacturing systems, image processing, aerospace/defense, and financial services.

All applications and components are encrypted to protect your intellectual property and can be shared royalty free.When compared with manually recoding algorithms, deploying your MATLAB applications and components provides advantages, such as:

• Domain experts can maintain ownership of ideas, algorithms, and applications.
• Software developers have the flexibility to integrate a common algorithm with different programming languages and platforms.
• Organizations gain efficiency by avoiding time consuming and error prone recoding, as well as easily adopting algorithm improvements throughout the application’s lifecycle.

Algorithm Development using Matlab Assignment Help

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Matlab provides integrated capabilities for the exploration of algorithm design and for the effective deployment of the embedded software and desktop. The environment of the matlab helps to explore the multiple approaches and ideas. 

The high level language automatically maintain the low level language like Matlab. Matlab enables to edit, debug and test different kind of design without linking or compiling. It customize the rich set of algorithms and functions which is already implemented in matlab language. Matlab consist of various tools for the effective algorithm design including:

MATLAB Editor: - It provides the features of editing and debugging like stepping by the individual line of code, setting break points

MATLAB Profiler: - It measures the performance of the program and identifies that areas which needs to be modify for the improvement.

Code Analyzer: - It automatically checks the problems in the code and immediately recommend the modification to maximize the performance.

Command Window: - It is basically used to enter data, manipulating command, programs and display results.

Additional tools: Besides it there are some additional tool which is used to compare the data files. After comparing the data files and code it provides the report showing dependencies of the file, code coverage, and annotated reminders.

Mathematical Modeling using Matlab Assignment help

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Online Mathematical Modeling using Matlab Assignment help with topics like Linear Programming, Nonlinear Programming, Difference Equations, Simulation Modeling, One Variable Optimization, Sensitivity Analysis, Multivariable Optimization, Constraint Optimization.

Computational Methods for Optimization, Linear Programming -, Simplex Method, Dynamic Models, Continuous Time Dynamical Models, Discrete Time Dynamical Systems are considered very complex & an expert help is required in order to solve the assignments based on topics like Stability of Equilibria. Phase Portraits, Control Theory, Pontryagin, Maximum Principle, Pontryagin Maximum Principle, Simulation of Dynamic Models, Euler Method, Chaotic Behavior in Nonlinear Systems.

Building models, Flow diagrams, mathematical equations, Testing models, Studying models, black box or white box models, groups of variables: decision variables, input variables, state variables, exogenous variables, random variables, and output variables, dynamical systems, statistical models, differential equations, or game theoretic models.

Technology and mathematics: document creation (LaTeX), computer algebra software (Maxima), spreadsheet programming, and wiki authoring, Difference equations, Applications of linear algebra, Stochastic processes, Data analysis, abstract theory and applications, Geometry of hypersurfaces, Large time behaviour for diffusive Hamilton, area-preserving crystalline curvature flow equation

Stochastic Performance Modeling Assignment help

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Stochastic Performance Modeling

• Open/closed queueing networks
• Operational laws
• M/M/1 queue Burke’s theorem and reversibility
• M/M/k queue
• M/G/1 queue
• G/M/1 queue
• P h/P h/k queues and their solution using matrix-analytic methods
• Arrival theorem and Mean Value Analysis
• Analysis of scheduling policies (e.g., Last-Come-First Served; Processor Sharing)
• Jackson network and the BCMP theorem (product form networks)
• Asymptotic analysis (M/M/k queue in heavy/light traf- fic, Supermarket model in mean-field regime)