Permanent Magnet Synchronous Generator (PMSG) Model Design for Wind Turbines
Design of PMSG model for wind turbines with Simulink simulation mdl file, including system modeling, control strategy implementation, and performance analysis
Explore MATLAB source code curated for "设计" with clean implementations, documentation, and examples.
Design of PMSG model for wind turbines with Simulink simulation mdl file, including system modeling, control strategy implementation, and performance analysis
MATLAB-implemented multi-objective particle swarm optimization program based on Pareto dominance theory, validated through multiple benchmark test functions with excellent performance results.
Design a prototype filter that serves as the foundation for constructing high-performance filter banks with diverse applications across signal processing systems.
Full-order observer design using Simulink implementation, which can be extended to derive reduced-order observers through appropriate state-space transformations and matrix manipulations.
MATLAB code implementation for recursive Gabor filter design, originating from international research institutions, offering significant reference value for both research and practical applications, featuring optimized algorithms and modular function architecture.
Implementing Inverted Pendulum Full-State Observer Design through Simulation in MATLAB/Simulink Environment with Code Implementation Details
This resource covers the design of bandpass and bandstop filters using a Butterworth filter package. The package includes: bendpass.m (bandpass filter implementation), bendblock.m (bandstop filter algorithm), SE144.wav (input audio file for processing). Requires placing SE144.wav in C: drive root directory. Processed outputs: bendpass.wav (bandpass-filtered audio saved to C:\) and bendblock.wav (bandstop-filtered audio saved to C:\).
MATLAB-based Digital Equalizer Design and Implementation with FIR Filter Algorithms and Frequency Response Analysis
Implementation of orthogonal filter bank design using MATLAB, including algorithm details and key function descriptions.
Designing a Kalman Filter to extract useful signals from noisy environments, including system modeling, parameter tuning, and noise adaptation techniques.