Explore MATLAB source code curated for "LQR控制" with clean implementations, documentation, and examples.
Single inverted pendulum LQR control simulation featuring two distinct approaches for reduced-order state observer design with practical implementation examples and code-related analysis
Inverted Pendulum Modeling and LQR Control with MATLAB Implementation, including simulation result curves and technical explanations
Single Inverted Pendulum LQR Control Simulation - Implementation of optimal control theory through state-space modeling and quadratic performance optimization to minimize control objectives using MATLAB/Simulink environments.
LQR control implementation for a single inverted pendulum system, consisting of two main components: a Simulink model and MATLAB m-file with detailed control algorithm implementation.
This study employs Newtonian dynamics methodology to establish a mathematical model of a single inverted pendulum system, followed by comparative simulation analysis of PID control (based on classical control theory), LQR control (based on optimal control theory), and fuzzy logic control methods. The simulation implementation includes system linearization techniques, state-space formulations for LQR design, and membership function configuration for fuzzy controllers. The analytical results provide theoretical guidance for research in this field, with practical insights into controller tuning parameters and stability margin comparisons.
MATLAB implementation of helicopter LQR control featuring an 8-dimensional state equation model, including complete dynamics analysis and control system design
1) Implementation of LQG design methodology for unmanned helicopter control systems, 2) Linear Quadratic Regulator (LQR) control strategy applied to helicopter dynamics, 3) Analysis of induction machine speed-torque characteristics with performance modeling
Simulation of LQR Control for Single Inverted Pendulum System with Reduced-Order Observer Design