Optimization Design of LQR Controller Based on Genetic Algorithm
Applying genetic algorithm to LQR controller design, leveraging its global search capability to optimize weighting matrices using active suspension performance metrics as objective functions, thereby improving LQR design efficiency and performance. Implementation involves chromosome encoding for matrix parameters, fitness evaluation based on system response, and iterative optimization through selection, crossover, and mutation operations.