Publication

Proposed, compared and simulated algorithms for Iterative learning controller, stabilizing a Chemical Reactor with uncertain parameters, initial output resetting error and input disturbance.

Proposed a robust adaptive control system by using Gamma neural networks for a nonlinear and unstable Inverted Pendulum system, showing higher applicability and adaptivity in encountering disturbance and colored noise situations compared to structures such as MLP and TDL networks.

Proposed, optimized and simulated Speed Control algorithms using Genetic Algorithm, fuzzy logic and PID controllers, achieving minimum torque ripple and high control performance.

Developed a method for time series prediction of chaotic systems using Genetic Algorithm to increase the time horizon of prediction.