PID vs. Artificial Neural Network Control of an H-Bridge Voltage Source Converter

Taylor Barto* Department of Electrical and Computer Engineering Cleveland State University Cleveland, Ohio 44115 December 2, 2014 Abstract An H bridge voltage source converter connected to a supercapacitor, knee motor, and ideal gear ratio is simulated with both a PID controller and an artificial neural network. The performance of the two controllers are compared to each other based upon their ability to track a reference knee angle trajectory and to harness energy inside the supercapacitor. The PID controller was able to match the trajectory with an RMS tracking error of 5.1 degrees while the ANN controller had and RMS error of 103.97 degrees. The PID controller was not able to harness as much energy as the ANN controller with 578.9 joules lost over the gait cycle compared to 53.62 joules lost for the ANN controller.