In this study, an artificial neural network (ANN) model-based self-tuning PIDcontrol method is proposed for the control of multi-input-multi-output (MIMO)nonlinear systems. A single layer, feed-forward ANN structure is trained viainput and output data randomly collected from the system and classified aslearning, test, and validation data to obtain the system model. The obtainedmodel is utilized in an adaptive PID control scheme in conjunction with twodifferent optimization methods for PID tuning and control. Using this scheme,PID parameters can be tuned to their optimum values and the system can becontrolled simultaneously. The performance of the proposed method isdemonstrated via experimental studies.