Advanced Control of Pressure Inside a Surgical Chamber Using AI Methods

This paper is presenting the mathematical model of the process dynamics describing the hyperbaric chambers and the comparison between some controllers for the pressure control to improve the efficiency and the safety inside the hyperbaric chamber, to avoid barotraumas and to reject the disturbances that may occur; the design methods of the PID and the adaptive PID controllers are presented. The parameters of the PID controller are computed based on the Ziegler-Nichols method, whilst the adaptive PID controller is implemented using artificial intelligence algorithms, learnt by neural networks. The adaptive PID controller is obtained through the discretization of the classical PID controller, with different sampling times; the coefficients of this transfer function are learnt using a neural network and the conversion to the continuous time is performed by computing the proper sampling-time which will improve the most the system performances of the technological process.