1. An automatic tuning control system for an air pollution control system comprises: the air pollution control system; a temperature sensor arranged downstream of a reactor, an SO 2 sensor arranged in a filter duct, and a slurry level sensor arranged in a head tank above the reactor sensor in the air pollution control system, with each of the sensors operative to measure a system parameter to obtain a system parameter measurement; a proportional integral derivative (PID) control for each of the sensors operative to receive the parameter measurement, to compare the received parameter measurement to a system parameter set point, and to control an air pollution control system valve device to affect the system parameter of slurry flow to the reactor based on the temperature sensor measurement, to control an air pollution control system valve device to affect the system parameter of dilution water flow based on the SO 2 sensor measurement, and to control an air pollution control system valve device to affect the system parameter of slurry flow to the head tank based on the slurry level sensor measurement, with each proportional integral derivative (PID) control operable for simultaneous tuning; one or more supervisory multivariable predictive control (MPC) controller layers operable to control the proportional integral derivative (PID) control, with the one or more supervisory multivariable predictive control (MPC) controller layers operable for tuning following simultaneous tuning of each proportional integral derivative (PID) control; and an integrated MPC/PID control design comprising a multivariable predictive control (MPC) controller layer operative to generate the system parameter set point used by the proportional integral derivative (PID) control; wherein the automatic tuning control system is operable for automatically tuned control of the air pollution control system by tuning of the proportional integral derivative (PID) control, the one or more supervisory multivariable predictive control (MPC) controller layers and the integrated MPC/PID control design using particle swarm optimization through simulation using one or more dynamic models mathematically representing air pollution control system behavior.