Hybrid Controller Based on Numerical Methods for Chemical Processes with a Long Time Delay

Abstract

A hybrid control framework is proposed as an alternative for long time delays in chemical processes. The hybrid approach mixes the numerical methods in an internal mode control (IMC) structure, which uses the particle swarm optimization (PSO) algorithm to improve the adjustment of the controller parameters. Simulation tests are carried out on linear systems of high order and inverse response, both with dominant delay, and tests on a nonlinear process (chemical reactor). The performance of the proposed controller is stable and satisfactory despite nonlinearities in various operating conditions, set-point changes, process disturbances, and modeling errors. In addition, experimental tests were performed on a setup composed of two heaters and two temperature sensors mounted on an Arduino microcontroller-based board called the Temperature Control Laboratory (TCLab), with an additional software delay introduced. The merits and drawbacks of each scheme are analyzed using radar charts, comparing the control methods with different performance measures for set-point and disturbance changes. Furthermore, the new controller uses PSO to improve the tuning parameters.

Causality Analysis of the Green Ammonia Synthesis Process Using the Convergent Cross Mapping Algorithm

“…Mehrkanoon et al estimated the time delay using least-squares support vector machines in the control system of a continuous, stirred, heated tank, where accurate estimates were provided even if significant noise or unmeasured additive disturbances were present. Herrera et al proposed a hybrid control scheme for processes with a long delay using Smith predictor compensation. The application to an Arduino-based temperature control lab demonstrated a reduced control error.…”