Robust design of Terminal ILC with an Internal Model Control using μ-analysis and a genetic algorithm approach

The thermoforming heater temperature setpoints can be automatically tuned with cycle-to-cycle control. Terminal Iterative Learning Control (TILC) is used to adjust the heater temperature setpoints so that the temperature profile at the surface of the plastic sheet converges to the desired temperature. Industrial thermoforming ovens generally have a large number of temperature sensors and heaters, which makes the design of TILC difficult. The proposed TILC design is based on Internal Model Control (IMC). The robustness of a closed-loop system with this TILC algorithm is measured using the μ-analysis approach. A Genetic Algorithm (GA) is used to find the IMC exponential filter parameters giving the most robust closed-loop system. Simulation results are included to show the effectiveness of this robust TILC algorithm.