AbstractAn experimental evaluation of methods to analyze process resilience based on internal model control (IMC) has been performed. A pilot plant consisting of two coupled distillation columns was instrumented for control studies using an LSI 11/23 microcomputer. Two alternative sets of inputs were chosen and the two full 7 (all outputs) × 4 (all inputs) transfer matrix models of the pilot plant were identified. From these models, a large number of potential 3 × 3 control structures were first screened for different levels of achievable control performance using the newly developed tools for resilience analysis. Without the need for simulation and with minimal computational effort these new techniques allow prediction of the effect of nonminimum phase characteristics, input constraints, and model uncertainty on achievable closed‐loop performance. The resilience analysis results were found to be in agreement with qualitative physical intuition. To more fully investigate the usefulness and precision of the resilience analysis, three control structures for maintaining three product compositions from a distillation system were studied experimentally. The design and performance of IMC for this complex system is demonstrated and compared with single‐loop PID controllers combined with a dynamic deco