Improvements on multiloop control design via net load evaluation

The plant-wide control problem is a very important topic in process control. A particular control structure design will define (restrict) the future operability degree for the plant under study. Classical control policies (decentralized or full) are not always the best solution. In this context a systematic and generalized strategy to solve the multivariable plant-wide control problem is proposed here. The methodology called minimum square deviation (MSD) considers several points such as the optimal controlled variables (CVs) selection based on the sum of square deviation (SSD) and controller structure design supported by net load evaluation (NLE) analysis. The overall problem is combinatorial and is solved by accounting several steady-state tools and new indexes minimizing the heuristic load. Four well-known case studies are presented and other approaches taken from the literature are accounted for the sake of comparison. A robust stability test, μ-tools, is also performed for concluding about the control policies.

► Generalize the SSD index via Frobenius norm for set point and disturbances effects. ► Mathematical insight about the SSD minimization accounting the subprocess properties. ► Generalize the NLE index for MIMO controller design with stability test by considering set point and disturbance effects. ► Systematic and generalized tool for plant-wide control which minimizes the heuristic load. ► Comparison with other approaches. Conclusion in Shen, Cai, and Li (2010) is modified.