Control configuration selection based on RNGA for non-square multivariable processes

The paper extends the conception of relative normalized gain array (RNGA) to control configuration selection for nonsquare multivariable processes. Since RNGA can give static and dynamic interaction measurements among inputs and outputs only by investigating the steady-state and the transient information of the process transfer function, preferable input/output paring for multivariable processes can be provided by a RNGA-based criterion. For non-square multivariable processes with outputs more than inputs, the introduction of non-square RNGA (NS-RNGA) will make the suggestion of eliminating which output variables or adding extra inputs to control which output variables. Compared with the conventional relative gain array (RGA) based method, the proposed technique gives a more accurate interaction assessment and loop configuration. Case studies illustrate the effectiveness of the proposed method for non-square multivariable processes.