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Performance assessment of control loops is of great importance for industrial production. This paper proposes a novel performance assessment and controller tuning method for non-Gaussian MIMO feedback control systems. First, an algorithm based on minimum entropy and mutual information projection to latent structure (ME-PLS) is proposed to replace the canonical correlation analysis algorithm (CCA). The ME-PLS algorithm decomposes the system data into independent components related to inputs and outputs, and this algorithm applies to both Gaussian and non-Gaussian systems. Each pair of principal components represents a virtual non-Gaussian control loop. Next, the performance of each virtual loop is calculated separately with the non-Gaussian minimum entropy method. Finally, a least absolute deviation iterative algorithm based on the CARMA model (CARMA-LADI) is given to identify the parameters of each virtual loop and to give the actual controller tuning directions based on the relationships obtained by the ME-PLS algorithm.INDEX TERMS control loop performance assessment, independent components, MIMO system, maximum mutual information, minimum entropy