Decentralized PI tracking control for non-Gaussian large-scale interconnected distribution systems

This paper addresses a novel constrained decentralized shaping control problem for a class of nonlinear large-scale interconnected distribution systems. Such systems are generated by multiple output conditional probability density functions (PDFs) and exist in multi-channel non-Gaussian stochastic processes. Following a decoupled B-spline approximation to the output conditional PDFs, the large-scale interconnected weight systems are introduced to characterize the correlation in different weight vectors and further to describe the dynamic relation between the control input and weight vectors. The decentralized PI controller with delay dependent analysis is designed to ensure the system stability and convergence of the dynamic tracking error to zero. Moreover, the L2−L∞ norm from the disturbance to the controlled output is reduced to a prescribed level and the state constraint requirement can also be guaranteed. The effectiveness of the developed algorithm is verified by simulations of paper making process.