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A multivariable nonlinear predictive control algorithm based on online fuzzy modeling and discrete optimization is presented for a family of complex systems with strong nonlinearity. The algorithm consists of two part: The first part is online fuzzy modeling using fuzzy clustering and linear identification, the second part is discrete optimization of the control action based on the principle of Branch and Bound method. In the process of fuzzy modeling, the unsupervised fuzzy competitive algorithm and a discarding criterion are introduced to ensure the fuzzy model can trace the system dynamics in time. The effectiveness and advantage of the presented algorithm are illustrated two numerical examples.