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A multi-step predictive control algorithm based on least squares support vector machines (LS-SVM) model for complex systems with strong nonlinearity is presented. The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel. Based on LS-SVM multi-step predictive outputs, the real process multi-step predictive outputs are expanded into Taylor series...
Aimed at nonlinear MIMO system, a model predictive control (MPC) strategy based on least squares support vector machine (LSSVM) and mutative scale chaos optimization is proposed. Existent method doesn’t consider the constrain of control law and results in some meaningless solution. So the proposed method utilizes mutative scale chaos optimization technique to search control law in the feasible interval...
A new one-step-ahead predictive control algorithm for a family of nonlinear MISO systems is presented. First, least squares support vector machine (LSSVM) with the quadratic multinomial function kernel is used to obtain the off-line nonlinear systemspsila model. Then, the analytical equation which includes the unknown optimal input increment and the known inputs/outputs is derived according to the...
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