an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. therefore, it is widely adopted for complex industrial process control. in this work, laguerre function based adaptive model predictive control algorithm (ampc) was implemented to control continuous stirred tank rea...

Model predictive control (MPC) for uncertain systems in the presence of hard constraints on state and input is a non-trivial problem, challenge increased manyfold absence measurements. In this paper, we propose an adaptive output feedback MPC technique, based novel combination observer robust MPC, single-input single-output discrete-time linear time-invariant systems. At each time instant, prov...