Greg Martin Pavilion Technologies Austin, TX 78758 [email protected] Mark Gerules Pavilion Technologies Austin, TX 78758 [email protected] Model Predictive Control (MPC), a control algorithm which uses an optimizer to solve for the optimal control moves over a future time horizon based upon a model of the process, has become a standard control technique in the process industries over the past two ...

A dynamic model that considers both linear and complex nonlinear effects extensively benefits the model-based controller development. However, predicting a detailed aerodynamic with good accuracy for unmanned aerial vehicles (UAVs) is challenging due to their irregular shape low Reynolds number behavior. This work proposes an approach full translational dynamics of quadrotor UAV by feedforward ...

In this paper, a second order plant is considered for identification using NN-predictive control technique. The neural network based predictive controller is configured based on MATLAB 7.0. This neural network controller uses a neural network model of plant. It predicts the future performance of the actual plant. The controller uses to calculate the control input. The control input will optimiz...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on wavelet neural network model. Through recursive wavelet neural network...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...