The adaptive generalized predictive control (GPC), which combines the process of system identification using recursive least-squares (RLS) algorithm and the process of generalized predictive feedback control design, has been presented and successfully implemented on testbeds. In this paper, the adaptive GPC algorithm is extended when the disturbance measurement signal is available for feedforwa...

Dynamic Positioning Systems (DPS) is a technique of automatically maintaining the position of vessels within the specified limits by controlling thrusters. This paper introduces a fuzzy predictive control to position vessels. Firstly, the mathematical model of vessel is created and simplified. Then, we use feedforward compensation to decouple the system. The T-S model is identified by Fuzzy C-M...

The key point of the networked control systems is that conventional generalized predictive control algorithm cannot deal with random delays, packet losses and vacant sampling. In this paper, the time-stamped generalized predictive control (TSGPC) with fuzzy rectification is proposed to deal with this problem. The TSGPC use timestamped to calculate the real delay and the LMS adaptive recursive a...

Predictive Control is one of the most powerful techniques in process control, but its application in non-linear processes is challenging. This is basically because the optimization method commonly used limits the kind of functions which can be minimized. The aim of this work is to show how the combination of Genetic Algorithms (GA) and Generalized Predictive Control (GPC), what we call GAGPC, c...

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...

In this paper, an Output Feedback Model Predictive Control for nonlinear systems is presented. The proposed output feedback control consists of the well known robust controller NCGPC (Nonlinear Continuous Time Generalized Predictive Control) and an open loop observer (a simulated model in parallel) in order to estimate the output derivatives and a regulation filter used to account for plant/mod...

In this paper, we obtain  Bayesian prediction intervals as well as Bayes predictive estimators under square error loss for generalized order statistics when the distribution of the underlying population belongs to a family which includes several important distributions.