Data–driven predictive control (DPC) is becoming an attractive alternative to model as it requires less system knowledge for implementation and reliable data increasingly available in smart engineering systems. Two main approaches exist within DPC: the subspace approach, which estimates prediction matrices (unbiased large data) behavioral, data-enabled uses Hankel (allows optimizing bias/varian...

This paper purposed a new generalized predictive control based on state feedback theory for the large inertia and large delay characteristics of the discrete reheat steam temperature plant. The idea is to compensate the large inertia and delay characteristics of the plant by the state feedback theory and the generalized plant by predictive control. The simulation results show that that the new ...

AbstructThis application paper addresses the control of a nonminimum-phase plant with variable large orders and delays. The process concerned is full penetration gas tungsten arc welding. Based on an analysis of accepted adaptive algorithms, the generalized predictive control algorithm presented by Clarke et al. is selected as the principal control strategy. An adaptive generalized predictive d...

Abstact-This application paper addresses the control of a nonminimum-phase plant with variable large orders and delays. The process concerned is futl penetration gas tungsten arc weld' ing. Based on an analysis of accepted adaptive algorithms, the generalized predictive control algorithm presented by Clarke' Mohtadi and Tirffs is selected as the principal control strategy. An adaptive generaliz...

this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays.  an optimization procedure for a neural mpc algorithm based on this model is then developed. the p...

A new generalized predictive control algorithm for a kind of input-output bilinear system is proposed in the paper (BGPC). The algorithm combines bilinear and linear terms of I/O bilinear system, and constitutes an ARIMA model analogous to linear systems. Using optimization predictive information fully, the algorithm carries out multi-step predictions by recursive approximation. The heavy compu...

A usual argument against GPC is its demand for processing power. In industry, however, this is not a serious argument if better control performance can be reached. As the development of new processors with increased performance takes place rather rapidly, the lag of processing power never was a long-term issue to prevent new algorithms from being introduced. This paper presents a practical real...

the control of car following is essential due to its safety and its operational efficiency. for this purpose, this paper builds a model of car following behavior based on armax structure from a real traffic dataset and design a model predictive control (mpc) system. based on the relative distance and relative acceleration of each instant, the mpc predicts the future behavior of the leader vehic...