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This paper presents a new PID controller model based on series leading correction, and its extension. By tuning the parameter(s) of the new PID controller, the controlled system's dynamic performance can be improved significantly. Not only reducing the maximum overshoot, but also shortening the setting time significantly. The results of simulations show the superiority of the new PID controller.
This paper presents a new PID controller model with series leading correction. The controller has a tuning parameter, by tuning the parameter, the new PED controller can reduce the controlled system's maximum overshoot and setting time significantly, so as to improve the controlled system's stability and rapidity of step response. Simulation results show the superiority of the new PID controller.
PID algorithms for batch reactor's temperature control of special plants or systems have been used widely. Adaptive PID control is also used to handle the model changing problems. This paper presents a new adaptive control that is based on PID algorithm, expert system and neural networks. Its main structure is a generalized PID (GPID) controller. Neural networks is applied to adjust the GPID parameters...
Model based batch reactor's temperature control algorithms for special plants or systems have been used widely. Adaptive control is also used to handle the model changing problems. This paper presents a new model free adaptive control that is based on expert system, fuzzy control and neural networks. Its main structure is a model free neural networks and the initial values of the neural networks parameters...
In this paper, the time-delay dependent robust stability problem is investigated for Markovian jump discrete-time neural networks with mode-dependent time delays. The jumping parameters are considered as discrete-time, discrete-state Markov process. The linear factional uncertainty is considered, it means that less conservative results will be obtained than using norm-bounded parameter uncertainties...
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