The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A multi-variable dynamic model of the glutamic acid fermentation process based on neural network is established. Combining the off-line Optimal control method and the on-line adaptive fuzzy neural network control method, the hybrid fuzzy adaptive fermentation process control model is designed. The off-line optimization track is the main control model, while the adaptive fuzzy neural network based...
Aimed at the strong coupling between basis weight and moisture content in papermaking, this paper put forward a decoupling method based on neural network, which is realized by designing a computing network to offset coupling in the process, and makes generalized object's transfer function matrix become diagonal. By decoupling control, we used slurry flow to control basis weight and steam flow to control...
As the liquid position control system has the characteristic of a large time delay, instability and non-linear, a neural network self-adaptive PID controller based on self-adaptive PID and neural network is introduced in this paper, it can optimize and adjust the controller parameters on line. The system simulation is carried out in the end. The simulation results show that the control effect of this...
Generally the application of traditional adaptive control algorithm relies on the mathematic model of system. But mathematic models of some dynamic systems are difficult to establish. According to this actual problem and the existing structure of algorithm, an improved Model Free Adaptive control algorithm based on neural network is put forward in this paper. Within corresponding controller, equivalent...
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...
Linear system theory has made significant contribute to the developments of the classical control's area in the past three decades. The motivation of this paper emerges from the need to develop novel control strategies that can be applied to nonlinear dynamic systems. Furthermore, the need for an adaptive scheme emerges for dealing with time varying systems. Paper presents model reference based neural...
Aiming at the practical plants with strong nonlinear characteristics, a new multi-model internal model control (MIMC) strategy based on Gaussian potential function networks (GPFN) is proposed in this paper. The internal model is represented by GPFN and the corresponding controller can be got directly, which simplifies the control law design and analyses greatly. Meanwhile, the way of model switch...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.