This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh-Nagumo (FHN) neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirect...

A new method for designing multivariable model reference adaptive control system is presented. In many adaptive control approaches, at least the following two assumptions regarding the plant have to be made. (1) The number of plant poles and zeros is known. (2) The plant is the minimum phase. The proposed method can avoid these restrictions by using the adaptive controller designed for an autor...

the paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. some mathematical vector models were obtained for control system multicriterion quality indices with due ...

We present DevFS, a direct-access file system embedded completely within a storage device. DevFS provides direct, concurrent access without compromising file system integrity, crash consistency, and security. A novel reverse-caching mechanism enables the usage of host memory for inactive objects, thus reducing memory load upon the device. Evaluation of an emulated DevFS prototype shows more tha...

this paper presents a theoretical approach to implementation of the “multi-realization of nonlinear mimo systems”. this method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. in this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for ...

Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...

This paper presents the application of direct model reference adaptive control (DMRAC) on a nonlinear model of coupled-tank liquid level control system through simulation. The coupled-tank liquid level control system is regarded as the relevant plant to emulate the process control in petrol and chemical industries. The processing plants in these industries largely involve in controlling the liq...

this paper focuses on the non-fragile guaranteed cost control problem for a class of t-s fuzzy time-varying delay systems with local bilinear models. the objective is to design a non-fragile guaranteed cost state feedback controller via the parallel distributed compensation (pdc) approach such that the closed-loop system is delay-dependent asymptotically stable and the closed-loop performance i...

A nonlinear mathematical model of a feed-batch fermentation process of Bacillus thuringiensis (Bt.), is derived. The obtained model is validated by experimental data. Identification and direct adaptive neural control systems with and without integral term are proposed. The system contains a neural identifier and a neural controller, based on the recurrent trainable neural network model. The app...