A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...

Benchmarking systems from a sample of reference buildings need to be developed to conduct benchmarking processes for the energy efficiency of commercial buildings. However, not all benchmarking systems can be adopted by public users (i.e., other non-reference building owners) because of the different methods in developing such systems. An approach for benchmarking the energy efficiency of comme...

In cite{beh}, the authors claimed by a counterexample that the cross product definition in cite{molo} is not correct and thus the proposed technique is false. In this note, we show that this assertion is ‎incorrect.

New types of systems of fuzzy relation inequalities and equations, called weakly linear, have been recently introduced in [J. Ignjatović, M. Ćirić, S. Bogdanović, On the greatest solutions to weakly linear systems of fuzzy relation inequalities and equations, Fuzzy Sets and Systems 161 (2010) 3081–3113.]. The mentioned paper dealt with homogeneous weakly linear systems, composed of fuzzy relati...

In this paper, we investigate the general fuzzy linear system of equations.  The  main aim of this paper is based on the embedding approach. We find the necessary and sufficient conditions for the existence of fuzzy solution of the mentioned systems.  Finally, Numerical examples are presented to more illustration of the proposed model.

The m×n fuzzy linear systems are studied in [1-3] based on Friedman's method. Recently, Ezzati [3] proposed a new method for solving fuzzy linear systems, numerically better than Friedman's method. The main aim of this paper, is to develop Ezzati's method for solving m×n fuzzy linear systems. Numerical examples are used to illustrate the proposed model.

One of the challenges in engineering biological devices is to precisely control the number of parts in each cell. Automobile engineers do not worry about control mechanisms for variation in the number of wheels on a car—if an engineer designs a car with four wheels, then all the cars roll off the assembly line with four wheels. But biology is dynamic, and biological circuits change continuously...