Fuzzy systems of linear equations play a vital role in various applications of engineering, science and finance problems. This paper proposes a new method for solving Fully Fuzzy System of Linear Equations (FFSLE) using the linear programming problem approach. There is no restriction on the elements of coefficient matrix. The proposed method is able to solve the system, when the elements of the...

In this paper, for nonlinear, time-varying and delayed system, PID parameters self-tuning fuzzy control was applied to a level process. The method of using VC++ programming to realize fuzzy control algorithm and obtain the discrete fuzzy control table is proposed, which simplified the computing process greatly. Furthermore, combing the inquiry of fuzzy control table and PID function module in P...

Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, prompt to nonlinear control issues due the flexibility joints friction motors within dynamics of their rigid part. To address these issues, Linear Matrix Inequalities (LMIs) Parallel Distributed Compensation (PDC) approaches implemented Takagy-Sugeno Fuzzy Model (T-SFM). We propose ...

Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability.  The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability is a way to present the reliability function uncertainly using fuzzy parameters. In the proposed...

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...

In this paper, an adaptive fuzzy controller based on fuzzy neural network is proposed for uncertain nonlinear systems. The main advantages are the simple design, no requirement of system model, and release of fixed universal range of fuzzy output. A fuzzy neural network is applied to on-line identify the control system and provide sufficient information of the adaptive laws for the proposed fuz...

Fuzzy control of robot manipulators with a decentralized structure is facing a serious challenge. The state-space model of a robotic system including the robot manipulator and motors is in non-companion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. Considering the problem, causes and solutions, we use voltage control strategy and convergence analy...

in industrial robotic manipulator, due to the presence of quite nonlinear dynamic and structural and nonstructural uncertainties, a precise model is not easily obtained. as a result, designing a controller with a suitable function based on system model is a challenging issue. sliding mode control is a robust control with numerous applications which can overcome the aforementioned uncertainties....