A Takagi-Sugeno Fuzzy Model for Greenhouse Climate

Observers for Takagi-Sugeno fuzzy systems

We focus on the analysis and design of two different sliding mode observers for dynamic Takagi-Sugeno (TS) fuzzy systems. A nonlinear system of this class is composed of multiple affine local linear models that are smoothly interpolated by weighting functions resulting from a fuzzy partitioning of the state space of a given nonlinear system subject to observation. The Takagi-Sugeno fuzzy system...

Takagi-Sugeno Fuzzy Modeling for Process Control

LMI-based tracking control for Takagi-Sugeno fuzzy model

This paper deals with the problem of tracking control for Takagi-Sugeno fuzzy model. An LMI (Linear Matrix Inequality) formulation is suggested to make possible the convergence of the state vector of the continuous-time system to a desired one using a new approach, called MultiQuadratic Fuzzy Lyapunov (MQFL). A fourth order unstable nonlinear system is studied to illustrate the efficiency of th...

A Takagi-Sugeno Fuzzy Gain-Scheduler

AbstructIn the present paper we describe the design of a fuzzy gain scheduler for tracking a reference trajectory of a nonlinear autonomous system. The proposed fuzzy gain scheduling method has two major advantages over the existing crisp gain scheduling methods. First, it provides a general and formally motivated method for the interpolation of available local control laws into a global gain s...

Energy Decomposition Model Using Takagi-Sugeno Neuro Fuzzy

Decomposition analysis is useful method to determine significant factors contribute towards the development of energy consumption. This paper presents factors decomposition of electricity consumption in Indonesia’s household sector using artificial intelligent method. The proposed artificial intelligent technique used in this study is the Neuro Fuzzy Takagi-Sugeno (NFTS) network, which is worke...