Takagi-Sugeno Fuzzy Scheme Research Articles

Observer-based fault detection for continuous–discrete systems in T-S fuzzy model

The observer design problem for fault detection is considered for nonlinear continuous–discrete systems with Takagi–Sugeno fuzzy scheme and finite frequency specification in this paper. Two finite frequency performance indices H− and H∞ are introduced to evaluate the sensitivity to faults and the robustness against disturbances in finite frequency domains. Based on the H−/H∞ technique, this research is aimed to design a fault detection observer for the addressed system. Sufficient conditions are derived to guarantee the asymptotic stability, fault sensitivity and disturbance robustness of the residual error system. Simulation results further demonstrate effectiveness of the proposed approach.

Nonlinear control design using Takagi-Sugeno fuzzy applied to under-actuated visual servo system

This paper presents the Takagi-Sugeno (TS) fuzzy control design for nonlinear stabilization and tracking control of a ball on plate system. To deal with the plant nonlinearity and the fuzzy convergence issue, we formulate the parallel distributed compensator (PDC) TS fuzzy model to characterize the global behaviour of the nonlinear system and synthesize a feasible control framework using a velocity compensation scheme. The nonlinear dynamics of the ball on plate system is obtained using the Euler-Lagrangian energy based approach. To identify the moving objects in the video stream, a background subtraction algorithm using thresholding technique is formulated. Moreover, the stability analysis of the TS fuzzy control is reduced to linear matrix inequality (LMI) problem and solved using the Lyapunov direct method. The potential benefits of the proposed control structure for real time test cases are experimentally assessed using hardware in loop (HIL) testing on a ball on plate system. Experimental results substantiate that the TS fuzzy scheme can significantly improve not only the tracking performance but also the robustness of the closed loop system.

A Hybrid Least Square-Fuzzy Bacterial Foraging Strategy for Harmonic Estimation

Harmonic estimation for a signal distorted with additive noise has been an area of interest for researchers in many disciplines of science and engineering. This work presents a new algorithm based on the foraging behavior of E. coli bacteria in our intestine to estimate the harmonic components present in power system voltage/current waveforms. The basic foraging strategy is made adaptive, through a Takagi-Sugeno fuzzy scheme, depending on the operating condition to make the convergence faster. Besides, the harmonic estimation is linear in amplitude and nonlinear in phase. As the proposed algorithm does not rely on Newton-like gradient descent methods, this is used for phase estimation whereas the linear least square scheme estimates the amplitude, thereby presenting the hybrid method. The improvement in %error, as well as the processing time compared with the conventional discrete Fourier transform and genetic algorithm method is demonstrated in this paper. Besides, the performance is quite acceptable even in the presence of decaying dc component as well as to change in amplitude and phase angle of harmonic components.