T2FSMC has succesfully overcome the chattering and robustness problems implementing on mobile inverted pendulum robot. The remaining drawback is the gain scale factor of controller determination of Fuzzy Type 2 that is still doing trial and error. Firefly Algorithm will be used in this paper to determine the best gain scale factor of controller of Fuzzy Type 2 automatically. Utilized as objecti...

Model-predictive control, which is an alternative to conventional optimal control, provides controller solutions to many constrained and nonlinear control problems. However, even when a good model is available, it may be necessary for an expert to specify the relationship between local model predictions and global system performance. We present a satisficing fuzzy logic controller that is based...

In this paper, the robust stability analysis of a fuzzy vehicle lateral system with perturbed parameters is presented. Firstly, the fuzzy controller can be linearized by utilizing the describing function method with experiments. After the describing function is obtained, the stability analysis of the vehicle lateral control system with the variations of velocity and friction is then carried out...

This paper presents the stability and robustness analyses of uncertain nonlinear control systems. TO proceed with the analysis, the uncertain nonlinear system is represented by a fuzzy model with uncertainties. Based on this model, under a single-grid-point (SGP) approach, a fuzzy controller is designed to close the feedback loop. A simple stability criterion is derived by estimating the norm o...

Abstract: In this paper a state feedback controller is designed to stabilize a discrete-time nonlinear and uncertain system. The Takagi Sugeno (TS) fuzzy model with norm-bounded uncertainties is considered for modelling the nonlinear system. Beyond stability, a mixed (LQ/H∝) index is also considered, which simultaneously guarantees an upper bound of LQ cost and is robust for unknown external di...

The problem of robust fuzzy control for a class of nonlinear fuzzy impulsive singular perturbed systems with time-varying delay is investigated by employing Lyapunov functions. The nonlinear delay system is built based on the well-known T–S fuzzy model. The so-called parallel distributed compensation idea is employed to design the state feedback controller. Sufficient conditions for global expo...

This paper addresses the robust H∞ fuzzy control problem for nonlinear uncertain systems with state and input time delays through Takagi–Sugeno (T–S) fuzzy model approach. The delays are assumed to be interval time-varying delays, and no restriction is imposed on the derivative of time delay. Based on Lyapunov–Krasoviskii functional method, delay-dependent sufficient conditions for the existenc...

A robust fuzzy control is developed for robot manipulators to guarantee both global stability and Performance. Robot dynamics under consideration may include large nonlinear uncertainties, such as nonlinear load variations and unmodelled dynamics. Fuzzy sets are chosen based on performance requirements and stability regions of the control system. For each fuzzy set, a sub-control is designed, b...

Abst rac t The slip power recovery configuration is an attractive scheme of variable speed drive, with high efficiency and low converter rating; however, high performance control has being difficult. In this paper, novel applications of fuzzy logic for the intelligent control of a slip power recovery system are presented. A direct fuzzy logic controller and an adaptive fuzzy controller, based o...

A fuzzy controller equipped with an adaptive algorithm and two supervisors is developed in this work to achieve tracking performances for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. The convergence of the training algorithm is guarantied by a gradient projection law. The effect of both the approximation errors and the external disturbance...