An approach for the design of fuzzy control laws for tracking control of a large class of mechanical systems is proposed. The approach employs the framework of Lyapunov’s stability theory to formulate a class of control laws that guarantee convergence of the tracking errors to within speci3cation limits in presence of bounded parameter uncertainties and input disturbances. The proposed control ...

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...

A fuzzy logic control (FLC) is designed to maintain constant tension for tandem rolling mills. Genetic algorithm (GA) is used as self-organization technique for FLC to locate the optimal parameters. Simulation results verify the superior performance of genetic fuzzy controller. Keywords-tension control, fuzzy logic, genetic fuzzy system, rolling mill.

in this study, a novel variable impedance control for a lower-limb rehabilitation robotic system using voltage control strategy is presented. the majority of existing control approaches are based on control torque strategy, which require the knowledge of robot dynamics as well as dynamic of patients. this requires the controller to overcome complex problems such as uncertainties and nonlinearit...

Fuzzy logic control is a relatively new technology and hence it needs rigorous comparative analyses with other well-established conventional control schemes. Further, fuzzy controller stability analysis is a major hindrance for its popularity among control engineers. This paper shows how stable &zzy controllers may be synthesized for a typical AGV from the perspective of variable structure syst...

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which...

A hierarchical intelligent control system paradigm for a vision-based autonomous driving scheme is presented for a leader-lollowing HMMWV. The paper shows how fuzzy logic is employed to represent knowledge at the organizational level, resolve conflicting perceived information and plan the best path for the vehicle. After introducing the methodology, simulation and experimental aspects for reali...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...

The degree of vagueness of variables, process description, and automation functions is considered and is shown where quantitative and qualitative knowledge is available for design and information processing within automation systems. Fuzzy-rule-based systems with several levels of rules form the basis for different automation functions. Fuzzy control can be used in many ways, for normal and for...

Common uses of fuzzy logic control today are found in relatively simple applications in products. These applications only scratch the surface of the potential of fuzzy logic control in complex mechatronic systems. In order to demonstrate the utility of fuzzy logic in complex device control, a fuzzy logic fly-by-wire system has been developed for a model airplane. The model airplane is a complex...