in this paper, an adaptive neuro fuzzy inference system (anfis) based control is proposed for the tracking of a micro-electro mechanical systems (mems) gyroscope sensor. the anfis is used to train parameters of the controller for tracking a desired trajectory. numerical simulations for a mems gyroscope are looked into to check the effectiveness of the anfis control scheme. it proves that the sy...

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 tracking control approach is proposed for a class of single-inputsingle-output (SISO) nonlinear systems in which the unknown continuous functions may be nonlinearlyparameterized. During the controller design procedure, the fuzzy logic systems (FLS) in Mamdani type are applied to approximate the unknown continuous functions, and then, based on the minimal learnin...

this paper presents a stable new algorithm for force/position control in robot manipulators. in this algorithm, position vectors are measured by sensors and then used in the control law. since using force sensor has some issues such as high costs and technical problems, an approach is presented to overcome these issues. in this respect, force sensor is replaced by an adaptive fuzzy estimator to...

Abstract. Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based ∞ H control scheme for a class of uncertain nonlinear timedelay systems. Firstly, the fuzzy T-S model is used to approximate the nonlinear systems, and an observer is designed to observe the system states, and the fuzzy control law of the fuzzy mo...

Though traditional neural networks and fuzzy logic are powerful universal approximators, however without some refinements, they may not, in general, be good approximators for adaptive systems. By extending fuzzy sets to qualitative fuzzy sets, fuzzy logic may become universal approximators for adaptive systems. Similar considerations can be extended to neural networks.

In this paper, an adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time delays and unmeasured states. By using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive state observer is designed for estimating the unmeasured states. By combining the adaptive backstepping technique with adaptive fuzzy control desi...

some applications are critical and must designed Fault Tolerant System. Usually Voting Algorithm is one of the principle elements of a Fault Tolerant System. Two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. Majority confronts with the problem of threshold limits and voter of weight...

some applications are critical and must designed Fault Tolerant System. Usually Voting Algorithm is one of the principle elements of a Fault Tolerant System. Two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. Majority confronts with the problem of threshold limits and voter of weight...

in recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...