In this paper, we introduce the notion of Q-fuzzification of M-subgroups in a near-ring and investigate some related properties. Characterization of Anti Q-fuzzy Msubgroups with respect to s-norm is given.

This paper proposes a simple but efficient technique to control 3D overhead crane. Load must track a desired path and not sway more than a reasonable range.The proposed method uses PID control for trolley to track the desired path and fuzzy control compensation to eliminate the load swing. Only the projection of swing angle is applied to design the fuzzy controller. No plant information of cran...

In this paper, we made an attempt to study the algebraic nature of antifuzzy subsemiring of a semiring and we introduce the some theorems in anti-fuzzy subsemiring of a semiring. 2000 AMS Subject classification: 03F55, 06D72, 08A72.

We investigate a notion of non-Archimedean fuzzy anti-n-normed spaces and prove the Mazur-Ulam theorem in the spaces. AMS subject classification: primary 46S10; secondary 47S10; 26E30; 12J25.

The behavior of many mechanical systems, such as overhead cranes, can be predicted through intuitive observation of their motion under various forces. Mathematical modeling of an overhead crane shows that it is highly coupled. Nonetheless, it is surprisingly easy for an experienced crane operator to drive payloads to target positions with minimal cable swing. This observation naturally promotes...

This paper proposes a simple but efficient technique to control 3D overhead crane. Load must track a desired path and not sway more than a reasonable range.The proposed method uses PID control for trolley to track the desired path and fuzzy control compensation to eliminate the load swing. Only the projection of swing angle is applied to design the fuzzy controller. No plant information of cran...

This paper proposed a method to identify nonlinear systems via the fuzzy weighted least squares support machine (FW-LSSVM). At first, we describe the proposed modeling approach in detail and suggest a fast learning scheme for its training. Because the training sample data of independent variable and dependent variable has a certain error, and we obtain the sample which has a certain fuzziness f...

The single input rule modules (SIRMs) based type-1 fuzzy inference systems (SIRM-T1FISs), which assign each input item with a rule module, can greatly reduce the number of fuzzy rules and have found lots of applications. This paper extends SIRMT1FISs to the interval type-2 case to achieve better performance. Furthermore, the properties of the SIRMs based interval type-2 fuzzy inference systems ...

A new interacting multiple model (IMM) algorithm using intelligent input estimation (IIE) is proposed for maneuvering target tracking. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown target acceleration by a fuzzy system using the relation between the residuals of the maneuvering filter and the non-maneuvering filter. The gene...

This paper proposes an approach to fuzzy modeling of Anti-lock Braking Systems (ABSs). The local state-space models are derived by the linearization of the nonlinear ABS process model at ten operating points. The Takagi-Sugeno (T-S) fuzzy models are obtained by the modal equivalence principle, where the local state-space models are the rule consequents. The optimization problems are defined in ...