Uncertainty Of Membership Functions Research Articles

IT2 fuzzy adaptive containment control for fractional-order heterogeneous multi-agent systems with input saturation

In this paper, the containment control problem of second-order nonlinear heterogeneous multi-agent system is studied. In order to deal with complex uncertainties such as unknown parts, uncertainties, and input constraints in the system, we designed a distributed fuzzy adaptive controller. The interval type-II (IT2) fuzzy set is adopted to deal with the uncertainty of membership functions. We construct a matrix equality and a matrix inequality to deal with the asymmetric Laplace matrix. The controller designed is simple and the designed controller only uses the information of itself and its neighbors. Therefore, it is very easy to be compensated in practice. Finally, a simulation example is introduced to verify the effectiveness of the proposed methods.

Admissibility Analysis for Interval Type-2 Fuzzy Descriptor Systems Based on Sliding Mode Control.

This paper is concerned with the sliding mode control of nonlinear singular systems in terms of the interval type-2 (IT2) fuzzy model. To better approximate the nonlinear systems, the modeling errors are considered in the IT2 fuzzy model. The uncertainties in membership functions are expressed based on their boundedness. Admissibility conditions are obtained via a linear matrix inequalities approach. A new reaching law-based sliding controller is presented by choosing a typical sliding surface to analyze the sliding motion, such that all of the input gains are allowed to be different and the chattering of the system can be minimized with a guaranteed H∞ performance. The feasibility of the proposed control method is verified by simulation results.

Modeling attribute control charts by interval type-2 fuzzy sets

Fuzzy attribute control charts, where data are classified into conforming/nonconforming product units, are used to monitor fuzzy fractions of nonconforming units for variable sample sizes and the fuzzy number of nonconforming units for constant sample sizes. Data defined as quality characteristics can be imprecise due to the subjective decisions of the quality control operator. Type-2 fuzzy set theory deals with ambiguity associated with the uncertainty of membership functions by incorporating footprints and modeling high-level uncertainty. In this paper, the structure of an interval type-2 fuzzy p-control chart and interval type-2 fuzzy np-control chart with constant sample size are developed and applied to real data. The main advantage in using interval type-2 fuzzy sets in control charts is the flexibility allowed in determining control limits for process monitoring by incorporating fuzzy set theory. Therefore, fuzzy control charts with interval type-2 fuzzy numbers afford the decision maker the opportunity to see and detect process defects.

Output Power Smoothing and Voltage Regulation of a Fixed Speed Wind Generator in the Partial Load Region Using STATCOM and a Pitch Angle Controller

The output power and terminal voltage of the fixed speed induction generator fluctuate in the partial load region where the wind speed is below the rated vale, resulting in fluctuations in the grid frequency and voltage. In this paper, a novel pitch angle control strategy has developed by introducing an exponential moving average (EMA) concept from which the controller reference power (signal) can be set for below-rated wind speeds. Therefore, the employed pitch angle controller together with static synchronous compensator (STATCOM), named the unified voltage and pitch angle controller (UVPC), addresses the objective of smoothing the output power and terminal voltage regulation of a wind generator, subjected to below-rated wind speed variations. Moreover, an interval type-2 fuzzy logic technique has incorporated in the pitch angle controller design, since it is more efficient in handling the uncertainties in membership functions and rules than its traditional fuzzy logic counterparts. Simulation results clearly show that the proposed UVPC effectively smoothens out the generator output power and also regulates the terminal voltage at its constant magnitude.

Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm

In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance by uncertainty of membership function especially when we have to confront with less expert knowledge or unpredicted external disturbances. The corresponding parameters and rule base of type-2 fuzzy logic power system stabilizer are optimally tuned by using differential evolution algorithm for multi-machine power system. Through simulation under different operational conditions, the results demonstrate the effectiveness of the proposed approach for damping the power system electromechanical oscillations.

Type-1/type-2 fuzzy logic systems optimization with RNA genetic algorithm for double inverted pendulum

This paper proposes a hybrid type-2 fuzzy logic system architecture with the aid of RNA genetic algorithm for a double inverted pendulum system. As an extension of type-1 fuzzy logic system, type-2 fuzzy logic system can effectively improve the control performance by uncertainty of membership function especially when we have to confront with corrupted data or unpredicted external disturbances. In this proposed method, the related parameters of type-1 and type-2 fuzzy logic systems are respectively optimized by using RNA genetic algorithm. Through computer simulation and comparisons, the better performance can be achieved by using optimized type-2 fuzzy logic system with RNA genetic algorithm.