Zhi Kong

The normal parameter reduction of soft sets and its algorithm

This paper is concerned with the reduction of soft sets and fuzzy soft sets. Firstly, the problems of suboptimal choice and added parameter set of soft sets are analyzed. Then, we introduce the definition of normal parameter reduction in soft sets to overcome these problems. In addition, a heuristic algorithm of normal parameter reduction is presented. Two new definitions, parameter important degree and decision partition, are proposed for analyzing the algorithm of normal parameter reduction. Furthermore, the normal parameter reduction is also investigated in fuzzy soft sets.

Application of fuzzy soft set in decision making problems based on grey theory

There are many uncertain problems in practical production and life which need decisions made with soft sets and fuzzy soft sets. However, the basis of evaluation of the decision method is single and simple, the same decision problem can obtain different results from using a different evaluation basis. In this paper, in order to obtain the right result, we discuss fuzzy soft set decision problems. A new algorithm based on grey relational analysis is presented. The evaluation bases of the new algorithm are multiple. There is more information in a decision result based on multiple evaluation bases, which is more easily accepted and logical to ones thinking. For the two cases examined, the results show that the new algorithm is efficient for solving decision problems.

An improved adaptive harmony search algorithm

This paper is concerned with the global adaptive harmony search (GAHS) algorithms for solving optimization problems. GAHS employs global information to the adaptive harmony search algorithm. The proposed GAHS algorithm is tested numerically and contrasted with improved harmony search (AHS) algorithm, and particle swarm optimization (PSO). Our simulation results reveal that GAHS is superior to AHS and PSO in terms of robustness and efficiency.

A new parameter reduction in fuzzy soft sets

The normal parameter reduction in fuzzy soft sets is an efficient method to overcome the problem of suboptimal choice and added parameter set. However, the condition of redundant parameter is so strict that the number of deleting redundant parameter in fuzzy soft sets is very few, the effect of reduction is poor. In order to deleting more redundant parameters, the proximate normal parameter reduction in fuzzy soft sets is proposed, and the method is more efficient.

Backstepping-based direct adaptive fuzzy control for SISO nonlinear systems

In this paper, adaptive fuzzy control scheme is proposed for a class of uncertain single-input and single-output (SISO) nonlinear systems with lower triangular form. The backstepping technique is applied to construct an adaptive fuzzy tracking controller which guarantees the output of system to follow the reference signal, and ensures uniform ultimate boundedness of all signals in the closed-loop system. The tracking error dynamics are proved to converge to small neighborhood of the origin. The control performance of the closed -loop system is guaranteed by properly choosing the design parameters. The proposed scheme offers systematic design procedure for the control of the uncertain nonlinear systems with lower triangular form. A main advantage of the suggested design scheme is that the adaptive mechanism with minimal learning parameterizations is obtained. To solve tracking control problems for an n - th order nonlinear system, there are at most n parameters needed to be adapted online. Finally, two simulation examples are used to demonstrate the effectiveness of the approaches presented in this paper.

Anti-swing control of overhead crane based on double fuzzy controllers

Eliminating and controlling the swing of the crane are very important for increasing the work efficiency, decreasing hazard during loading and unloading operation. By the analysis of the simulation of the two-dimensional motion of overhead crane model, this paper obtained the basic domains of the displacement and tilt angle, applied the fuzzy control principle to ensure the structure of fuzzy control, design the membership functions of the input and output variables, and build the fuzzy controllers. The result of the simulation show that the design of the fuzzy controllers have a good performance which effectively inhibits the hoisting swing and make the car arrive at its destination accurately and it also has a strong anti-interference ability.

The application research of compound control based on the fuzzy neural network inverse method

Through the study of the boiler-turbine coordination and control network, this paper analysis the difficulties of the inverse system analytical method in practical use. A structure and learning method with close to the dynamic inverse system capacity of continuous-time dynamic neural network has been raised. A coordination and control neural network inverse system control method for the thermal power plant boiler-turbine has been raised. A more complete control for coordinated neural network of boiler-turbine has been studied and the basic design approach for neural network inverse system in practical application has been given.

Sequence Intuitionistic Fuzzy Soft Sets and Its Application in Decision Making

Intuitionistic fuzzy sets think about both true membership degree and false membership degree, which makes it have stronger ability to tackle uncertain information, but it has the defect that cannot dynamically deal with membership degree of investigated subjects, so this paper introduces the concept of sequence intuitionistic fuzzy soft sets and analyses its operations. Finally, we apply sequence intuitionistic fuzzy soft sets to the multiple attribute decision making problems and illustrate it by a practical case.

An HV transmission line overhaul plan optimization method based on the color Petri net

In making the transmission line overhaul plan of electrical power system, HV transmission line overhaul plan is often used in engineering. The method is mainly depended on the experience with the low efficiency. Moreover, the operation ability is not strong in the process of implementation, which greatly threats the safe stable movement of the electrical power system. In this paper, order to overcome these problems, the HV transmission line overhaul plan model is established, furthermore, a new method is proposed to design HV transmission line overhaul plan with color Petri net theory. The feasibility of this method is proved by the final example.

The unit Coordinated Control System based on the fuzzy neural network inverse control method

According to the performance of fossil fuel-fired units, that profound coupling nonlinearity and which made the mathematical model very difficult. Inverse method control for the design of MIMO system of unit coordinated control system is suggested. the realization of the inverse system up is not adopt traditional meaning is of the obvious analyze, but adopt the dynamic neural network, the inverse system that construct to non-analytical model, combine the neural network inverse system and the linear PID control to construct closed loop system, apply in the boiler-turbine coordinated control system. Through simulation testing, this kind of new control method not only has the satisfied control performance, but also has the stronger robustness and interference resistance, improve coordinated control system of fossil fuel-fired units altering operating mode of adaptability and the control quality.