Fuzzy Universal Appraisal of Technical Condition of the Equipment

This paper introduces a new method to evaluate the technical condition of the equipment, by means of two-grade Fuzzy Universal Appraisal,we can evaluate them more accurately. At first we establish the principle factor set U={U_1,U_2,U_3,…,U_n}and each principle factor U is composed of many subfactors U_j={u_(j1),U_(j2),…,U_(jn)},Then we establish the weight distribution in U and U_j.The decision set has five grades,namely:very good,pretty good,critical,rather bad,very bad.Through the establishments of appraisal metrix U_j and U We can get the final conclusion. A real example is introduced to illustrate the process of appraisal.

Fault tolerant control of electric pitch control system based on single current detection

In view of the current sensors failure in electric pitch system,a variable universe fuzzy fault tolerant control method of electric pitch control system based on single current detection is proposed.When there is single or two-current sensor fault occurs,based on the proposed method the missing current information can be reconstructed by using direct current（DC）bus current sensor and the three-phase current can be updated in time within any two adjacent sampling periods,so as to ensure stability of the closed-loop system.And then the switchover and fault tolerant control of fault current sensor would be accomplished by fault diagnosis method based on adaptive threshold judgment.For the reconstructed signal error caused by the modulation method and the main control target of electric pitch system,a variable universe fuzzy control method is used in the speed loop,which can improve the anti-disturbance ability to load variation,and the robustness of fault tolerance system.The results show that the fault tolerant control method makes the variable pitch control system still has ideal control characteristics in case of sensor failure although part of the system performance is lost,thus the correctness of the proposed method is verified.

Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept

This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm.The pathological basal ganglia oscillations in the theta(4-9 Hz)and beta(12-35 Hz)frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson’s disease(PD).Although the clinical application of open-loop deep brain stimulation(DBS)is effective,the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses,and thus the stimulation effects go poor.To deal with this difficult problem,a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states.We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect.The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms,which may become an alternative method to administrate the symptoms in PD.

Approximation and universality of fuzzy Turing machines

Fuzzy Turing machines are the formal models of fuzzy algorithms or fuzzy computations. In this paper we give several different formulations of fuzzy Turing machine, which correspond to nondeterministic fuzzy Turing machine using max-＊ composition for some t-norm＊ （or NFTM＊, for short）, nondeterministic fuzzy Turing machine （or NFTM）, deterministic fuzzy Turing machine （or DFTM）, and multi-tape versions of fuzzy Turing machines. Some distinct results compared to those of ordinary Turing machines are obtained. First, it is shown that NFTM＊, NFTM, and DFTM are not necessarily equivalent in the power of recognizing fuzzy languages if the t-norm＊ does not satisfy finite generated condition, but are equivalent in the approximation sense. That is to say, we can approximate an NFTM＊ by some NFTM with any given accuracy; the related constructions are also presented. The level characterization of fuzzy recursively enumerable languages and fuzzy recursive languages are exploited by ordinary r.e. languages and recursive languages. Second, we show that universal fuzzy Turing machine exists in the approximated sense. There is a universal fuzzy Turing machine that can simulate any NFTM＊ on it with a given accuracy.

Variable Universe Fuzzy Control for Battery Equalization

In order to avoid the overcharge and overdischarge damages, and to improve the lifetime of the lithium-ion batteries, it is essential to keep the cell voltages in a battery pack at the same level,i.e., battery equalization. Based on the bi-directional modified Cuk converter, variable universe fuzzy controllers are proposed to adaptively maintain equalizing currents between cells of a serially connected battery pack in varying conditions. The inputs to the fuzzy controller are the voltage differences and the average voltages of adjacent cell pairs. A large voltage difference requires large equalizing current while adjacent cells both with low/high voltages can only stand small discharge/charge currents. Compared with the conventional fuzzy control method, the proposed method differs in that the universe can shrink or expand as the effects of the input changes. This is important as the input may change in a small range. Simulation results demonstrate that the proposed variable universe fuzzy control method has fast equalization speed and good adaptiveness for varying conditions.

Observer-based Variable Universe Adaptive Fuzzy Controller Without Additional Dynamic Order

A high-precision fuzzy controller, based on a state observer, is developed for a class of nonlinear single-input-single-output(SISO) systems with system uncertainties and external disturbances. The state observer is introduced to resolve the problem of the unavailability of state variables. Assisted by the observer, a variable universe fuzzy system is designed to approximate the ideal control law. Being auxiliary components, a robust control term and a state feedback control term are designed to suppress the influence of the lumped uncertainties and remove the observation error, respectively. Different from the existing results, no additional dynamic order is required for the control design. All the adaptive laws and the control law are built based on the Lyapunov synthesis approach, and the signals involved in the closed-loop system are guaranteed to be uniformly ultimately bounded. Simulation results performed on Duffing forced oscillation demonstrate the advantages of the proposed control scheme.

Development of the automatic navigation system for combine harvester based on GNSS

An automatic navigation system was developed to realize automatic driving for combine harvester,including the mechanical design,control method and software design.First of all,for the harvester modified with the automatic navigation system,a dynamic calibration method of the rear wheel center position was proposed.The control part included the navigation controller and the steering controller.A variable universe fuzzy controller was designed to the navigation controller,which used fuzzy control to change the fuzzy universe of input and output dynamically,that means,under the condition that the fuzzy rules remain unchanged,the fuzzy universe changes with the change of input,which is an adaptive fuzzy control method and can modify the control strategy in time.To realize the automatic navigation of the harvester,the decision result of the navigation controller based on the variable universe fuzzy control was input into the steering controller,and then the electric steering wheel was controlled to rotate.To test the performance of the designed automatic navigation system,the field experiment was carried out.When the combine harvester was navigating linearly at a speed of 0.8 m/s,the overall root mean square error(RMSE)of the lateral deviation was 5.87 cm.The test results showed that the system was designed could make the combine track the preset path smoothly and stably,and the tracking accuracy was at the centimeter level.

Variable universe fuzzy control of walking stability for flying‐walking power line inspection robot based on multi‐work conditions

To address complex work conditions incredibly challenging to the stability of power line inspection robots,we design a walking mechanism and propose a variable universe fuzzy control(VUFC)method based on multi‐work conditions for flying‐walking power line inspection robots(FPLIRs).The contributions of this paper are as follows:(1)A flexible pressing component is designed to improve the adaptability of the FPLIR to the ground line slope.(2)The influence of multi‐work conditions on the FPLIR's walking stability is quantified using three condition parameters(i.e.,slope,slipping degree and swing angle),and their measurement methods are proposed.(3)The VUFC method based on the condition parameters is proposed to improve the walking stability of the FPLIR.Finally,the effect of the VUFC method on walking stability of the FPLIR is teste.The experimental results show that the maximum climbing angle of the FPLIR reaches 29.1°.Compared with the constant pressing force of 30 N,the average value of slipping degree is 0.93°,increasing by 35%.The maximum and average values of robot's swing angle are reduced by 46%and 54%,respectively.By comparing with fuzzy control,the VUFC can provide a more reasonable pressing force while maintaining the walking stability of the FPLIR.The proposed walking mechanism and the VUFC method significantly improve the stability of the FPLIR,providing a reference for structural designs and stability controls of inspection robots.