New Asymmetric Fuzzy PID Control for Pneumatic Position Control System

A fuzzy control algorithm of asymmetric fuzzy strategy is introduced for a servo-pneumatic position system. It can effectively solve the difficult problems of single rod low friction cylinders, which are mainly caused by asymmetric structures and different friction characteristics in two directions. On the basis of this algorithm, a traditional PID control is used to improve dynamic performance. Furthermore, a new asymmetric fuzzy PID control with α factor is advanced to improve the self-adaptability and robustness of the system. Both the theoretical analyses and experimental results prove that, with this control strategy, the dynamic performance of the system can be greatly improved. The system using this control algorithm has strong robustness and it obtains desired overshoot and repeatability in both transient and steady-state responses.

Slow driving control of tracked vehicles with automated mechanical transmission based on fuzzy logic

In order to move tracked vehicles at an extremely slowspeed with automated mechanical transmission（ AMT）,slowdriving function was added in the original system. The principle and requirement of slowdriving function were analyzed. Based on analysis of slow driving characteristic,identification of slowdriving condition and fuzzy control algorithm,a control strategy of the clutch was designed. In order to realize slowdriving,the clutch was controlled in a slipping mode as manual driving. The vehicle speed was increased to a required speed and kept in a small range by engaging or disengaging the clutch to the approximate half engagement point. Based on the control strategy,a control software was designed and tested on a tracked vehicle with AMT. The test results showthat the control of the clutch with the slowdriving function was smoother than that with original systemand the vehicle speed was slower and steadier.

Cost-Based Research on Energy Management Strategy of Electric Vehicles Using Hybird Energy Storage System

This paper uses the minimization and weighted sum of battery capacity loss and energy consumption under driving cycles as objective functions to improve the economy of Electric Vehicles(EVs)with an hybrid energy storage system composed of power batteries and ultracapacitors.Furthermore,Dynamic Programming(DP)is employed to determine the objective function values under different weight coefficients,the comprehensive cost consisting of battery aging and power consumption costs,and the relationship between the hybrid power distribution.We also evaluate the real-time fuzzy Energy Management Strategy(EMS),fuzzy control strategies,and a strategy based on DP using the World Light vehicle Test Procedure(WLTP)driving cycle and a synthesis driving cycle derived from New European Driving Cycle(NEDC),WLTP,and Urban Dynamometer Driving Schedule(UDDS)as examples.Then,the proposed strategy is compared with the fuzzy control strategy and the strategy based on DP.Compared with fuzzy energy management strategy(namely FZY-EMS),the proposed EMS reduces the battery capacity loss and system energy consumption.The results demonstrate the effectiveness of the proposed EMS in improving EV economy.

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations.Researchers have used Light Detection and Ranging(LiDAR)data for extracting the building damage maps.For producing building damage maps from LiDAR data in a rapid manner,it is necessary to understand the effectiveness of features and classifiers.However,there is no comprehensive study on the performance of features and classifiers in identifying damaged areas.In this study,the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated.In the proposed method,at first,a pre-processing stage was utilized to apply essential processes on post-event LiDAR data.Second,textural features were extracted from the pre-processed LiDAR data.Third,fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents.The proposed method was tested across three areas over the 2010 Haiti earthquake.Three building damage maps with overall accuracies of 75.0%,78.1%and 61.4%were achieved.Based on outcomes,the fuzzy inference systems were stronger than random forest,bagging,boosting and support vector machine classifiers for detecting damaged buildings.

Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm

Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em-