模糊控制器中的智能积分

分析了传统模糊控制稳态精度差的缺陷，引入了智能积分以减少稳态误差和避免积分饱和，采用△ｕ＝ｆ（ｅ，ｅｃ）＋Ｅｄｔ（当Ｅ·ｃ＞０或ｃ＝０而Ｅ≠０）及△ｕ＝ｆ（ｅ，ｅｃ）（当Ｅ·ｃ＜０或Ｅ＝０）（其中ｅ为系统误差，ｃ为系统误差变化，ｆ（ｅ，ｅｃ）为模糊控制器输邮，ＫＫＥｄｔ为智能积分输出，△ｕ。为模糊控制器总输出）。然后设计了一个自组织模糊逻辑控制器以实现快速响应和小的超调，在金属镁还原炉上运行后获得较理想的效果。

基于模糊控制下的汽车ABS系统研究

基于汽车ABS系统的工作原理和模糊控制理论,应用模糊控制理论研究汽车ABS系统,同时,设计模糊控制逻辑规则。

改进模糊PID参数的电动汽车动力控制系统研究

在传统PID控制策略的基础上,引入逻辑模糊控制思想,通过逻辑模糊法则对PID控制参数KP、KI和KD进行优化.仿真结果表明,采用优化的PID控制参数,可以使电动汽车具有良好的起动加速性能、运行性能、爬坡性能以及车速突变控制性能.

螺杆式冷水机组滑阀无级调节控制探讨

针对冷水机组的能量调节,介绍了螺杆式冷水机组采用滑阀调节的原理,并就如何实现滑阀的无级调节提出了一种可行的做法。

“权数分配”在综合评判中的应用

综合评判在决策和预测中广泛应用，用解析函数和模糊控制逻辑方法确定变权是可取的，变权的应用为综合评判提供了一个较好的途径，并使其综合评判的结果令人满意。

Study of Controlling Clutch Engagement for AMT Based on Fuzzy Logic

The control of the clutch engagement for an automatic mechanical transmission in the process of a tracklayer getting to start is studied. The dynamic model of power transmission and automatic clutch system is developed. Using tools of Simulink, the transient characteristics during the vehicle starting, including the jerk and the clutch slip time, are provided here. Based on the analyses of the simulation results and driver’s experiences, a fuzzy controller is designed to control the clutch engagement. Simulation results verify its value.

Performance analysis of air suspension system of heavy truck with semi-active fuzzy control

In order to analyze and evaluate the performance of the air suspension system of heavy trucks with semi-active fuzzy control, a three-dimensional nonlinear dynamical model of a typical heavy truck with 16-DOF（degree of freedom） is established based on Matlab/Simulink software. The weighted root-mean-square（RMS） acceleration responses of the vertical driver ＇s seat, the pitch and roll angle of the cab, and the dynamic load coefficient（DLC） are chosen as objective functions, and the air suspension system is optimized and analyzed by the semi-active fuzzy control algorithm when vehicles operate under different operation conditions. The results show that the influence of the roll angle of the cab on the heavy truck ride comfort is clear when vehicles move on the road surface conditions of the ISO level D and ISO level E at a velocity over 27.5 m/s. The weighted RMS acceleration responses of vertical driver＇ s seat, the pitch and roll angle of the cab are decreased by 24%, 30% and 25%, respectively,when vehicles move on the road surface condition of the ISO level B at a velocity of 20 m/s. The value of the DLC also significantly decreases when vehicles operate under different operation conditions. Particularly, the DLC value of the tractor driver axle is greatly reduced by 27.4% when the vehicle operates under a vehicle fully-loaded condition on the road surface condition of ISO level B at a velocity of 27.5 m/s.

NOVEL DESIGN OF ENERGY CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE

A novel design method of control strategy for a parallel hybrid electric vehicle is proposed. The sequential quadratic programming（SQP） is first used to solve the optimal problem of maximizing system efficiency in terms of the global optimization. And then a fuzzy logic controller is developed to implement the optimal control strategy for a tradeoff between the engine and the battery in local. In addition, the performance of the fuzzy system is improved by optimizing the fuzzy rules based on the SQP results. Simulation results show that the proposed control strategy achieves better fuel economy under the duty cycle.

A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS

Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.

Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

Design of an optimal active stabilizer mechanism for enhancing vehicle rolling resistance

Improving rollover and stability of the vehicles is the indispensable part of automotive research to prevent vehicle rollover and crashes.The main objective of this work is to develop active control mechanism based on fuzzy logic controller(FLC) and linear quadratic regulator(LQR) for improving vehicle path following,roll and handling performances simultaneously.3-DOF vehicle model including yaw rate,lateral velocity(lateral dynamic) and roll angle(roll dynamic) were developed.The controller produces optimal moment to increase stability and roll margin of vehicle by receiving the steering angle as an input and vehicle variables as a feedback signal.The effectiveness of proposed controller and vehicle model were evaluated during fishhook and single lane-change maneuvers.Simulation results demonstrate that in both cases(FLC and LQR controllers) by reducing roll angle,lateral acceleration and side slip angles remain under 0.6g and 4° during maneuver,which ensures vehicle stability and handling properties.Finally,the sensitivity and robustness analysis of developed controller for varying longitudinal speeds were investigated.

SERVICE-AWARE BASED FUZZY ADMISSION CONTROL SCHEME IN MULTI-SERVICE NETWORKS

Multi-service aggregated transmission is the direction of IP network. Providing different Quality of Service (QoS) assurance for different services has become a crucial problem in future network. Admission control is a vital function for multi-service IP network. This paper proposes a novel fuzzy admission control scheme based on coarse granularity service-aware technique. Different service has discriminative sensitivity to the same QoS characteristic parameter in general. The traffic class can be perceived by the service request parameter and the proposed QoS function. And requirements of dif- ferent applications can be met by maintaining the life parameter. From simulation results, the proposed scheme shows a better QoS provisioning than those traditional fuzzy logic based methods under the same admission probability.

Adaptive control using interval Type-2 fuzzy logic for uncertain nonlinear systems

A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.

Reactive fuzzy controller design by Q-learning for mobile robot navigation

In this paper a learning mechanism for reactive fuzzy controller design of a mobile robot navigating in unknown environments is proposed. The fuzzy logical controller is constructed based on the kinematics model of a real robot. The approach to learning the fuzzy rule base by relatively simple and less computational Q-learning is described in detail. After analyzing the credit assignment problem caused by the rules collision, a remedy is presented. Furthermore, time-varying parameters are used to increase the learning speed. Simulation results prove the mechanism can learn fuzzy navigation rules successfully only using scalar reinforcement signal and the rule base learned is proved to be correct and feasible on real robot platforms.

Development of single-chip fuzzy controller based on FFSI in binary

Length and concise structure of fuzzy logic reasoning program and its real-time reasoning characteris-tic have their effect on the performance of a digital single-chip fuzzy controller. The control effect of a digitalfuzzy controller based on looking up fuzzy control responding table is only relative to the table and not relative tothe fuzzy control rules in the practical control process. Aiming at above problem and having combined fuzzy log-ic reasoning with digital operational characteristics of a single-chip microcomputer, functioning-fuzzy-subset in-ference (FFSI) in binary, in which triangle membership functions of error and error-in-change are all represen-ted in binary and singleton membership functions of control variable is binary too, has been introduced. The cir-cuit principle plans of a single-chip fuzzy controller have been introduced for development of its hardware, andthe primary program structure, fuzzy logic reasoning subroutine, serial communication subroutine with PC andreliability design of the fuzzy controller are all discussed in detail. The control of indoor temperature by a fuzzycontroller has been conducted using a testing-room thermodynamic system. Research results show that the FFSIin binary can exercise a concise fuzzy control in a single-chip fuzzy controller, and the fuzzy controller is there-fore reliable and possesses a high performance-price ratio.

Torque Distribution Strategy for Integrated Starter/ Generator Hybrid Bus Implemented by Fuzzy Algorithm

A torque distribution strategy was designed by using fuzzy logic to realize the optimal control. The vehicle load zones were dynamically divided into several zones by several torque lines to indicate the drivers demand and the high or low efficient operating areas of the diesel engine. The fuzzy logic controller with trapezoid membership function and Mamdani rule reference mechanism was utilized. There are over 100 rules used in this fuzzy-based torque distribution strategy which are sorted into four rule-bases. The fuel economy and acceleration tests were designed to test and validate the integrated starter/generator (ISG) bus perfor-mance using fuzzy-based torque distribution strategy. The fuel economy is improved 7.7% compared with the rule-based strategy. Finally the road test results reveal that there is about 15% improvement of fuel economy. And the 0-50 km/h acceleration time is 9.5% shorter than the original bus.

AN INTELLIGENT METHOD FOR REAL-TIME DETECTION OF DDOS ATTACK BASED ON FUZZY LOGIC

The paper puts forward a variance-time plots method based on slide-window mechanism tocalculate the Hurst parameter to detect Distribute Denial of Service(DDoS)attack in real time.Basedon fuzzy logic technology that can adjust itself dynamically under the fuzzy rules,an intelligent DDoSjudgment mechanism is designed.This new method calculates the Hurst parameter quickly and detectsDDoS attack in real time.Through comparing the detecting technologies based on statistics andfeature-packet respectively under different experiments,it is found that the new method can identifythe change of the Hurst parameter resulting from DDoS attack traffic with different intensities,andintelligently judge DDoS attack self-adaptively in real time.

Virtual Reality Simulation of Fuzzy-logic Control during Underwater Dynamic Positioning

In this paper, graphical-user-interface （GUI） software for simulation and fuzzy-logic control of a remotely operated vehicle （ROV） using MATLABTM GUI Designing Environment is proposed. The proposed ROV＇s GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative （PID） and sliding-mode controller （SMC） systematically and interactively. External disturbance such as sea current can he added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.

Fuzzy logic controller design with unevenly-distributed membership function for high performance chamber cooling system

Fuzzy logic controller adopting unevenly-distributed membership function was presented with the purpose of enhancing performance of the temperature control precision and robustness for the chamber cooling system.Histogram equalization and noise detection were performed to modify the evenly-distributed membership functions of error and error change rate into unevenly-distributed membership functions.Then,the experimental results with evenly and unevenly distributed membership functions were compared under the same outside environment conditions.The experimental results show that the steady-state error is reduced around 40% and the noise disturbance is rejected successfully even though noise range is 60% of the control precision range.The control precision is improved by reducing the steady-state error and the robustness is enhanced by rejecting noise disturbance through the fuzzy logic controller with unevenly-distributed membership function.Moreover,the system energy efficiency and lifetime of electronic expansion valve(EEV) installed in chamber cooling system are improved by adopting the unevenly-distributed membership function.

Traffic Signals Control with Adaptive Fuzzy Controller in Urban Road Network

An adaptive fuzzy logic controller (AFC) is presented for the signal control of the urban traffic network. The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level. The control level decides the signal timings in an intersection with a fuzzy logic controller. The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one. Consequently the system performances are improved. A weight coefficient controller (WCC) is also developed to describe the interactions of traffic flow among the adjacent intersections. So the AFC combined with the WCC can be applied in a road network for signal timings. Simulations of the AFC on a real traffic scenario have been conducted. Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.