Vibration damping of a flexible car body structure using piezo-stack actuators

Active vibration damping of a railway car body is accomplished by actuator forces acting directly on the flexible car body structure. In this work piezo-stack actuators mounted in consoles are utilized to introduce bending moments into the flexible structure, thus achieving a significant increase in ride comfort. For a heavy metro vehicle the complete design of the active vibration damping system is presented. Analytic modeling, system identification, and robust controller design are presented. The excellent performance of the proposed method is documented by both extensive experimental results and co-simulation studies.     

基于MC9S08GB60的汽车电控悬架控制系统设计

对空气悬架的控制是提高车辆行驶平顺性的有效方法。以MC9S08GB60为控制芯片,以YBL6891H型客车的1/4车辆模型为研究对象,设计了一种客车用空气悬架的电子控制单元。该控制单元通过调整空气弹簧的刚度,降低车身垂直加速度,并采用模糊PID控制算法,提高控制精度。试验表明:该电子控制单元能有效降低车身垂直加速度,在改善车辆行驶平顺性的同时,提高了操纵稳定性。     

基于车体横移振动的高速列车虚拟复合阻尼天棚控制算法研究

高速列车车体横向随机振动由车体的横移振动、侧滚振动和摇头振动三自由度合成,是影响车体横向运行平稳性的关键;为了改善列车横向运行平稳性,提高半主动控制性能;通过建立某型高速列车动力学模型,对车体横向振动特性进行分析,得出横移振动的加剧是造成车体合成横向振动和横向平稳性恶化的主要原因;通过分析在传统天棚阻尼控制算法下分别以车体合成横向振动为反馈和以横移振动为反馈对车体横向振动的控制效果,得出采用以车体横移振动为反馈的传统天棚阻尼控制算法对车体横向振动的抑制效果更佳;在此基础上,提出一种以车体横移振动为反馈的虚拟复合阻尼天棚控制算法,并进行联合仿真分析;结果表明:相比于被动控制,采用虚拟复合阻尼天棚控制算法后,车体合成横向振动加速度峰值、均方根值和平稳性改善率分别达到了46%、43%和19.5%,均高于采用传统天棚阻尼控制算法;可见,采用虚拟复合阻尼天棚控制算法在抑制车体合成横向振动,改善车体横向平稳性方面控制性能更佳。     

Estimation of railway vehicle suspension parameters for condition monitoring

This paper investigates the problem of parameter estimation for railway vehicle suspensions so as to provide information to support condition-based (instead of calendar-based) maintenance. A simplified plan view railway vehicle dynamical model is derived and a newly developed Rao–Blackwellized particle filter (RBPF) based method is used for parameter estimation. Computer simulations are carried out to assess and compare the performance of parameter estimation with different sensor configurations as well as the robustness with respect to the uncertainty in the statistics of the random track inputs. The method is then verified practically using real test data from a Coradia Class 175 railway vehicle with only bogie and body mounted sensors, and some preliminary results are presented.     

汽车振动的一种模糊自适应控制

该文研究了一种汽车模糊自适应控制方法,并借助于一个二自由度的汽车动力学模型,探讨了该模糊自适应控制技术在汽车车身主动减振方面的控制问题。在测得汽车垂直振动强度,行驶速度等条件下,在保持各个状态变量和控制量的模糊集数量不变的情况下,通过自动调整模糊集的相应大小与相应中央位置,仿真研究表明,该自适应模糊控制器使汽车在不同路面波度大小,行驶速度等情况下的车身振动强度均能大幅度下降,达到主动减振的目的。其原理与方法可用于研制简单可靠的模糊控制主动悬架。     

Fuzzy logic and slip controller of clutch and vibration for hybrid vehicle

This paper is the second part of the paper titled “Simulation and Control of Hybrid Electric Vehicles” published in IJCAS, Vol. 10(2)/2012 where the model predictive control has been built to handle the clutch engagement between the combustion engine and the electrical motor. In this research, a fuzzy logic and slip controller of clutch and vibration of the hybrid vehicle have been considered and tested as a second control strategy. The use of the fuzzy logic control can avoid the need of the complex and rigorous mathematical modeling since the fuzzy logic can work very successfully on the uncertain and imprecise information. The clutch slip controller is implemented in an experimental test vehicle for the critical vibration reduction.     

基于自适应遗传算法的半主动悬架模糊控制研究

模糊规则的正确选择是半主动悬架模糊控制器设计的关键和难点,本文提出一种自适应地选择交叉概率和变异概率的遗传算法,以车身垂直加速度均方根值为优化目标,对汽车半主动悬架模糊控制规则进行优化,以达到提高半主动悬架模糊控制器的控制效果,改善汽车行驶平顺性的目的。为了证明该优化方法的可行性,将该自适应遗传算法优化的模糊控制器对汽车半主动悬架进行控制,并建立Matlab文本与Simulink相结合的仿真模型。仿真结果表明：优化后的半主动悬架车身垂直加速度均方根值减小,汽车行驶的平顺性得到了提高。     

Experimental Comparison Research on Active Vibration Control for Flexible Piezoelectric Manipulator Using Fuzzy Controller

Space manipulators are flexible structures. Vibration problem will be unavoidable due to motion or external disturbance excitation. Model based control methods will not maintain the required accuracy because of the existence of nonlinear factors and parameter uncertainties. To solve these problems, fuzzy logic control laws with different membership function groups are adopted to suppress vibrations of a flexible smart manipulator using collocated piezoelectric sensor/actuator pair. Also, dual-mode controllers combining fuzzy logic and proportional integral control are designed, for suppressing the lower amplitude vibration near the equilibrium point significantly. Experimental comparison research is conducted, using fuzzy control algorithms and the dual-mode controllers with different membership functions. The experimental results show that the adopted fuzzy control algorithms can substantially suppress the larger amplitude vibration; and the dual-mode controllers can also damp out the lower amplitude vibration significantly. The experimental results demonstrate that the proposed fuzzy controllers and dual-mode controllers can suppress vibration effectively, and the optimal placement is feasible.     

Expert system based controller for the high-accuracy automatic assembly of vehicle headlamps

A vehicle headlamp is a high-sophisticated device basically composed of three elements: housing, lighting system and lens. Nowadays, they are assembled with no dimensional control, obtaining a final product with high physical deviations. Since the car manufacturer is requiring more and more precision, the number of faulty headlamps is increasing, and thus the cost to the headlamp producer. To solve this problem, a new automatic assembly machine was built. It integrated different technologies such as sensor systems, linear actuators and computational capacities.This work presents the conception, design and development of a fuzzy control algorithm for an automatic machine capable of correcting the dimensional tolerances of vehicle headlamps during its assembly process. Particularly, this paper describes the problem of modeling and control an industrial system, with a high complex dynamics and unknown model, by a rule-based model constructed from measured data.To validate the proposed control system, different experimental tests were carried out in both the lab and the assembly line in the factory. The obtained results show how the prototype, together with the proposed fuzzy software, solve the problem of assembling vehicle headlamps obtaining a final product with minimum dimensional errors.     

信号交叉口模糊逻辑自适应控制

针对城市道路交叉口的智能交通信号控制,提出了一种主从式模糊逻辑自适应控制算法,该算法综合考虑了本相位最小绿灯时间结束时刻的路段车辆数和相邻相位的车辆排队长度,以及本相位非关键车流对关键车流的影响,采用两个规则前件进行主模糊控制器的模糊推理,设计了具有更多控制信息的两级模糊控制器。结合已有类似研究成果进行了仿真比较研究,结果表明:该控制算法在减少车辆延误方面有明显改进。     

Design optimization of fuzzy controllers in building structures using the crystal structure algorithm (CryStAl)

The current study uses a recently-developed metaheuristic method called Crystal Structure Algorithm (CryStAl) to achieve optimized vibration control in structural engineering. More specifically, this algorithm, which is inspired by the well-established crystallographic principles underlying the formation of crystalline solids in nature, is applied to the optimization of fuzzy logic controllers in building structures. To demonstrate the capability of this method in solving real engineering problems, two real-size building structures, one with three and the other with twenty stories, are considered. The fuzzy controllers are implemented through an active control system to control the seismically-induced vibrations of the structures intelligently. The evaluation criteria utilized to assess the overall performance of the optimization method applied to the fuzzy control system are presented and discussed. Through nonlinear structural analyses, the ductility, energy dissipation, and other nonlinear characteristics of the structures are also considered as the structural responses to be controlled. The computational results obtained from this novel metaheuristic algorithm are compared with those of the other expert systems from the optimization literature. The findings of this paper demonstrate that the Crystal Structure Algorithm is capable of outranking the other methods in the majority of considered cases.     

Fuzzy Logic Based Approach to Design of Flight Control and Navigation Tasks for Autonomous Unmanned Aerial Vehicles

This paper proposes a fuzzy logic based autonomous navigation controller for UAVs (unmanned aerial vehicles). Three fuzzy logic modules are developed under the main navigation system for the control of the altitude, the speed, and the heading, through which the global position (latitude–longitude) of the air vehicle is controlled. A SID (Standard Instrument Departure) and TACAN (Tactical Air Navigation) approach is used and the performance of the fuzzy based controllers is evaluated with time based diagrams under MATLAB’s standard configuration and the Aerosim Aeronautical Simulation Block Set which provides a complete set of tools for rapid development of detailed six-degree-of-freedom nonlinear generic manned/unmanned aerial vehicle models. The Aerosonde UAV model is used in the simulations in order to demonstrate the performance and the potential of the controllers. Additionally, FlightGear Flight Simulator and GMS aircraft instruments are deployed in order to get visual outputs that aid the designer in the evaluation of the controllers. Despite the simple design procedure, the simulated test flights indicate the capability of the approach in achieving the desired performance.     

Fuzzy force learning controller of flexible wiper system

Wiper blade of automobile is among those types of flexible system that is required to be operated in quite high velocity to be efficient in high load conditions. This causes some annoying noise and deteriorated vision for occupants. The modeling and control of vibration and low-frequency noise of an automobile wiper blade using soft computing techniques are focused in this study. The flexible vibration and noise model of wiper system are estimated using artificial intelligence system identification approach. A PD-type fuzzy logic controller and a PI-type fuzzy logic controller are combined in cascade with active force control (AFC)-based iterative learning (IL). A multi-objective genetic algorithm is also used to determine the scaling factors of the inputs and outputs of the PID-FLC as well as AFC-based IL gains. The results from the proposed controller namely fuzzy force learning (FFL) are compared with those of a conventional lead–lag-type controller and the wiper bang–bang input. Designing controllers based on classical methods could become tedious, especially for systems with high-order model. In contrast, FFL controller design requires only tuning of some scaling factors in the control loop and hence is much simpler and efficient than classical design methods.     

上海A型地铁车辆弹性车体与转向架耦合振动分析

基于上海A型地铁车辆弹性车体有限元模型,建立弹性车体的刚柔耦合动力学模型,用其研究车体垂向弹性对运行平稳性的影响,分析弹性车体与转向架的耦合振动,探究车体弹性共振的机理.结果表明,在车体刚度低的情况下,该型地铁车辆车体弹性对车辆运行平稳性影响较大;车体的弹性共振并非由车体与转向架耦合振动引起,在车辆悬挂及车体的设计过程中应当考虑几何滤波现象引发车体弹性共振对车辆平稳性的影响。     

野草入侵模糊算法的半主动空气悬架研究

为了抑制由路面不平引起的车辆振动,结合磁流变阻尼器和空气弹簧的变阻尼/刚度特性,设计了含内置永磁体式磁流变阻尼器的半主动空气悬架系统.基于电磁学原理,对内置永磁体式磁流变阻尼器的力学特性建模.建立了1/4车辆二自由度动力学模型,并利用野草入侵算法对常规模糊算法规则进行优化,开发了野草入侵-模糊混合控制策略对内置永磁体磁流变阻尼器的空气悬架进行半主动控制.为验证该控制策略在磁流变空气悬架的半主动控制效果,进行了C级路面随机输入及凸块脉冲输入仿真分析,仿真结果可知,野草入侵-模糊控制策略能有效地提高半主动悬架系统的综合性能.并且通过台架试验进一步表明,利用该控制策略能够使车身振动加速度及悬架动挠度分别减小25.87%、35.13%.     

An effective hybrid approach of desirability,fuzzy logic,ANFIS and LAPO algorithm for optimizing compliant mechanism

This paper proposes an efficient hybrid approach for solving multi-objective optimization design of a compliant mechanism. The approach is developed by integrating desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system, and Lightning attachment procedure optimization. Box–Behnken design is used to form a numerically experimental matrix. First, a refinement of design variables is conducted through analysis of variance and Taguchi approach in terms of considerably eliminating space of design variables and computation efforts. Next, desirability of two objective functions is computed and transferred into the fuzzy logic system. The output of fuzzy logic system is regarded as single combined objective function. Subsequently, a modeling for fuzzy output is developed via adaptive neuro-fuzzy inference system. Then, LAPO algorithm is adopted for solving the optimization problem. By investigating three different numerical examples, performance of the proposed approach is validated. Numerical results revealed that the proposed approach has a computational accuracy better than that of Taguchi-based fuzzy logic reasoning. Finally, case study 1 is chosen as an optimal solution for the mechanism. Furthermore, the effectiveness of proposed approach is greater than that of the Jaya algorithm and TLBO algorithm through Wilcoxon signed rank test and Friedman test. The proposed approach can be used for related engineering fields.

     

基于MSC Adams/View的动力总成悬置系统匹配设计

运用MSC Adams/View建立某轿车整车多体动力学模型,对动力总成悬置系统进行匹配设计,以满足频率合理分布、模态振型解耦、限位等诸多设计要求. 在建模过程中,通过定义高阶传递函数实现对悬置的动刚度和损失角特性的模拟;在仿真过程中,通过刚体模态分析、动力总成质心位移和转角计算以及典型工况的仿真,成功地预测了悬置系统的性能,为进一步优化指明方向.     

Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase

The intelligent autonomous control of hypersonic vehicles has aroused great interest from the field of spacecraft. To solve the problem of longitudinal attitude control of hypersonic vehicle in gliding phase, a new intelligent controller is proposed in this paper. This new controller is based on the fuzzy dynamic characteristic modeling method. The fuzzy logic is introduced into the characteristic modeling by dividing the whole restriction range into several subspaces. Simulations show that this modificatio...     

A self-learning fuzzy logic controller using genetic algorithmswith reinforcements

This paper presents a new method for learning a fuzzy logic controller automatically. A reinforcement learning technique is applied to a multilayer neural network model of a fuzzy logic controller. The proposed self-learning fuzzy logic control that uses the genetic algorithm through reinforcement learning architecture, called a genetic reinforcement fuzzy logic controller, can also learn fuzzy logic control rules even when only weak information such as a binary target of “success” or “failure” signal is available. In this paper, the adaptive heuristic critic algorithm of Barto et al. (1987) is extended to include a priori control knowledge of human operators. It is shown that the system can solve more concretely a fairly difficult control learning problem. Also demonstrated is the feasibility of the method when applied to a cart-pole balancing problem via digital simulations     

Sliding mode control of wind-induced vibrations using fuzzy sliding surface and gain adaptation

Although fuzzy/adaptive sliding mode control can reduce the chattering problem in structural vibration control applications, they require the equivalent control and the upper bounds of the system uncertainties. In this paper, we used fuzzy logic to approximate the standard sliding surface and designed a dead-zone adaptive law for tuning the switching gain of the sliding mode control. The stability of the proposed controller is established using Lyapunov stability theory. A six-storey building prototype equipped with an active mass damper has been used to demonstrate the effectiveness of the proposed controller towards the wind-induced vibrations.