基于遗传算法的芦苇笋采收机模糊PID控制策略研究

芦苇笋采收机在工作时需人工实时操纵输出电压来适应负载力矩的变化,为提高采收效率和降低操作难度,提出了一种基于遗传算法的模糊控制PID算法以实现芦苇笋采摘装置同步带转速的智能控制。通过分析芦苇笋采摘装置的工作原理,建立了控制电压和负载力矩输入和液压马达输出轴角速度输出的状态方程数学模型;利用MATLAB/Simulink软件设计通过遗传算法优化隶属度函数和模糊规则的Mamdani模糊PID控制器,对液压马达的状态方程进行仿真。结果表明：采用遗传算法优化的模糊PID控制器相较于普通PID控制器和模糊控制器能够对输入信号更迅速地做出响应,且上升过程平稳无超调,有较强的抗干扰能力,鲁棒性较强,满足对芦苇笋采收机工作过程的简化操作和提高效率的控制要求。     

模糊自整定PID的液压马达驱动机床主轴速度控制研究

液压马达驱动机床主轴系统具有参数时变和高度非线性,传统PID控制器控制精度不高。针对液压马达驱动机床主轴系统速度控制问题,采用模糊自整定PID控制器实现液压马达驱动机床主轴系统的有效控制,并对控制效果进行仿真验证。构造了液压马达驱动机床主轴系统模型简图,建立了液压马达驱动机床主轴系统数学模型。对传统PID控制器参数,用模糊控制器进行实时整定,开发了模糊自整定PID控制器。最后,采用MATLAB对液压马达驱动机床主轴系统进行仿真。同时,与传统PID控制器的计算结果进行对比和分析。仿真结果显示：采用模糊自整定PID控制器的液压马达驱动机床主轴转速超调量小,具有更快的响应时间,跟踪精度高,同时系统能耗减少20%左右;即使受到较大随机干扰,模糊自整定PID控制器也能快速消除干扰,使机床主轴转速处于受控状态。采用模糊自整定PID控制器可以有效提高液压马达驱动机床主轴系统的动态稳定性以及抗干扰能力。     

基于自适应鲁棒的电液伺服转台双马达同步控制

转台是航空航天半实物仿真系统的重要装备,双马达驱动的电液伺服转台具有速度高、加速度大、频响快等优点。针对转台外框双马达的同步问题,建立了转台的动力学模型。该模型考虑了外框的机械耦合、中框旋转造成的惯量扰动等因素对马达输出的影响。基于该模型提出了变惯量自适应鲁棒同步控制(Adaptive Robust Synchronous Control with Inertia Disturbance,ARSCI)方法,有效提高了双马达的跟踪精度和同步性能。通过Lyapunov方法证明,只要选择合适控制器参数,就能保证所有的系统状态有界。最后通过仿真研究,证明了该方法的有效性。     

阀控液压马达动态特性控制的仿真研究

文章针对阀控液压马达动态特性进行研究,建立液压阀流量方程、液压马达流量连续性方程和液压马达与负载的力矩平衡方程,推导出阀控液压马达的传递函数。运用MATLAB软件的SIMULINK模块对阀控液压马达系统进行动态特性仿真分析。仿真结果表明,在不同负载作用的情况下,系统中加入PID控制和未加PID控制比较,系统的调整幅度和调整时间均减小,PID控制器能够提高系统的抗负载扰动性能。     

液压仿真转台中框等同式同步控制系统的研究

该文针对基于等同方式的同步控制系统的特点，设计液压三轴仿真转台的中框双液压马达同步驱动系统，为保证转台中框的性能，对两同步通道分别进行设计，使其具有良好的并尽量一致的静、动态特性。实验表明，采用的设计方式具有较高的同步精度，对仿真转台中框的同步驱动系统来说是完全有效的。     

电液比例阀控液压马达系统的模糊PID恒速控制

针对电液比例阀控液压马达系统,分别采用常规PID控制策略和参数自整定的模糊PID控制策略来实现液压马达的恒速控制。通过分析阀控液压马达系统的工作原理和调速原理,设计出模糊PID控制器。运用Simulink仿真工具来建立阀控液压马达系统的仿真模型,并在外加负载转矩的作用下对该仿真模型进行仿真。仿真结束后对比常规PID控制策略和模糊PID控制策略下的仿真结果,得出在模糊PID控制策略下液压马达输出转速峰值时间、调整时间、超调量和在外界突加相同负载转矩下液压马达转速调整的时间都优于常规PID控制策略。     

变转速液压调速系统转速模糊控制实验研究

针对变转速液压调速系统存在非线性、时变及调速精度低等技术问题,提出液压马达转速模糊控制策略。以伺服电动机驱动定量泵为动力源,设计了模糊控制器,实现了基于Lab VIEW测控平台的以电动机转速为控制量的马达转速模糊控制策略。在典型工况下,对模糊控制和传统PID控制调速系统的动态响应性能及抗负载干扰能力进行了实验对比分析,结果表明:所提方法比传统PID模糊控制具有更好的鲁棒性,且两种控制方式的动态响应特性相近。     

一种泵、马达双用火炮随动系统负载仿真策略研究

基于目前双联液压马达/泵的工作方式提出一种新型的泵、马达双用工作方式,以模拟火炮随动系统在实际不同运行过程中的各种负载情况。建立了泵、马达工作状态的数学模型,研究了基于干扰观测器和非线性PID控制器的电液模拟加载控制方法,有效地抑制了干扰力矩,提高了系统的跟踪性能。仿真结果表明:泵、马达双用控制策略能够有效地模拟各种力矩,且在观测器补偿与PID控制器并用控制时能够取得较好的载荷谱跟踪性能。     

液压转台动态摩擦的自适应鲁棒补偿研究

复杂的动态非线性摩擦力矩是影响液压转台低速性能的关键因素.为提高液压转台的低速性能,通过分析液压转台单框动态摩擦力矩特性,建立转台摩擦的LuGre模型基础上,提出用一种自适应鲁棒控制补偿液压转台动态摩擦.构造两个非线性观测器对液压转台LuGre摩擦状态进行精确估计,不连续投影映射方法提高参数自适应和摩擦状态估计的稳定性,鲁棒反馈项削弱估计误差和未确定非线性以确保控制系统的鲁棒性能.对液压转台外框的试验结果证明了该方法的正确性和优越性.     

机舱罩装配平台双液压缸同步控制策略

为了提高风力发电机机舱罩装配平台双液压缸同步控制系统的同步精度,分析了阀控缸位置控制的数学模型,并设计了一种基于模糊自适应PID的双液压缸位置同步控制系统。运用MATLAB仿真软件,将模糊自适应PID控制器应用于液压同步控制系统中。结果表明,使用模糊PID控制器的控制系统能够减小由外负载差异引起的液压缸位置同步误差,提高装配平台的运动精度。     

Controller tuning based on optimization algorithms of a novel spherical rolling robot

This study presents the construction process of a novel spherical rolling robot and control strategies that are used to improve robot locomotion. The proposed robot drive mechanism is constructed based on a combination of the pendulum and wheel drive mechanisms. The control model of the proposed robot is developed, and the state space model is calculated based on the obtained control model. Two control strategies are defined to improve the synchronization performance of the proposed robot motors. The proportional-derivative and proportional-integral-derivative controllers are designed based on the pole placement method. The proportional-integral-derivative controller leads to a better step response than the proportional-derivative controller. The controller parameters are tuned with genetic and differential evaluation algorithms. The proportional-integral-derivative controller which is tuned based on the differential evaluation algorithm leads to a better step response than the proportional-integral-derivative controller that is tuned based on genetic algorithm. Fuzzy logics are used to reduce the robot drive mechanism motors synchronizing process time to the end of achieving a high-performance controller. The experimental implementation results of fuzzy-proportional-integral-derivative on the proposed spherical rolling robot resulted in a desirable synchronizing performance in a short time.

     

Fuzzy MRAC controller design for vane-type air motor systems

Air motors are widely used in the automation industry due to special requirements, such as spark-prohibited environments, the mining industry, chemical manufacturing plants, and so on. The purpose of this paper is to analyze the behavior of a vane-type air motor and to design a model reference adaptive control (MRAC) with a fuzzy friction compensation controller. It has been noted that the rotational speed of the air motor is closely related to the compressed air’s pressure and flow rate, and due to the compressibility of air and the friction in the mechanism, the overall system is actually nonlinear with dead-zone behavior. The performance of the previous controllers implemented on an air motor system demonstrated a large overshoot, slow response and significant fluctuation errors around the setting points. It is important to eliminate the dead-zone to improve the control performance. By considering the effects of the dead-zone behavior, we have developed an MRAC with fuzzy friction compensation controller to overcome the effect of the dead-zone. The following experimental results are given to validate the proposed speed control strategy.     

Active suppression of chatter in peripheral milling. Part II. Application of fuzzy control

In this paper, a feasibility study is conducted where fuzzy logic control is investigated to actively vary spindle speed modulation parameters for chatter suppression. A justification for using fuzzy control is given, as well as a brief synopsis of the fuzzy inferencing mechanism. Proportional and proportional-integral fuzzy control algorithms are developed. The set point in these controllers is established from experimental observations and measurements of the machined surfaces. Controller performance is tested by simulating changes in the axial depth of cut from a stable depth to 20% and 50% beyond the stable limit for constant speed cutting. It was found that both controllers were able to regulate the vibration in the milling process, however, the proportional-integral controller generally exhibited more desirable performance characteristics.     

FUZZY NEURAL NETWORK CONTROL FOR VIBRATION WAVEFORM SYSTEM OF MOLD

Combining with the characteristic of the fuzzy control and the neural network control(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesis design method of the control law and fast speed learning algorithm of the parameters of networks are put forward. The output of the controller is composed of two parts, part one is derived on basis of the principle of sliding control, the lower order model and the estimated parameters of the plant are only required, part two is derived on basis FNN, it is used to compensate the uncertainties of the systems. Because new type of FNN controller extracts from the advantages of the intelligent control and model based sliding mode control, the numbers of adjusting parameters and the structure of FNN are simplified at large, and the practical significance and variation range are attached to each layer of the network and its connected weights, the control performance and learning speed are increased at large. The lightness of the conclusions     

New modifying self-organizing fuzzy controller for robotic motion control

The precise motion control of robotic manipulators is important in improving productivity and quality. However, robotic manipulators are multivariable nonlinear dynamic systems. Designing a model-based controller for robotic system control is difficult because its mathematical model is hard to accurately establish. This study proposed a self-organizing fuzzy controller (SOFC) to control a robotic system and evaluate its control performance. The SOFC continually updates the learning strategy in the form of fuzzy rules during the control process. The learning rate and the weighting distribution value of the controller are hard to regulate, so its fuzzy control rules may be modified to such an extent that the system response generally causes oscillatory phenomena. Two fuzzy logic controllers were designed according to the system output error and the error change, and introduced to the SOFC to determine the appropriate parameters of the learning rate and the weighting distribution, in order to eliminate this oscillation. This new modifying self-organizing fuzzy controller (NMSOFC) can effectively improve the control performance of the system, reduce the time consumed to establish a suitable fuzzy rule table, and support practical and convenient fuzzy controller applications. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old robot for a control system to evaluate the feasibility of motion control. Experiment results indicate the NMSOFC has better control performance in reducing the tracking errors of the joint-space trajectories and the positions, and requires less computational time than does the traditional fuzzy controller.     

Analysis,control and design of a non-inverting buck-boost converter: A bump-less two-level T–S fuzzy PI control

In this paper, a new modified fuzzy Two-Level Control Scheme (TLCS) is proposed to control a non-inverting buck-boost converter. Each level of fuzzy TLCS consists of a tuned fuzzy PI controller. In addition, a Takagi–Sugeno–Kang (TSK) fuzzy switch proposed to transfer the fuzzy PI controllers to each other in the control system. The major difficulty in designing fuzzy TLCS which degrades its performance is emerging unwanted drastic oscillations in the converter output voltage during replacing the controllers. Thereby, the fuzzy PI controllers in each level of TLCS structure are modified to eliminate these oscillations and improve the system performance. Some simulations and digital signal processor based experiments are conducted on a non-inverting buck-boost converter to support the effectiveness of the proposed TLCS in controlling the converter output voltage.     

电液压力控制系统的模糊智能控制

本文以四辊冷轧机为对象,根据电液弯辊压力控制系统的特点,综合运用优化理论和模糊控制理论,对电液弯辊压力控制系统采用模糊智能控制,取得了满意的效果。     

模糊自适应PID控制的仿真研究

首先介绍了PID控制系统的工作原理,因PID控制器结构简单、实现简单,控制效果良好,所以已得到广泛应用。但当控制对象变化时,控制器的参数难以自动调整。为了使控制器具有较好的自适应性,可以采用模糊控制理论的方法来实现控制器参数的自动调整。模糊PID控制系统就是模糊理论与传统的PID控制器的结合。最后以一控制对象为例,对该两种方式的控制进行了仿真和比较,并得出了相应的结论。     

复合模糊控制器在航空发动机上的应用研究

提出一种基于参考模型的复合模糊控制方法,它把主模糊控制器与基于参考模型的逆模糊控制器进行复合,构成复合模糊控制器,主、逆模糊控制器输出构成合成控制量。并把该方法用于航空发动机控制,通过让被控制量逼近参考模型性能,实现对低压转子转速的无静差控制与基本模糊控制相比,控制性能改善较大,供油量变化物理可实现。仿真结果证明了该方法的有效性。     

Calculation of PID controller parameters by using a fuzzy neural network

In this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (Ms). The FNN system is used to identify the relationship between plant model and controller parameters based on IAE and Ms. To derive the tuning rule, the dominant pole assignment method is applied to simplify our optimization processes. Therefore, the FNN system is used to automatically tune the PID controller for different system parameters so that neither theoretical methods nor numerical methods need be used. Moreover, the FNN-based formula can modify the controller to meet our specification when the system model changes. A simulation result for applying to the motor position control problem is given to demonstrate the effectiveness of our approach.