基于线性自抗扰的消防水炮控制系统

针对消防机器人中水炮控制系统存在非线性、快时变、强耦合的特点,提出一种基于线性自抗扰的控制策略以提高控制精度。给出消防水炮伺服控制系统的结构及数学模型,设计线性自抗扰控制器,并根据现代控制理论给出线性自抗扰控制的参数选择方法。在消防水炮控制实验平台对线性自抗扰控制器与常规的PD控制器进行对比实验。实验结果表明,该方案与传统PD控制相比较,具有控制精度高、超调量小的优点,改善了系统的控制性能。     

惯性系统平台的自适应稳定回路研究

稳定回路在平台惯性系统中起着关键作用.但在设计稳定回路的控制器时,发现普通PID控制有抗干扰能力不强、控制参数易改变的缺点;因此设计了一种基于模糊控制原理的自适应模糊自抗扰控制器.该控制器充分结合了模糊控制器和自抗扰控制器的各自优势,利用模糊控制的推理能力,达到自动调整参数的目的.通过对光纤陀螺随动系统的仿真结果表明,在控制效果上,该控制器的自适应能力和抗干扰能力都优于经典PID控制器.说明自适应模糊自抗扰控制器在稳定回路中具有很好的应用前景.     

拼接镜面望远镜位移促动器系统的自抗扰控制

针对拼接镜面望远镜主动光学控制技术的要求,设计了一种改进型自抗扰控制器以改善位移促动器系统的位置跟踪性能和提高抗扰动能力。首先,建立了拼接镜面位移促动器系统及扰动风载的数学模型;设计了改进型自抗扰控制器,并给出了控制器参数选择的方法。其次,对位移促动器控制系统进行了仿真分析,验证了控制器的可行性。最后,利用风载扰动模拟装置,在位移促动器系统中引入扰动,并对比改进型自抗扰控制器与线性自抗扰控制器以及PID控制器控制性能。实验结果表明,改进型自抗扰控制器系统阶跃跟踪的稳定时间为201 ms,稳态均方差为7.1 nm,无超调;风载干扰实验中,改进型ADRC的最大偏差值为38.8 nm,稳态均方差为7.6 nm,改进型ADRC的性能明显优于线性自抗扰控制器和PID控制器,对提高位移促动器系统的性能有较高的实用性。     

光电稳定平台变论域模糊自抗扰控制器设计

为了提高线性自抗扰控制(LADRC)应用下的光电稳定平台稳定精度及抗干扰能力,提出一种变论域模糊自抗扰控制(VFADRC)方法.在系统模型未知的情况下,在线性自抗扰的设计中引入不依赖模型信息的模糊控制器,使用伸缩因子函数实现变论域设计,并将VFADRC与线性自抗扰及模型辅助自抗扰(MLADRC)方法进行仿真对比.仿真结...     

基于自抗扰技术的四旋翼姿态解耦控制方法

针对小型四旋翼飞行器姿态控制问题,基于姿态非线性耦合数学模型,设计了一种自抗扰姿态控制器。引入自抗扰控制技术,介绍了自抗扰控制器结构,包括安排过渡过程,扩张状态观测器以及非线性状态误差反馈。针对模型非线性耦合特点,介绍了多变量系统的自抗扰解耦控制原理,并设计了一种自抗扰姿态解耦控制器。基于Simulink搭建仿真模型进行了仿真。参数整定及仿真结果表明,所设计自抗扰控制器具有强鲁棒性、抗干扰性,系统具有良好的动态性能和稳态性能,对非线性耦合系统能有效地控制。     

自调整模糊控制器在永磁同步电机矢量控制中的应用

模糊控制器对系统模型依赖程度低,性能优异,已经在许多场合得到了应用。传统的永磁同步电机矢量控制系统采用PI控制,在电机参数变化或负载波动较大时性能不佳。针对这一问题,本文设计了一种基于量化因子和比例因子自调整的自适应模糊控制器。仿真结果表明,与传统PI和基本模糊控制器相比,这种参数自调整模糊控制器能使系统具有更好的抗扰性和更优良的稳态性能。     

半捷联导引头混合自抗扰控制系统设计

为了使半捷联导引头在干扰力矩和刻度尺误差引起的耦合干扰及其他不确定干扰下仍具有很强的鲁棒性,提出了伺服系统混合自抗扰控制（Active Disturbance Rejection Control,ADRC）方案。首先,建立了导引头半捷联稳定平台数学模型;其次,设计了半捷联导引头稳定平台混合自抗扰控制系统,通过对自抗扰稳定回路频带特性进行研究,分析了控制器参数对控制性能的影响,给出了控制参数设计原则;最后,对混合自抗扰控制方案进行了数字仿真验证。仿真结果表明:相比于传统控制器,混合自抗扰控制器能获得更好的控制精度,能有效克服干扰力矩和刻度尺误差对导引头的影响,在典型弹体频率2 Hz处隔离度幅值比传统控制器最多能降低约67.9%。研究成结果可为半捷联导引头稳定控制系统的设计提供指导。     

小型漂浮式卫星天线自抗扰控制器的研究

研究了一种适用于军事隐蔽式侦察的小型漂浮式卫星天线双环自抗扰控制器,实现了在中小涌浪扰动下天线自动跟踪目标卫星的俯仰伺服控制. 以自抗扰理论为基础,结合小型天线俯仰控制的特点分别设计了位置环和速度环自抗扰控制器;比较了双环自抗扰控制器和比例-积分-微分(Proportional-Integral-Derivative,PID)控制器的阶跃响应,验证了双环自抗扰控制器性能优于PID控制器性能;利用半实物仿真平台,以中小涌浪扰动下天线系统俯仰角的变化为控制器的输入,进行天线俯仰伺服控制,通过检测到的信标信号验证了双环自抗扰控制器可以实现中小涌浪扰动下天线对目标卫星的稳定跟踪.     

四旋翼无人机轨迹跟踪控制系统设计

针对四旋翼无人机参数不确定性和对外部干扰敏感的问题,提出一种基于线性自抗扰的轨迹跟踪控制系统设计方案。线性自抗扰能够很好地克服无人机的强耦合性、模型不确定性以及外部干扰问题。将四旋翼无人机的轨迹跟踪控制系统分为内外两个环路,内环采用线性自抗扰控制器,外环采用简单的PD控制器。在仿真平台上对线性自抗扰控制系统进行轨迹跟踪实验,并与传统的PID控制系统进行对比分析。通过仿真实验证明,所设计的线性自抗扰控制器不仅能够很好地估计并补偿系统所受内外部干扰,而且对四旋翼无人机参数的不确定性具有较强的鲁棒性,能够满足无人机姿态调节快速和高稳定度的控制要求,性能指标明显优于PID控制器。     

基于自抗扰控制器的柴油机转速控制

当柴油机作为转速控制系统的被控对象时,是一个多变量强耦合非线性系统,采用经典PID控制难以得到满意的控制效果,但是自抗扰控制理论设计的控制器,能够提高调速系统的精度、准确度和柴油机的抗扰动能力。本文主要介绍了自抗扰控制技术(Active Disturbance Rejection Control Technique,ADRC),并且根据自抗扰控制技术设计了切实可行的自抗扰控制器,通过与PID控制的仿真比较,显示出自抗扰控制器对转速控制的较小超调量和较短调节时间,反应出良好的动态性能和稳态特性。     

New hybrid fuzzy controller for direct torque control induction motor drives

A new hybrid fuzzy controller for direct torque control (DTC) induction motor drives is presented in this paper. The newly developed hybrid fuzzy control law consists of proportional-integral (PI) control at steady state, PI-type fuzzy logic control at transient state, and a simple switching mechanism between steady and transient states, to achieve satisfied performance under steady and transient conditions. The features of the presented new hybrid fuzzy controller are highlighted by comparing the performance of various control approaches, including PI control, PI-type fuzzy logic control (FLC), proportional-derivative (PD) type FLC, and combination of PD-type FLC and I control, for DTC-based induction motor drives. The pros and cons of these controllers are demonstrated by intensive experimental results. It is shown that the presented induction motor drive is with fast tracking capability, less steady state error, and robust to load disturbance while not resorting to complicated control method or adaptive tuning mechanism. Experimental results derived from a test system are presented confirming the above-mentioned claims.     

基于FPGA的模糊PID控制器设计

针对实现传统模糊PID控制器时,需要建立比例、积分和微分三个模糊控制器,存在模糊规则较繁杂、运算量大、速度慢等问题,提出了以PD模糊控制器代替PI模糊控制器,采用两个PD模糊控制器,并引入FPGA技术,实现模糊PID控制器.通过Quartus Ⅱ和Matlab联合仿真,比较了基于FBC和SBC实现的模糊PID控制器的控制效果,验证了设计方案的正确性和可行性.     

A Genetic Fuzzy Controller for Vehicle Automatic Steering Control

This paper presents the design and experimental implementation of a genetic fuzzy controller for automatic steering of a small-scaled vehicle. We first derive a dynamic model of the vehicle via system identification and show that the model exhibits similar characteristics to full-sized vehicles. Subsequently, a stable fuzzy proportional-derivative controller is designed and optimized by genetic algorithms. The control system is transformed into a Lureacute system, and Lyapunov's direct method is used to guarantee the stability of the control system. Experimental studies suggest that the control system is insensitive to parametric uncertainty, load, and disturbances. The performance of the proposed controller is also compared against a conventional proportional derivative (PD) controller. Experimental results confirm that it outperforms the conventional PD controller, particularly in terms of robustness     

A two-layered fuzzy logic controller for systems with deadzones

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. In particular, we show that a usual "fuzzy PD" controller applied to a system with a deadzone suffers from poor transient performance and a large steady-state error. In this paper, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator followed by a usual fuzzy PD controller. Our proposed controller exhibits superior transient and steady-state performance compared to usual fuzzy PD controllers. In addition, the controller is robust to variations in deadzone nonlinearities. We illustrate the effectiveness of our scheme using computer simulation examples.<>     

SPR污水处理系统的智能控制

针对SPR污水处理系统工作中所存在的问题,控制出水化学需氧量COD保持恒定,以保证在各种务件下出水的水质,介绍了一种采用混合型模糊控制器控制的SPR污水处理系统的控制原理,并设计了模糊控制器、PI调节器和控制软件.仿真表明控制速度快,超调量小,调节时间短.系统动态性能和静态性能良好,具有较高的鲁棒性和性价比,实用性强.     

Vibration Suppression Using Single Neuron-Based PI Fuzzy Controller and Fractional-Order Disturbance Observer

An approach is proposed for vibration suppression in a two-inertia system using an integration of a fractional-order disturbance observer and a single neuron-based PI fuzzy controller. The former is used to obtain disturbance estimate and generate compensation signal, and the latter is utilized to realize outer loop control. Fractional-order disturbance observer has a wider range to select a suitable tradeoff between robustness and vibration suppression, because introduction of fractional calculus makes universe of relative degree of Q-filter is expanded from integer domain to real-number domain. For the single neuron-based PI fuzzy controller, a single neuron makes up a PI controller and such a controller is embedded in each cell of the fuzzy control table. Thus, the fuzzy control table is changed into a controller matrix and it constructs a nonlinear adaptive controller with parameter self-tuning property. Experimental results illustrate that the integration of fractional-order disturbance observer and single neuron-based PI fuzzy controller can improve the performance of disturbance attenuation and system robustness     

Adaptive Fuzzy Controller of the Overhead Cranes With Nonlinear Disturbance

Overhead cranes are common industrial structures that are used in many factories and harbors. They are usually operated manually or by some conventional control methods, such as the optimal and PLC-based methods. The theme of this paper is to provide an effective all-purpose adaptive fuzzy controller for the crane. This proposed method does not need the complex dynamic model of the crane system, but it uses trolley position and swing angle information instead to design the fuzzy controller. An adaptive algorithm is provided to tune the free parameters in the crane control system. The ways to speed the transportation and reduce the computational efforts are also given. Therefore, the designing procedure of the proposed controller will be very easy. External disturbance, such as the wind and the hit, which always deteriorates the control performance, is also discussed in this paper to verify the robustness of the proposed adaptive fuzzy algorithm. At last, several experimental results with different wire length and payload weight compare the feasibility and effectiveness of the proposed scheme with conventional methods     

超声电机驱动的机器人的模糊神经网络控制

超声电机的小质量、大转矩、响应快等特点,是其成为小型直接驱动机器人执行器的基础。通过对超声电机的伺服特性研究及关节型机器人动力学分析,提出了超声电机驱动的机器人的模糊神经网络控制的复合控制方法,该方法中,模糊子控制器实现了关节定位的初步控制,神经网络子控制器起到降解稳态误差、提高控制精度作用。文中较详细地研究了复合控制器的结构及两个子控制器的设计问题。为了检验控制效果,对控制系统进行了仿真,结果表明,采用这种复合控制器可获得较高的位置精度。     

Kinematics control of a pneumatic system by hybrid fuzzy PID

In a pneumatic system, normally, the piston can stop at only two terminal endpoints. In order to extend the capabilities of the system, this research is conducted to develop a kinematics control-based pneumatic system. Both position and velocity of the pneumatic piston are controlled in such a way that the controlled piston is able to move with the specified velocity to the target position. A hybrid of fuzzy and proportional-plus-integral-plus-derivative (PID) control algorithm is proposed in this paper as the solution. The control algorithm is separated into two parts: fuzzy control and PID control. The fuzzy controller is used to control the piston when the piston locates far away from the target position whereas the PID controller is applied when the piston is near the desired position. The development starts with designing of a position sensor to detect position information of the piston. The sensor-manipulating circuit consisting of potentiometer, inverting amplifier, summing amplifier, low-pass filter and analog-to-digital converter is then designed and realized. Next, the proposed hybrid of fuzzy and PID control is implemented and programmed on the microprocessor. In order to test performance of the system, settling time and steady-state error of five control algorithms – proportional (P) control, proportional-plus-integral (PI) control, proportional-plus-derivative (PD) control, PID control, and hybrid of fuzzy and PID control – are investigated. The results from the experiments show that the proposed hybrid of fuzzy and PID control gives the most satisfied settling time and steady-state error.