角伺服系统模糊自适应PID控制研究

将模糊控制和PID控制相结合,提出了一种智能复合控制策略,并将其应用于某型导弹系统角伺服系统的控制。利用模糊控制在线自适应调整PID控制器的参数,从而使系统的静态和动态性能指标较为理想。在Simulink中的仿真结果表明,这种模糊PID控制器的控制效果优于单纯的PID控制,超调量小,抗干扰性能强,对变参数系统的鲁棒性强,满足在线实时自适应控制的要求。     

基于遗传算法和 Vague集的液压位置控制系统自适应 PID控制

在被控对象模型精度不高的情况下,设计了一种自适应PID控制方法,提高其鲁棒性,以确保系统的响应具有最优的动态性能和稳态性能。该方法在常规PID控制的基础上,引入智能技术,在线实时调整PID控制器的3个参数。该控制器主要由3部分构成:一是采用遗传算法优化模糊推理规则;二是精确的Vague集推理规则表;三是基于Vague集相似度量的自适应PID控制。仿真结果表明,该控制方法响应速度快,稳态精度高。     

基于相似理论的航空发动机转速自适应PID控制

根据航空发动机在相似坐标系中特性不变的特点，提出一种基于相似理论的航空发动机转速自适应PID控制。该方案采用衰减曲线法进行换算PID参数整定，获得自适应调节律。仿真结果表明控制器具有良好的动静态性能，自适应性和鲁俸性。所得参数变化规律对数控系统全包线内PID控制器的参数选择具有一定的指导意义。     

基于深度信念网络的船用燃气轮机自适应控制

针对船用燃气轮机非线性强、惯性大和负载多变等特点,提出1种基于深度信念网络的自适应控制器。该控制器结合了深度信念网络和传统PID控制器,利用深度信念网络对燃气轮机的转速误差信息以及负载状态提取实时特征,在线调节PID参数,并将参数传递给PID控制器,由其输出控制量。通过数字仿真验证表明:该控制器满足燃气轮机转速控制的要求,并且具有良好的自适应性,在不同工况下,能够对燃气轮机转速进行准确控制,使得系统快速响应的同时无超调量。     

一种新型的智能非线性PID控制器

在分析总结标准PID控制器、各种变形PID控制器、非线性PID控制器特点的基础上，提出了一种智能非线性PID(INPID)型变结构控制器。将该INPID控制器应用于典型带延迟一阶对象和二阶对象控制，并与传统PID进行了对比，证明该控制器具有良好的控制效果、广泛的对象适应性和很强的鲁棒性。仿真结果表明．在控制量受限越强和系统参数变化范围越大的情况下，其优势越突出。     

空面导弹模型参考自适应控制设计与仿真

为提高空面导弹控制系统的性能,解决传统PID控制在导弹大空域飞行、系统参数大范围变化时控制能力欠缺的问题,以法向过载作为被控量代替对迎角、侧滑角的控制,基于波波夫超稳定性理论设计了模型参考自适应控制器。六自由度仿真结果表明,所设计的自适应控制器具有良好的控制性能和鲁棒性。     

专家-模糊自适应PID算法在伺服控制系统中的应用

为满足工程中伺服系统所用控制算法的要求,基于控制系统输出误差及误差变化率的大小,在专家PID和模糊自适应PID之间进行模式转换,提出一种基于专家控制的模糊自适应PID控制算法。将该算法用于飞机燃油全模试验伺服控制系统中,并使用Matlab进行仿真。结果表明,该算法既具有模糊PID控制精度高、稳态性好、鲁棒性强的优点,又继承了专家PID控制器响应快速的特点,具有很好的控制效果。     

航空发动机自适应神经网络PID控制

本文提出了一种航空发动机多变量自适应神经网络 PID控制方法, 采用基于共轭梯度的神经网络学习算法在线整定控制器参数。该控制器的设计无需知道发动机精确模型, 具有响应速度快、抗干扰能力强和鲁棒性好等优点。控制器不仅算法简单, 实现容易, 而且适用范围广。      

基于非线性PID控制的无人机飞控系统优化设计

针对固定翼无人机的飞行控制律设计问题,提出了一种基于非线性PID控制原理的控制器。该控制器的比例、积分、微分增益是控制误差的非线性函数。确定该组函数的参数主要根据最优控制理论选择性能指标,采用遗传算法寻优。在此基础上,实现对无人机飞行控制律的优化设计。仿真结果表明,使用该控制器设计的无人机飞行控制回路比用常规PID控制器表现出很大的优越性。     

基于迭代学习的PID控制器研究

将目前对u(t)的记忆与修正改成对期望控制ud(t)的记忆与修正,提出两种新的拟合控制系统的PID控制器参数的方法。这两种方法实现的PID控制器较常规的PID控制器结构简单,作用于系统可获得较佳的动态特性和较强的鲁棒性。研究目的是为迭代学习控制理论在设计性能优良的控制器方面扩大应用领域。     

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators. The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID (FOPID) controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead (N-M) optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers.     

基于内模控制的多输入多输出高阶振动系统

常规的比例-积分-微分(PID)控制器一般用于单输入单输出系统。对于具有多个输入和多个输出且相互之间具有较强耦合作用的高阶多变量系统,PID控制器的设计常难以实现。针对高阶柔性结构振动控制问题,提出如下PID控制策略：首先在某一频段内对频响函数进行拟合降阶,建立过程模型,然后采用内模控制方法和麦克劳林展开式设计多输入多输出振动系统PID控制器。以4层刚架进行建模仿真计算,结果表明,通过本文方法设计的PID控制器,可以在避免未控模态影响的前提下,使外部干扰得到有效抑制,得到比较理想的控制效果。     

复合材料布带缠绕成型压力控制技术

复合材料布带缠绕成型过程中的压力波动会影响制品的致密度和均匀度,同时会造成缠绕制品的界面强度及纤维体积分数不一致。芯模的圆度误差和安装误差会导致压力波动,气体的可压缩性、比例阀的死区效应、阀的流量非线性、气缸摩擦力及测量噪声会对缠绕压力控制造成非线性干扰。因此,设计了自适应灰色预测模糊PID控制器,通过对气缸输出缠绕压力的灰色预测,正确反映了压力信号的变化趋势,为模糊PID控制的推理提供了可靠依据。同时,采用两个独立的模糊推理系统来调节预测控制的步长和步长自整定算法的比例因子。仿真分析和实验结果表明：相比于传统PID控制,采用自适应灰色预测模糊PID控制使缠绕压力的稳态误差减小了62%,超调量减小了80%,有效提高了复合材料缠绕成型压力控制系统的稳定性。     

基于微分进化算法的二自由度PID控制器参数优化

针对二自由度PID控制器参数多、调节困难等问题,提出了一种基于微分进化算法参数调节优化方法。证明了微分进化算法能够收敛到平稳点,并具有概率全局收敛性。研究了二自由度PID控制器参数与抑制特性、跟踪特性的关系,并将微分算法与遗传算法、粒子群算法的参数优化结果进行了比较。仿真验证表明,微分算法能够更好地实现二自由度PID控制器参数的调节,具有优异的跟踪特性和抑制特性。     

线性插值方法在某型航空发动机模型控制器设计中的应用

采用线性插值算法,根据已知点的精确模型求取包线内任1点的发动机模型；应用Z-N整定经验公式,对插值点进行了PID控制器设计；使用simulink进行了建模仿真。仿真结果表明,所设计的控制器控制效果良好。     

基于变权重变异鸽群优化的无人机空中加油自抗扰控制器设计

针对空中加油过程中的受油机模型建模误差和强扰动以及自抗扰控制器（ADRC）人工参数整定难的问题，提出了一种基于变权重变异鸽群优化（VWMPIO）算法的无人机自抗扰控制器优化算法。首先，给出了六自由度无人机（UAV）模型，基于自抗扰控制结构设计了一种受油机的姿态控制器，在此基础上用所提出的变权重变异鸽群优化算法整定了自抗扰控制器参数。随后，将变权重变异鸽群优化与其他基本鸽群优化算法、粒子群优化算法进行了实验对比，并从控制性能和抗噪声性能的角度对自抗扰控制器和传统的比例-微分-积分（PID）控制器进行了仿真对比。实验结果表明所提算法能提高复杂态势环境下无人机空中加油的控制精度和扰动抑制性能。     

A New Hybrid Control Scheme for an Integrated Helicopter and Engine System

A new hybrid control scheme is presented with a robust multiple model fusion control(RMMFC) law for a UH-60 helicopter and an active disturbance rejection control(ADRC) controller for its engines.This scheme is a control design method with every subsystem designed separately but fully considering the couplings between them.With three subspaces with respect to forward flight velocity,a RMMFC is proposed to devise a four-loop reference signal tracing control for the helicopter,which escapes the closed-loop system from unstable state due to the extreme complexity of this integrated nonlinear system.The engines are controlled by the proposed ADRC decoupling controller,which fully takes advantage of a good compensation ability for unmodeled dynamics and extra disturbances,so as to compensate torque disturbance in power turbine speed loop.By simulating a forward acceleration flight task,the RMMFC for the helicopter is validated.It is apparent that the integrated helicopter and engine system(IHES) has much better dynamic performance under the new control scheme.Especially in the switching process,the large transient is significantly weakened,and smooth transition among candidate controllers is achieved.Over the entire simulation task,the droop of power turbine speed with the proposed ADRC controller is significantly slighter than with the conventional PID controller,and the response time of the former is much faster than the latter.By simulating a rapid climb and descent flight task,the results also show the feasibility for the application of the proposed multiple model fusion control.Although there is aggressive power demand in this maneuver,the droop of power turbine speed with an ADRC controller is smaller than using a PID controller.The control performance for helicopter and engine is enhanced by adopting this hybrid control scheme,and simulation results in other envelope state give proofs of robustness for this new scheme.     

MULTI-CONTROLLER STRUCTURE OF SUPERMANEUVERABLE AIRCRAFT

Supermaneuver flight is often operated withhigh angle- of- attack and high angular rates.Su-per- maneuver flight cannot be controlled by aconventional gain- scheduled controller but canbe controlled by using a nonlinear dynamic- in-version controller[1～ 3] .　　 This paper presents a method to use twokinds of controllers,nonlinear dynamic- inver-sion and conventional gain- scheduled con-trollers,in a flight control system.The nonlin-ear dynamic- inversion controller is used to con-trol superm…     

Automatic landing system using neural networks and radio-technical subsystems

The paper focuses on the design of a new automatic landing system(ALS) in longitudinal plane; the new ALS controls the aircraft trajectory and longitudinal velocity. Aircraft control is achieved by means of a proportional-integral(PI) controller and the instrumental landing system– the first phase of landing(the glide slope) and a proportional-integral-derivative(PID) controller together with a radio-altimeter – the second phase of landing(the flare); both controllers modify the reference model associated with aircraft pitch angle. The control of the pitch angle and longitudinal velocity is performed by a neural network adaptive control system, based on the dynamic inversion concept, having the following as components: a linear dynamic compensator, a linear observer, reference models, and a Pseudo control hedging(PCH) block. The theoretical results are software implemented and validated by complex numerical simulations; compared with other ALSs having the same radio-technical subsystems but with conventional or fuzzy controllers for the control of aircraft pitch angle and longitudinal velocity, the architecture designed in this paper is characterized by much smaller overshoots and stationary errors.