基于CGT的自适应模型输出跟踪控制及其应用北大核心CSCD

基于CGT(Command Generator Tracker)理论的模型输出跟踪控制可实现对低阶理想参考模型的性能跟踪。然而,当被控对象会随环境变化而改变时,控制系统的跟踪性能会有所下降。为了进一步提高控制系统的适应性,提出了一种基于CGT的自适应模型输出跟踪控制方法。该方法通过在线辨识系统参数,自动调整前馈输入,从而提高控制系统的跟踪性能。随后,针对网络化铝板温度系统应用了提出的基于CGT的自适应模型输出跟随控制器。实验验证了控制方法的有效性,实现了对铝板温度的网络化跟踪控制。     

利用两类状态的混合MRACS设计

为提高使用低阶参考模型的MRACS的抗扰能力,提出同时采用被控对象和参考模型状态构成混合自适应控制器的方法,数字仿表真明设计方法是正确的,控制效果良好。     

具有减少辨识参数的随机多变量极点配置自适应控制器

本文提出了一种新的限制输出个数减少随机多变量自适应控制中辨识参数的方法，并给出了减少辨识参数的极点配置自适应算法。虽然采用ｎ个输入１个输出的减少辨识参数的模型来设计控制器，但所提出的控制器能够保证被控系统的几个输出跟踪参考输入信号，仿真结果表明，所提出的方法是成功的。     

多变量发酵过程的神经网络在线解耦控制

为提高多变量系统解耦控制的性能,提出了一种基于参考模型的神经网络在线解耦控制方法.构造神经网络实现前馈解耦,通过参考模型的输出与被控系统输出估计耦合作用对被控量的影响,由此设计神经网络权值参数学习算法,在线调整网络参数使多变量耦合系统实现解耦;对解耦后的子系统分别设计闭环控制器,以达到优良的控制性能.仿真实验结果表明,提出的解耦控制方法是简单有效的.     

大滞后多变量计算机控制系统的设计与研究

提出了一种多变量大滞后计算机控制系统的设计方法.介绍了系统的设计思想,数字控制器的设计方法及在多输入多输出大滞后系统中的应用实现.以具有滞后的二输入二输出多变量被控对象(两种形式)为例,说明了系统设计方法及步骤,并进行仿真实验.实验结果表明,该数字控制器能够使其控制质量满足性能要求,具有良好的控制效果.     

基于极点配置的多模型自适应控制

基于极点配置技术对单输入单输出离散时间被控对象提出多模型自适应控制算法，在保证稳定性的前提下，算法对被控对象参数跳变时能进行有效的控制，并提高了系统的瞬态响应。     

过热气温的多内模自适应内模控制的研究

针对电厂过热汽温被控对象具有大惯性、大滞后特性且对象参数随负荷变化较大等因素,提出了一种基于多模型的自适应内模控制策略。通过在不同工况辨识得到其多模型,设计出相应的内模控制器,根据运行工况选择相应的控制器,从而实现全工况运行的自适应;同时以火电厂过热汽温被控对象为参考模型设计自适应控制律,使控制器内部模型的参数逐步逼近被控对象的参数直至相等。仿真结果表明,该控制策略比常规的内模控制具有更好的控制品质。     

带有改进自适应动量因子的四容水箱DRNN控制系统设计

针对多变量耦合的四容水箱系统,提出一种带有自适应动量因子的对角递归神经网络(DRNN)自学习PID控制方法.首先依据四容水箱实验平台的结构,简要介绍了被控对象的数学模型,并给出了以PID为主控制器,DRNN用于辨识系统动态的总体控制方案;其次,考虑到耦合系统中控制输入与系统输出的之间耦合作用,为了减小整体跟踪误差,给出...     

多变量解耦控制系统设计与仿真

工业生产过程中,被控系统越来越复杂,需要控制的变量通常不止一对,而且相互耦合,较成熟的线性多变量控制理论与设计方法已难以满足实际的多变量生产过程控制。本文针对多变量强耦合带有延迟环节的被控系统,研究了一种简化的串联前馈补偿解耦控制器设计方法。根据被控对象的辨识模型,设计串联前馈补偿解耦器,使系统解耦成单输入单输出模型,进而分别对解耦后输入输出模型设计PID控制器,整定PID控制器参数。仿真结果表明该方法具有较好的解耦能力和鲁棒性,算法简单,易于实现。     

多变量解耦控制系统设计与仿真北大核心CSCD

工业生产过程中,被控系统越来越复杂,需要控制的变量通常不止一对,而且相互耦合,较成熟的线性多变量控制理论与设计方法已难以满足实际的多变量生产过程控制。本文针对多变量强耦合带有延迟环节的被控系统,研究了一种简化的串联前馈补偿解耦控制器设计方法。根据被控对象的辨识模型,设计串联前馈补偿解耦器,使系统解耦成单输入单输出模型,进而分别对解耦后输入输出模型设计PID控制器,整定PID控制器参数。仿真结果表明该方法具有较好的解耦能力和鲁棒性,算法简单,易于实现。     

利用模糊系统的直升机的自适应控制

针对直升机动力学为非线性,且存在不确定因素和状态变化,设计利用模糊系统的自适应控制器.设计的控制器是系统的输出跟踪参考模型输出的直接调整模糊控制器参数的自适应控制器.又利用Lyapunov函数保证了闭环控制系统的稳定性并推导最优的自适应规律.实验结果表明,有外部扰动的情况下所设计的自适应控制器比模糊控制器对直升机控制具有良好的动态响应和稳定性,是一种非常有效的控制方法.     

An indirect model reference robust fuzzy adaptive control for a class of SISO nonlinear systems

In this paper we are interested in robust adaptive fuzzy control of nonlinear SISO systems in the presence of parametric uncertainties. The plant model structure is represented by the Takagi-Sugeno (T-S) type fuzzy system. An indirect adaptive fuzzy controller based on model reference control scheme is proposed to provide asymptotic tracking of reference signal. The controller parameters are computed at each time. The plant state tracks asymptotically the state of the reference model for any bounded reference input signal. Inverted pendulum and mass spring damper are used to check the performance of the proposed controller.     

Adaptive control of rigid body satellite

The minimal controller synthesis （MCS） is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.     

利用模糊系统的自适应模糊控制器

针对非线性系统控制,设计了利用TSK(Takagi-Sugeno-Kang)模糊系统的自适应模糊控制器。所设计的自适应控制方法是参考模型自适应控制方法,而且利用Lyapunov函数保证了闭环系统的稳定性,同时推导了最优的自适应控制规律。首先,根据控制对象的输入输出数据建立TSK模糊模型,然后,由TSK模糊模型设计初期的TSK模糊控制器,并根据自适应规律随时调整模糊控制器参数。倒立摆系统的仿真实验验证了所设计的自适应模糊控制器的有效性。     

Stable indirect adaptive switching control for fuzzy dynamical systems based on T–S multiple models

A new indirect adaptive switching fuzzy control method for fuzzy dynamical systems, based on Takagi–Sugeno (T–S) multiple models is proposed in this article. Motivated by the fact that indirect adaptive control techniques suffer from poor transient response, especially when the initialisation of the estimation model is highly inaccurate and the region of uncertainty for the plant parameters is very large, we present a fuzzy control method that utilises the advantages of multiple models strategy. The dynamical system is expressed using the T–S method in order to cope with the nonlinearities. T–S adaptive multiple models of the system to be controlled are constructed using different initial estimations for the parameters while one feedback linearisation controller corresponds to each model according to a specified reference model. The controller to be applied is determined at every time instant by the model which best approximates the plant using a switching rule with a suitable performance index. Lyapunov stability theory is used in order to obtain the adaptive law for the multiple models parameters, ensuring the asymptotic stability of the system while a modification in this law keeps the control input away from singularities. Also, by introducing the next best controller logic, we avoid possible infeasibilities in the control signal. Simulation results are presented, indicating the effectiveness and the advantages of the proposed method.     

Reference model selection and adaptive control for induction motordrives

An adaptive model-following speed controller for induction motor drives is proposed and implemented. This adaptive controller is easy to implement since, for the controlled plant, only the output signal is fed back. In order to choose a reference model with the desired drive dynamic behavior, a two-degree-of-freedom (2-DOF) controller is designed, using a systematic procedure based on the prescribed drive specifications. The reference model of the adaptive system is chosen as the transfer function of the controlled drive system by the 2-DOF controller in the nominal case. An adaptation signal is augmented to let the prescribed specifications be maintained under a wide range of operating conditions     

大纯滞后系统的自适应补偿控制

针对工业过程中普遍存在的纯滞后对象的控制问题,提出了一种带误差补偿环节的模型参考自适应控制方法。仿真结果表明,这种自适应控制器对于一类大纯滞后系统的控制具有比较好的控制效果,且结构简单,有一定的鲁棒性。     

Robust adaptive fault tolerant control for a process with actuator faults

This paper studies design and implementation of an enhanced multivariable adaptive control scheme for an uncertain nonlinear process exposed to actuator faults. For adaptive fault compensation, a model reference adaptive control (MRAC) strategy is utilized as main controller. A new adaptation algorithm making possible to improve transient performance of adaptive control is integrated to the controller. With the help of further modifications, some restrictive conditions on multivariable adaptive design are relaxed so that the system requires less plant information. The resulting controller has a simpler structure than the other matrix factorization based controllers. At the final stage of design, a robust adaptive control scheme is obtained with consideration of practical implementation problems such as sensor noises, external disturbances and unmodeled​ system dynamics. It is proved that the controller guarantees closed-loop signal boundedness and asymptotic output tracking. Real-time experiment results acquired from quadruple tank benchmark system are presented in order to exhibit the effectiveness of the proposed scheme.     

大柔性飞行器的自适应姿态控制设计

研究系统存在不确定性的大柔性飞行器的姿态跟踪控制问题.针对高阶大柔性飞行器模型,使用平衡实现方法对其降阶,并通过奇异值对比分析系统降阶前后特性.基于降阶模型,设计LQR-PI控制器作为基线控制器.考虑不确定性,利用李雅普诺夫稳定性理论设计模型参考自适应控制器,并对比两种方法的控制效果.仿真结果显示,所提方案对包含不确定性的系统具有较好的控制效果,能使系统完成期望的姿态跟踪目标.     

基于U-LMS算法的船舶自适应逆控制

自适应逆控制的基本思想就是要用一个来自控制器的信号去驱动对象,而该控制器的传递函数就是参考模型与该对象建模函数的商.按照某一种自适应算法,用对象和指令输入之差的误差信号来调节控制器的参数以使该误差信号的均方差最小.根据IIR算法的快速收敛性,该文设计了基于U-LMS算法的IIR控制器,并把其应用到船舶模型控制上,仿真结果表明这种控制器大大减少了计算量,快速性得到了提高,并且权值的失调较小,对于参考模型的输出具有非常优良的跟踪性能.