基于Simulink的空调系统先进自校正控制仿真研究

空调系统可以被看作是一阶惯性加延迟的过程,系统具有时延和参数时变的特性.提出了一种先进的自校正控制策略并将其应用在空调系统中.该控制策略采用了一种混合的参数辨识算法,在控制系统闭环运行条件下,空调系统的过程参数包括延迟时间可以被在线辨识.辨识出的延迟时间被Smith预估器用来补偿控制回路中的时延,同时该控制策略的控制信号可由内环回路中的PI控制器根据ITAE整定规则计算获得.Simulink仿真结果表明该自校正控制策略较自适应PI控制的控制性能更为优越.     

自相关过程能力分析方法

针对平稳自相关过程,提出了一种过程能力分析方法。该方法利用统计过程控制(statistical processcontrol,SPC)与工程过程控制(engineering process control,EPC)的整合来消除数据的自相关性并判断过程稳态,应用回归和方差分析估计过程均值和方差。给出了该方法的具体步骤,通过一个实例验证了该方法的有效性。     

一种改进的自适应模糊滑模大包线飞行控制方法

提出了一种改进的自适应模糊滑模大包线飞行控制方法。该方法以经模拟退火粒子群算法优化的小波神经网络实现非线性模型的逆,能够更加细致地逼近非线性模型,并针对自适应控制的鲁棒性与瞬态性能差的缺点,将滑模控制与自适应控制相结合共同补偿逆误差,提高了自适应控制的鲁棒性与瞬态性。仿真结果表明:所设计的自适应模糊滑模大包线飞行控制器具有优良的控制性能。     

Adaptive integral dynamic surface control based on fully tuned radial basis function neural network

An adaptive integral dynamic surface control approach based on fully tuned radial basis function neural network (FTRBFNN) is presented for a general class of strict-feedback nonlinear systems, which may possess a wide class of uncertainties that are not linearly parameterized and do not have any prior knowledge of the bounding functions. FTRBFNN is employed to approximate the uncertainty online, and a systematic framework for adaptive controller design is given by dynamic surface control. The control algorithm has two outstanding features, namely, the neural network regulates the weights, width and center of Gaussian function simultaneously, which ensures the control system has perfect ability of restraining different unknown uncertainties and the integral term of tracking error introduced in the control law can eliminate the static error of the closed loop system effectively. As a result, high control precision can be achieved. All signals in the closed loop system can be guaranteed bounded by Lyapunov approach. Finally, simulation results demonstrate the validity of the control approach.     

Output feedback based adaptive robust fault-tolerant control for a class of uncertain nonlinear systems

An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed. The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors. Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault, and robust control based designs can achieve guaranteed transient response. However, neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults. In the present work, an adaptive robust fault-tolerant control scheme is claimed to solve both the problems, as it seamlessly integrates adaptive and robust control design techniques. Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.     

Adaptive fuzzy sliding mode control for robotic airship with model uncertainty and external disturbance

An adaptive fuzzy sliding mode control (AFSMC) approach is proposed for a robotic airship.First,the mathematical model of an airship is derived in the form of a nonlinear control system.Second,an AFSMC approach is proposed to design the attitude control system of airship,and the global stability of the closed-loop system is proved by using the Lyapunov stability theorem.Finally,simulation results verify the effectiveness and robustness of the proposed control approach in the presence of model uncertainties and external disturbances.     

基于T-K控制图的多品种生产模式统计过程控制方法

根据SPC基本原理, 传统的统计过程控制技术无法直接用于多品种生产环境的质量监控. 提出了一种新颖的统计过程控制方法, 对工艺参数均值及标准偏差监控, 仅需一张控制图即可对多品种生产过程的运行状态做出评价. 详细给出了T、K统计量的定义和计算方式及T-K控制图控制限的确定. 理论分析表明, T-K控制图具有稳定的监控性能且具有self-starting特点. 通过实例分析及仿真验证, 证实该过程控制方法能够及时、有效地检测出多品种生产模式下导致生产过程失控的异常因素, 提示操作人员适时做出响应, 使生产过程维持在统计受控状态以保证产品质量.     

严格区域稳定的模型参考自适应控制器设计

针对模型参考自适应控制的区域稳定性问题,采用Lyapunov直接法分析参数收敛与系统跟踪误差之间的关系。通过对系统误差项与参数估计项之间能量转移过程的描述,说明常规的区域稳定自适应控制器尚未充分考虑因估计参数振荡引起系统失稳的可能性。为此,提出一种简洁有效的区域稳定控制器设计方案,根据系统跟踪误差大小动态引入增益动态调整的鲁棒控制项,有效消除了控制中潜在的不稳定因素。基于SISO非线性系统的仿真研究验证了所提方案的有效性。     

Decentralized model reference adaptive sliding mode control based on fuzzy model

1.INTRODUCTIONIn recent years,decentralized control of interconnect-ed systems has become an i mportant and challengingtopic[1~3].However,it is usually difficult to modelthe systemexactly due to the complex real environ-ment.In the past several years,active research hasbeen carried out in controller design based on univer-sal approxi mators,such as fuzzy control and neuralnetwork control[4~6].For a class of SISO nonlinearsystems,adaptive fuzzy control approaches were pro-posed based on …     

Adaptive functional link network control of near-space vehicles with dynamical uncertainties

The control law design for a near-space hypersonic vehicle (NHV) is highly challenging due to its inherent nonlinearity, plant uncertainties and sensitivity to disturbances. This paper presents a novel functional link network (FLN) control method for an NHV with dynamical thrust and parameter uncertainties. The approach devises a new partially-feedback-functional-link-network (PFFLN) adaptive law and combines it with the nonlinear generalized predictive control (NGPC) algorithm. The PFFLN is employed for approximating uncertainties in flight. Its weights are online tuned based on Lyapunov stability theorem for the first time. The learning process does not need any offline training phase. Additionally, a robust controller with an adaptive gain is designed to offset the approximation error. Finally, simulation results show a satisfactory performance for the NHV attitude tracking, and also illustrate the controller's robustness.     

时滞大系统的模型参考鲁棒自适应分散控制

基于Lyapunov-Krasovskii (L-K) 泛函方法,结合线性矩阵不等式（linear matrix inequality, LMI）技术以及自适应控制方法,研究了一类不确定时变时滞大系统的模型参考跟踪控制问题,提出了一种鲁棒自适应分散控制器设计方法。时滞无关的控制器设计无需模型参考跟踪控制中苛刻的模型匹配条件且局部状态反馈增益以LMI 形式给出,便于计算机求解和参数优化。为避免控制过程中的自适应参数持续增长问题,提出了死区自适应算法。最后以仿真实例表明了所提方法的正确性与有效性。     

直接力导弹的模型参考自适应滑模控制器设计

针对导弹直接力/气动力复合控制的特点,提出了一种基于参考模型的自适应滑模控制方案.该设计方法针对系统所存在的不确定性,在滑模控制中引入了自适应参数调节律和模糊控制规则,采用自适应律逼近模型摄动和外界干扰的上界,采用模糊调节律有效减弱了一般变结构控制系统的抖颤问题,既进一步增强了系统的鲁棒性,又提高了自适应参数收敛过程中的跟踪精度.仿真结果表明,所提出的控制方案对机动指令具有较好的跟踪效果,适用于直接力/气动力复合控制导弹的控制系统设计.     

Variation Analysis and Stability Control for Measurement Process

1　IntroductionDuring production processes and in scientific experiments,we often collectdata in order toanalyze and improve processes and experiments.For example,data obtained from a manu-facturing process can be used to improve productquality and to modify the production pro-cess.Since the data are obtained from the measurement process,the measured data mightnot reflect the true status of the production process if errors caused by the measurementprocess are not small enough compared with the…     

STATE-FEEDBACK ADAPTIVE STABILIZING CONTROL DESIGN FOR A CLASS OF HIGH-ORDER NONLINEAR SYSTEMS WITH UNKNOWN CONTROL COEFFICIENTS

In this paper, a new approach is successfully addressed to design the state-feedback adaptive stabilizing control law for a class of high-order nonlinear systems in triangular form and with unknown and nonidentical control coefficients, whose stabilizing control has been investigated recently under the knowledge that the lower bounds of the control coefficients are exactly known. In the present paper, without any knowledge of the lower bounds of the control coefficients, based on the adaptive technique and appropriately choosing design parameters, we give the recursive design procedure of the stabilizing control law by utilizing the approach of adding a power integrator together with tuning functions. The state-feedback adaptive control law designed not only preserves the equilibrium at the origin, but also guarantees the global asymptotic stability of the closed-loop states and the uniform boundedness of all the other closed-loop signals.     

直接鲁棒自适应模糊控制

针对一类不确定非线性系统 ,基于监督控制方案并利用第二类模糊系统的逼近能力 ,提出了一种直接鲁棒自适应模糊控制器设计的新方案。该方案通过引入最优逼近误差的自适应补偿项来消除建模误差的影响 ,从而在稳定性分析中取消了要求逼近误差平方可积或逼近误差的上确界已知的条件。理论分析证明了闭环控制系统是全局稳定的 ,跟踪误差收敛到零。仿真结果表明了该方法的有效性。     

基于RCMAC干扰观测器的高超声速飞行控制

利用自回归小脑模型神经网络(recurrent cerebella model neural network, RCMAC)良好的非线性逼近能力和自学习能力,结合反馈线性化和反演控制方法,提出了一种自适应非线性控制策略,用于高速再入飞行器控制系统的设计。该方案将RCMAC干扰观测器(recurrent cerebella disturbance observer, RCDO)用于估计系统模型的不确定项,同时采用反演控制方式设计伪线性控制项,并利用符号函数逼近误差的上界,根据Lyapunov稳定性理论设计了权值更新规则,保证闭环系统信号有界。高速再入飞行器的六自由度仿真结果验证了方法的有效性和鲁棒性。     

Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead-zone

The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors are adopted to minimize the inuence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.     

基于有限自动机的模式匹配算法及其应用研究

针对质量统计过程控制（SPC）中的异常模式快速匹配问题,提出了基于确定有限自动机（DFA）的模式匹配算法,给出了能利用DFA进行匹配的基于多维输入数据的模式串定义.在分析常规质量控制图中的八种异常模式的基础上,给出了基于DFA的模式串匹配算法.该算法在企业计算机辅助质量控制系统（CAQCS）中得到了成功的应用, 表明它适于解决SPC中的异常模式的匹配问题, 且有简单、快速和准确的特点.     

增益符号未知的鲁棒自适应模糊控制

针对一类具有函数控制增益符号未知的不确定非线性系统,根据滑模控制原理和模糊系统的逼近能力,提出了一种自适应模糊控制器设计新方案。该方案利用Nussbaum函数的性质,取消了常用的函数控制增益符号已知这一条件。并通过引入最优逼近误差的自适应补偿项来消除建模误差和参数估计误差的影响。理论分析证明了闭环系统的有界性和跟踪误差收敛到零。仿真结果表明了该方法的有效性。     

基于遗传预估策略的智能主动队列管理

针对TCP传输过程中的典型时滞特性,提出了一种智能主动队列管理算法.该算法以自学习预估机制模型为核心来克服大时滞特征对网络稳定性能的影响,拥塞控制系统以两条信息通道分别实现模型补偿和预测控制功能.模型补偿通道采用了Smith预估嚣实现对网络时滞特征的动态补偿,并进一步设计迭代进化算法实现对Smith预估模型未建模特征的估计过程.预测控制通道采用基于神经网络的PID智能丢弃算法,通过神经网络的学习预测功能自适应调整预测控制通道的控制行为.通过仿真研究表明了提出的控制方法显著提高了拥塞控制机制的稳定性能和自适应性能.