Model Uncertain Prior analysis assumed a perfect model. What if the model is in correct= actual system dynamics GA(s)are in one of the sets Multiplicative model G,(s=GN(s(1+E(s)) Additive model Gp(S)=GN(S)+E(s) where

Statistical approach to estimation Examine the multivariate Gaussian distribution: (x-)\v-(x-) Multivariant f(x)= Minimize (x-u)'v(x-u) gives largest probability density By minimizing the argument of the exponential in the probability density function, we maximize the likelihood of the estimates(MLE)

16.31 Feedback Control State-Space Systems What are state-space models? Why should we use them? and how do we develop a state-space mode( &ased in classical control design How are they related to the transfer functions What are the basic properties of a state-space model, and how do we analyze these?

Goal: Design a controller K(s so that the system has some desired characteristics. Typical objectives Stabilize the system( Stabilization) Regulate the system about some design point(Regulation Follow a given class of command signals(Tracking) Reduce the response to disturbances(Disturbance Rejection Typically think of closed-loop control > so we would analyze the

MG!∈R- ORDER5)sT6As RREL丹T(0sHP5 BETWEEN1MER6soN5毛 TAST∈P兵 ND THE POLE LOCAT(0NS心EK ALCULATE0 FoR A SECOND-ORDER SYSTEM GuES60工 NSIGHTS AcTuALLy Gooo APPRoXIMATIONS foR MAwy HIGHER- ORDER SYSTEMS BECAUSE THEIR

3.1 引言 3.2 一阶系统的时域分析 3.3 二阶系统的时域分析

3.1 引言 3.2 一阶系统的时域分析 3.3 二阶系统的时域分析

3.5 线形定常系统的稳定性 3.6 线性系统的稳态误差计算

3.3.1 二阶系统的数学模型 3.3.2 二阶系统的单位阶跃响应 3.3.3 二阶系统阶跃响应的性能指标

4.1 操纵系统的特性 4.2 现代高速飞机稳定性和操纵性的基本特点与操纵系统设计 4.3 飞机主动控制技术 4.4 电传操纵系统 4.5 综合飞行控制系统