飞行控制系统设计.docx

1、飞行控制系统设计(此文档为word格式，下载后您可任意编辑修改！)一、对最简单的角位移系统的评价1、某低速飞机本身具有较好的短周期阻尼，采用这种简单的控制规律是可行的。它的传递函数为：open p3_6 系统根轨迹为：nem1=-12.5;den1=1 12.5;sys1=tf(nem1,den1);nem2=-1 -3.1;den2=1 2.8 3.24 0;sys2=tf(nem2,den2);sys=series(sys1,sys2);rlocus(sys) 随着k的增大，该系统的一对闭环复极点的震荡阻尼逐渐减小。但由于飞机本身的阻尼较大，所以当k增大致1.34时，系统的震荡阻尼比仍有0

2、.6。k增大到6.2时系统才开始不稳定。2、现代高速飞机的短周期运动自然阻尼不足，若仍采用上述单回路控制系统则不能胜任自动控制飞机的要求。open p3_10系统根轨迹为：nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3 0;sys2=tf(nem2,den2);sys=series(sys1,sys2);rlocus(sys) 随着k增大，系统阻尼迅速下降。当k=1.06时，处于临界稳定。所以无法选择合适的k值以满足系统动静态性能。为了使系统在选取较大的k值基础上仍有良好的动态阻尼，引入俯仰角速

3、度反馈。二、具有俯仰角速率反馈的角位移自动驾驶仪参数设计open p3_161、系统内回路根轨迹为：nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);rlocus(sys)按物理概念似乎速率陀螺的作用越强，阻尼效果越显著。但根轨迹分析告诉我们，只有在一定范围内这种概念才是正确的，否则会得到相反的效果。这种现象是由舵回路的惯性造成的。舵回路具有不同时间常数时的内回路根轨迹图：T=0sys1=-1;nem2=-4.3 -

4、4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);rlocus(sys)T=0.1nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);rlocus(sys)T=0.25nem1=-4;den1=1 4;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,d

5、en2);sys=series(sys1,sys2);rlocus(sys)结论：1)、为了确保角稳定回路的性能，不能单纯地增加速率陀螺信号强度，必须同时设法减小舵回路的惯性，使舵回路具有足够宽的通频带。2)、一般舵回路时间常数限制在0.030.1秒内，接近飞机自然频率的5倍。这就是舵回路频带一般比飞行器的频带宽3至5倍的理由。2、角稳定回路的设计系统角稳定回路根轨迹为：nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2

6、);sys=feedback(sys,0);sys3=tf(1,1 0);sys=series(sys,sys3);figurerlocus(sys)hold onnem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,0.4);sys3=tf(1,1 0);sys=series(sys,sys3);rlocus(sys)hold onnem1=-10;den1=1 10;sys1=tf(

7、nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,0.7);sys3=tf(1,1 0);sys=series(sys,sys3);rlocus(sys)hold onnem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,1.3)

8、;sys3=tf(1,1 0);sys=series(sys,sys3);rlocus(sys)hold onnem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,1.56);sys3=tf(1,1 0);sys=series(sys,sys3);rlocus(sys)比较：与的选值关系。=0=0.4=0.7=1.3=1.560.6无0.141.081.9无01.065.28.711.6

9、17.3系统选不同的与值时的阶跃响应图：nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,0);sys3=tf(1,1 0);sys4=tf(1.06);sys=series(sys,sys3);sys=series(sys,sys4);sys13=feedback(sys,1);nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3

10、*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,0.4);sys3=tf(1,1 0);sys4=tf(0.14);sys=series(sys,sys3);sys=series(sys,sys4);sys14=feedback(sys,1);nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=fee

11、dback(sys,0.7);sys3=tf(1,1 0);sys4=tf(1.08);sys=series(sys,sys3);sys=series(sys,sys4);sys12=feedback(sys,1);nem1=-10;den1=1 10;sys1=tf(nem1,den1);nem2=-4.3 -4.3*0.33;den2=1 0.61 3.3;sys2=tf(nem2,den2);sys=series(sys1,sys2);sys=feedback(sys,1.3);sys3=tf(1,1 0);sys4=tf(1.9);sys=series(sys,sys3);sys=se

12、ries(sys,sys4);sys11=feedback(sys,1);step(sys11,sys12,sys13,sys14);3、自动驾驶仪参数与飞机特性的关系：用根轨迹法选择参数时，若要求一定的振荡阻尼比，参数与之间有这样的规律：当所选择的较大时，才能得到较大的值，它们之间的比值存在一定的规律：当参数与选得比较合理时，比值AP=/总是落在飞机短周期运动自然频率d的附近。三、Control Design Using SimulinkThis demonstration illustrates how to use the Control System Toolbox and Simul

13、ink Control Design to interact with Simulink to design a digital pitch control for the U.S. Navys F-14 Tomcat aircraft. In this example, we will design the controller to permit the aircraft to operate at a high angle of attack with minimal pilot workload. Our example takes you through the first pass

14、 at designing a digital autopilot for a high angle of attack controller. To run everything in this demo you must have the Control System Toolbox, Simulink Control Design, Simulink, and Real-Time Workshop. If you dont have all of these products, you can still run portions of the demo using cell execu

15、tion mode of the MATLAB editor. Below is a Simulink model of the F-14. The control systems in the Controllers block can be switched in the model to allow you to see the analog response and then to switch to a design created using the Control System Toolboxs Linear Time Invariant (LTI) objects. A con

16、troller is also included that is a discrete implementation of the analog design that is similar to the algorithm that would go into an on-board flight computer. Take a few moments to explore the model. Open the f14_digital modelf14dat_digital;f14_digitalsim(f14_digital);Figure 1: Simulink model of t

17、he F-14 flight control system. Trim and LinearizationThe model can be linearized in the Control and Estimation Tools Manager launched from f14autopilot Simulink model. In the Tools menu, select Control Design Linear Analysis. When the Control and Estimation Tools Manager opens, select an operating p

18、oint and click the Linearize Model button. An LTI Viewer can be created showing a step plot of the linearization. To browse around the LTI Viewer, right click on the graph window to see your options. For help type help slcontrol or help ltiview or look at the Control System Toolbox and Simulink Cont

19、rol Design product documentation.Open the f14autopilot modelapmdl = f14autopilot;open_system(apmdl)op = operpoint(apmdl);io = getlinio(apmdl);contap = linearize(apmdl,op,io) a = Alpha-sensor Pitch Rate L Proportional Stick Prefil Alpha-sensor -2.526 0 0 0 Pitch Rate L 0 -4.144 0 0 Proportional -1.71

20、 0.9567 0 10 Stick Prefil 0 0 0 -10 b = Stick (pt. 1 Alpha Sensed q Sensed (pt Alpha-sensor 0 1 0 Pitch Rate L 0 0 1 Proportional 0 0 -0.8156 Stick Prefil 1 0 0 c = Alpha-sensor Pitch Rate L Proportional Stick Prefil Sum (pt. 1) 2.986 -1.67 -3.864 -17.46 d = Stick (pt. 1 Alpha Sensed q Sensed (pt Su

21、m (pt. 1) 0 0 1.424 Continuous-time model.Figure 2: Original analog autopilot. Linear Time-Invariant (LTI) SystemsThere are three types of LTI objects you can use to develop a linear model:State Space (SS), Transfer Function (TF), and Zero-Pole-Gain (ZPG) objects.The variable contap is a State Space

22、 object. You can then get one of the other types with the other commands. When you create the object in MATLAB, you can manipulate it using operations such as *, +, -, etc. This is called overloading the MATLAB operators. Try creating an object of your own and see what happens when adding, multiplyi

23、ng, etc. with the contap object. To see exactly what is stored in the LTI object, type get(contap) or contap.InputName for example.contap = tf(contap);contap = zpk(contap) Zero/pole/gain from input Stick (pt. 1) to output Sum (pt. 1):-17.46 (s+2.213) s (s+10) Zero/pole/gain from input Alpha Sensed (

24、pt. 1) to output Sum (pt. 1):2.9857 (s+2.213) s (s+2.526) Zero/pole/gain from input q Sensed (pt. 1) to output Sum (pt. 1):1.424 (s+2.971) (s+2.213) s (s+4.144) Discretized Controller Using Zero-Order HoldNow the LTI object will be used to design the digital autopilot that will replace the analog au

25、topilot. The analog system is coded into the LTI object called contap (CONtinuous AutoPilot). The first attempt at creating a digital autopilot will use a zero-order hold with a sample time of 0.1 seconds. Note that the discrete object maintains the type (ss, tf, or zpk). It is clear from Bode plot

26、below that the systems do not match in phase from 3 rad/sec to the half sample frequency (the vertical black line) for the pilot stick input and the angle of attack sensor. This design has poorer response than the analog system. Go to the Simulink model and start the simulation (make sure you can se

27、e the scope windows). While the simulation is running, double-click the manual switch labeled Analog or Digital. Does the simulation verify the conclusion reached by interpreting the Bode diagram?discap = c2d(contap, 0.1, zoh);get(discap)bode(contap,discap) z: 1x3 cell p: 1x3 cell k: -1.25 0.294 1.4

28、2 ioDelay: 0 0 0 DisplayFormat: roots Variable: z Ts: 0.1 InputDelay: 3x1 double OutputDelay: 0 InputName: 3x1 cell OutputName: Sum (pt. 1) InputGroup: 1x1 struct OutputGroup: 1x1 struct Name: Notes: UserData: Figure 3: Bode diagram comparing analog and ZOH controllers. Tustin (Bilinear) Discretizat

29、ionNow try different conversion techniques. You can use the Tustin transformation. In the command window type the commands above.It should be clear that the systems still do not match in phase from 3 rad/sec to the half sample frequency, the Tustin transformation does better. The simulation uses the

30、 LTI object as it is designed. To see how the object is used look in the Controllers subsystem by using the browser or by double clicking the icon. The LTI block picks up an LTI object from the workspace. You can change the object name used in the block to any LTI object in the workspace. Try using discap1, the Tustin discretization of the analog design: discap1 = c2d(contap,0.1,tustin);bode(contap,discap,discap1)Figure 4: Bode diagram comparing analo