Chapter 3 mathematical Modeling of Dynamic Systems Modeling Mathematical models are developed from: physical laws chemical laws biological laws economic laws etc Mathematical models take the form of: differential.
Download ReportTranscript Chapter 3 mathematical Modeling of Dynamic Systems Modeling Mathematical models are developed from: physical laws chemical laws biological laws economic laws etc Mathematical models take the form of: differential.
Chapter 3 mathematical Modeling of Dynamic Systems Modeling Mathematical models are developed from: physical laws chemical laws biological laws economic laws etc Mathematical models take the form of: differential equations transfer functions state equations block diagrams signal flow graphs etc Mathematical models are used to analyze dynamic characteristics and to design control systems Models Simplicity vs Accuracy lumped vs distributed parameter models linear vs nonlinear models time-invariant vs time varying models As simple as possible with the required accuracy Transfer Function and Impulse-Response Function Transfer Function Convolution Integral Impulse-Response Function Convolution Integral Y ( s ) G ( s ) R( s ) y(t ) t y(t ) ? ILT convolution g (t )r ( )d 0 t 0 g ( )r (t )d Multiplication in the frequency domain corresponds to convolution in the time domain Convolution Laplace Transformation Time domain functions g(t), r(t) Frequency Domain functions, G(s), R(s) Time domain convolution Frequency domain product Time domain y(t)=conv(g(t),r(t)) Frequency domain Y(s)=G(s)R(s) Inverse Laplace Transform Impulse Response Function The response of a differential equation to an impulse (delta function) input is the Impulse Response Function of that differential equation. Y (s) G(s) R(s) For an impulse input r (t ) (t ) R(s) 1 The Laplace transform of the impulse response is Y (s) G(s)1 G ( s ) = transfer function The impulse response is the inverse Laplace transform of the transfer function g (t ) Impulse Response, Convolution, and solution to DEs The output of a system due to the input r(t) is the convolution of the input function and the impulse response of the system. y(t) = conv(g(t),r(t)) There is an intimate relationship between the impulse response of a system and the response of the system to any other input. Automatic Control Systems Block Diagrams Signals Blocks and Transfer functions Summing point Branch point Block diagram of a closed loop system Open-loop transfer function and feedforward transfer function Closed-loop transfer function Automatic Controllers Industrial Controllers On-off, P, I, PI, PD, PID Disturbances Block diagram reduction Start by doing what’s necessary, then what’s possible, and suddenly you are doing the impossible. -St. Francis of Assisi Modeling review Mechanical systems Electrical systems I hope to come back to this topic later Skip 3-5, 3-9, 3-10 x(t ) 1 x(t ) kr (t ) x(t ) 2n x(t ) n2 x(t ) kr (t ) Mechanical examples? Electrical examples? Thermal examples? Transfer function? Time constant Mechanical examples? Electrical examples? Thermal examples? Transfer function? Undamped natural frequency damping ratio Transfer function Input signal r (t ) Output signal y(t ) Transfer function Y ( s) G( s ) R ( s ) i .c . s 0 Block diagram R(s) Equation Y (s) G(s) R(s) G(s) Y(s) Block Diagram reduction L(s) R(s) GR(s) + E(s) C(s) U(s) G1(s) + + Y(s) G2(s) + + H(s) T ? Y /N ? Y /L? E/RS ? N(s) GR ( s ) 1 H (s) 1 G1 ( s ) a /( s b) Open loop TF? Feedforward TF? Closed loop TF? G2 ( s ) K /( Ms Bs ) 2 Steady-State Error E ( s ) Y ( s ) R( s ) or E ( s) H ( s)Y ( s) GR ( s) R( s) Steady-state means the output looks like the input. Step inputs produce step (constant) outputs Sinusoidal inputs produce sinusoidal outputs Ramp inputs produce ramp outputs X inputs produce X outputs Steady-state means that the transients have died out. The output has (at least) two terms, steady-state (mathematically looks like the input) transient (decays to zero) sometimes other terms (normally a bad situation) Computing SS error steady state error ess lim e(t ) t To compute E(s): •inverse Laplace transform to get e(t) •take limit as t goes to infinity. •Steady state error only exists if the limit exists. Chapter 3 Problems A 1-5 6-10, 12,13 11 14-18 19-22 23 24-26 B 1-8 9 10-12 13-18 19-24 25 26-27 Comments Block diagram reduction State space State space to transfer function Mechanical models Electrical models Electro mechanical model Signal flow graph 27 28-29 linearization Assignments Ungraded homework: A1-5 Graded homework: B1-7 Test 1: Solving DEs via Laplace transforms, Block diagrams. Laplace transforms definition 2 formulas for functions derivatives Euler’s identities ALGEBRA CALCULUS Complex numbers/algebra