Lecture Signals, systems & inference – Lecture 5: State-space models, equilibrium, linearization

Lecture Signals, systems & inference – Lecture 5: State-space models, equilibrium, linearization. The following will be discussed in this chapter: State variables are (relevant) “memory” variables, defining properties of CT state-space models and the governing equations, linearization at an equilibrium yields an LTI model,. | Lecture Signals, systems & inference – Lecture 5: State-space models, equilibrium, linearization State-Space Models, Equilibrium, Linearization , Spring 2018 Lec 5 1 State variables are (relevant) “memory” variables In physical systems, the natural state variables are typically related to energy storage mechanisms: capacitor voltages or charges, inductor currents or fluxes, positions and velocities of masses, 2 Defining properties of CT state-space models ⇣ ⌘ q˙ (t) = f q(t), x(t), t ⇣ ⌘ y(t) = g q(t), x(t), t •  State evolution property •  Instantaneous output property 3 Numerical solution of CT state-space model . qi(t0) qi(t0) qi(t) t t0 + ¢ 4 t0 Integrator-adder-gain system x(t) . . q2(t) q2(t) q1(t) q1(t) y(t) -1 + • • -2 8 5 Mechanistic model for capnography 6 and the governing equations V (t) LV¨ (t) + RV˙ (t) + = P C pD (t) + pA ˙ p˙D (t) = V (t) , V˙ (t) > 0 VD pD (t) ˙ p˙D (t) = V (t) , V˙ (t) < 0 VD 7 Equilibrium For a time-invariant nonlinear system with a constant input, an initial state that the system remains at: DT : ¯ = f (q q ¯, x ¯) CT : ¯, x 0 = f (q ¯) 8 Linearization at an equilibrium yields an LTI model e , x[n] = x¯ + x[n] ¯ + q[n] DT case: q[n] = q e , q[n + 1] = f (q[n], x[n]) # h @f i h @f i e + 1] ⇡ q[n e + q[n] e x[n] @q ¯ ¯ q,x @x ¯ ¯ q,x e for small perturbations q[n] e and x[n] from equilibrium 9 Linearization at an equilibrium yields an LTI model e , x(t) = x¯ + x(t) ¯ + q(t) CT case: q(t) = q e , q˙ (t) = f (q(t), x(t)) # h @f i h @f i e˙ q(t) ⇡ e + q(t) e x(t) @q ¯ ¯ q,x @x ¯ ¯ q,x e for small perturbations q(t) e and x(t) from equilibrium 10 MIT OpenCourseWare Signals, Systems and Inference Spring 2018 For information about citing these materials or our Terms of Use, visit: . 11

Không thể tạo bản xem trước, hãy bấm tải xuống
TÀI LIỆU MỚI ĐĂNG
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.