PPT-Lecture 9 : Structure for Discrete-Time System

Xiliang Luo 201411 1 Block Diagram Adder Multiplier Memory Coefficient 2 Example 3 General Case 4 Direct Form 1 Rearrangement 5 Rearrangement 6 Zeros 1 st Poles 1 st Canonic Form. Before discussing the stability test let us rst introduce the following notions of stabilit y for a linear time invariant LTI system 1 BIBO stability or zero state stbaility 2 Internal stability or zero input stability Since we have not introduced t The main objective of a control system is to design a controller either in forward or in feedback path so that the closed loop system is stable with some desired performance Two mos t popular design techniques for continuous time LTI systems are usi Dr. Feng Gu. Way to study a system. . Cited from Simulation, Modeling & Analysis (3/e) by Law and . Kelton. , 2000, p. 4, Figure 1.1. Model taxonomy. Modeling formalisms and their simulators . Discrete time model and their simulators . 5.1 Discrete-time Fourier Transform . Representation for discrete-time signals. Chapters 3, 4, 5. Chap. 3 . Periodic. Fourier Series. Chap. 4 . Aperiodic . Fourier Transform . Chap. 5 . Aperiodic . Advanced Mechanical Design. December 2008. Shaghayegh. . Kazemlou. Advisor. : . Dr. . Shahab. . Mehraeen. Louisiana State University. Part I: Grid-connected Renewable System. Part II: . Converter D. Example. The representation of discrete-time signals in terms of impulse. Convolution. The representation of continuous-time signals in terms of impulse. Properties of LIT systems. Commutative property. Dr. . Feng Gu. Weather Prediction Example. Possible models to predict the weather tomorrow. . 1. Mystery-based models . (e.g., whenever my right eyelid twitches, it is going to rain tomorrow) . 24 May 2018. Veton Këpuska. 2. Introduction. Review of the foundation of discrete-time signal processing:. Investigation of essential discrete-time methods. Briefly touch upon the limitations of these techniques in the context of speech processing:. Announcements:. HW . 4. . posted, . due Tues May 8 at 4:30pm. . No late HWs as solutions will be available immediately.. Midterm details on next page. HW . 5 will . be posted . Fri May 11. , . due . Lecture . 6. (Structures for discrete-time systems). Husheng. Li, UTK-EECS, Fall 2012. Purpose of this chapter. Study how to implement the LTI discrete-time systems.. We first present the block diagram and signal flow graph.. Equations. Outline. • Discrete-time state equation from . solution of . continuous-time state equation.. • Expressions in terms of . constituent matrices. .. • Example.. 2. Solution of State Equation. MatLab. 2. nd. Edition. Lecture 11:. Lessons Learned from the Fourier Transform. . Lecture 01. . Using . MatLab. Lecture 02 Looking At Data. Lecture 03 Probability and Measurement Error. Lecture 04 Multivariate Distributions. Chapter 5. Discrete-Time Process Models. Discrete-Time Transfer Functions. The input to the continuous-time system . G. (. s. ) is the signal:. The system response is given by the convolution integral:. Chapter 5. Discrete-Time Process Models. Discrete-Time Transfer Functions. The input to the continuous-time system . G. (. s. ) is the signal:. The system response is given by the convolution integral:.