Presentation on theme: "EE357 Control System I - Lec B2 (2010W) - Introduction."— Presentation transcript:
EE357 Control System I - Lec B2 (2010W) - Introduction
Outline What is a control system? Open-loop control vs. Closed-loop (feedback) control Development of control theory A brief overview of EE357
What is a control system? A general definition: “A control system is a device or set of devices to manage, command, direct or regulate the behavior of other devices or systems.” A control (feedback) loop, including sensors, control algorithms and actuators, is arranged in such a fashion as to try to regulate a variable at a set point or reference value.
What is a control system? Plant/process - object to be controlled Controllers - devices that compute and generate control signals/actions Actuators - devices that perform control actions Sensors - devices that measure the output Control objectives - tasks, targets of control A typical (feedback) control system contains
Open-loop Control The controller does not use measurement of system output being controlled when computing the control action, i.e. no feedback processcontroller command input control action output Fig. 1. A block diagram representation of an open loop control sensor
Closed-loop Control Also called feedback control, the controlled system output is measured and being used for computing the control action. controllerprocess sensor - command input error control action output Fig. 2. A block diagram representation of a closed-loop control actuator
Example 1. Room Temperature Control Open-loop scheme: –no measurement for feedback –fixed control action –can’t adjust to unexpected changes from the system environment roomfurnace Switch (on/off) inlet vent heat temperature
Example 1. Room Temperature Control Closed-loop scheme –thermostat: sensing plus control device – automatically adjust room temperature – can easily change room temp. as desired furnaceroom room temp. thermostat desired temp. inlet heat heat variation
Example 1. Room Temperature Control Fig. 3. Response of closed-loop room temp. control (ref. EE4629 notes, A. Lynch, 2006)
Example 2: Car Cruise Control Control mechanism: compute the difference between the set speed and the actual speed; then open throttle according to the quantity of error Engine Car body speed Control unit desired speed Road grade speedometer Fig. 4. Bock diagram of closed-loop car speed control
Example 3: Human Balance System ankle, hip, foot body position (com) brain perturbation Sensors: eye, inner ear balance sys. & legs (pressure) Fig. 5. Block diagram of human balance control
Example 3: Human Balance System Analogy of human balance control: –ankle, hip strategy: similar to inverted pendulum –step strategy: similar to inverted pendulum on a cart
Application and Theory Control systems and feedback control concepts are everywhere: daily life, manufacture plant, aerospace industry, automotive industry, chemical, biomedical processes … … The subject of control is multidisciplinary: engineering, mathematics, computer science, etc.
History: Primitive Phase Float valve feedback regulator for water clock –time is determined by the outlet flow rate, which is determined by liquid level –liquid level is regulated by the float valve –sensing and actuation functions are integrated in the float valve mechanism (Ref. Dorf, 10th.)
History: Primitive Phase Flyball Governor (Watt 1788) –Mile stone for industry revolution –Flyball feedback mechanism for the regulation of steam engine speed –Sensing and actuation are integrated in one mechanism (Ref. Dorf, 10th.)
History: Classical Phase Analysis based on mathematical modeling –Analysis of Flyball governor based on nonlinear differential equations (Maxwell 1868) Stability notions, stabilization –nonlinear stability (Lyapunov, 1890) –gyroscope/autopilot (Sperry, 1910) PID control (Minorsky, 1922)
History: Classical Phase Frequency domain methods for analysis and design –Nyquist plot, Bode diagram, feedback amplifier (Black, Bode, Nyquist at Bell lab) (1930’s - 50’s) Key classical control methods –Routh-Hurwitz stability criterion, root locus, frequency response methods, Nyquist criterion –Graphical and hand computation –Suitable for SISO and low order systems
History: Modern Phase (1960 -) Computer controlled system State space modeling (based design) Optimal control, Kalman filter Communication systems, network based, distributed control systems (DCS)… Modern control uses state space modeling and can deal with MIMO and high order systems
Related Issues in Control System Modeling: obtain mathematical models Analysis: stability, time-domain specifications Design: specify the structure and parameters of a controller to achieve the desired performance specifications Implementation: analog filters, digital controllers, micro-controllers, PLC, DCS, etc.
EE 357 Classical control methods and theories are covered in EE357, the first control course for EE students –Modeling: o.d.e, transfer function –Analysis: stability criteria, time-domain and frequency-domain system specification –Design: classical design tools based on several important system charts and plots Modern control is covered in EE460 and EE461.
Your consent to our cookies if you continue to use this website.