This course discusses many fundamental concepts associated with classical feedback control theory. Feedback control measures the state of a physical system or device with a sensing system. The measured state is fed-back and compared to a desired state and the error used by a controller to reduce the difference between the actual and desired states. An example of a feedback control system is the central heating and air conditioning system for a home, or building. A thermostat or temperature sensor is the feedback sensor that measures the room temperature and compares it to the desired temperature or set point, calculating a difference or error. If the temperature is less than the set point, the error is used by the controller to force more heat into the room. When the set point is reached, the error is zero or below an error threshold and the controller will stop heating the room. Another example is the speed control in most of today's automobiles. The speed of the vehicle is measured and compared to a desired speed. Based on the difference between actual speed and the set point, acceleration or braking is applied to the automobile drive to null the error and maintain the desired speed.
Classical control deals directly with the differential equations that describe the dynamics of a plant or process. These equations are transformed into frequency dependent transfer functions. The transfer function is the ratio of two frequency dependent polynomials whose roots describe the response of the plant in a frequency domain. The controller or compensator shapes the closed feedback loop response, given the plant response, to achieve the control performance objectives. Classical feedback control design and analysis tends to require a good foundation in mathematics, however the purpose of this course is not to dwell on the math, although examples are provided, but to provide the basic design and analysis concepts.
The topics covered begin with a description of the basic block diagram in section 2. The relationships between time and frequency domain representations of the block diagram elements are discussed in section 3 followed by the key feedback relationships derived from the block diagram algebra in section 4. Control loop stability and methods to determine stability margins are described in section 5 followed by a discussion of specifying control loop performance in section 6. A couple of control loop design methods are provided in section 7. The basic theory is then applied to two examples; a home heating system in section 8 and motion control applications in section 9. Converting to a digital sample data controller is discussed in section 10; as related to the motion control example in section 9.