Control System Design and Analysis

In this lab students will begin by learning the theory and background, including the necessary equations, behind First Principles Modeling and Experimental Modeling. Then they will implement their knowledge by building a DC motor model, running a VI, and obtaining a waveform graph. From here students can formulate their differential equation and analyze the data with the help of short answer questions. The ultimate goal of modeling for control design is to be able to create a simulation of a plant and various controllers in order to gain confidence that an approach will work before implementation on hardware.

Controlling the speed of a DC motor is one of the most common tasks that automation, robotics, and industrial engineers are called upon to perform when creating industrial systems. In this lab students will learn the fundamentals of qualitative and quantitative PI control design. They will then implement a controller and analyze the data through a series of short calculations and short answer questions. The skills gained in these exercises are directly applicable to a multitude of exciting emerging application areas in engineering.

In this lab students start by studying the theory of quantitative PD control design along with necessary equations. Then students will implement a controller on a DC motor and obtain and analyze response data. Finally, students will asses the steady-state error and answer several short answer questions and calculations.

Balancing an inverted pendulum may seem like a purely academic challenge, but the control algorithm that is used is analogous to a wide variety of real-life problems, from Segway scooters to rockets. In this lab, students will begin by learning the fundamentals of inverted pendulum control, followed by optimal control of an inverted pendulum in section two. They will then apply this knowledge to a hands-on activity using the Quanser Controls Board, perform calculations, and answer free response questions.

This lab covers the basics of stability analysis, including bounded-input bounded-output (BIBO) stability, Nyquist stability analysis, and the Routh Hurwitz coefficient test. Students complete activities in which they apply each approach to a real control system.

Controls theory is generally introduced to students through continuous transfer functions. Strictly speaking, this means that the real-world controllers would be implemented using only analog electronics. In most cases, however, it is not feasible to implement a controller using only analog electronics. Analog electronics are inherently prone to variations in their nominal values, and thus extensive fine-tuning is necessary for each implemented controller using the same nominal electronics. Furthermore, each pure analog circuit will be very susceptible to environmental changes, in particular changes in temperature and humidity. Therefore, most control systems are now being implemented on digital computers, i.e. usually using either a PC/laptop or a microprocessor. In this lab students will investigate the impact of implementing a continuous controller in a digital environment.