High performance control theory, design, and applications

Online virtual labs offer potential for students to participate in laboratory practice without access to physical laboratory equipment. Existing online labs show a tradeoff between extensibility for different systems and interactivity with the user. A Virtual Control Lab that overcomes this hurdle has been developed using LabView. A modular structure that allows a developer to simulate a new system is presented to the user by a system of panels and tabs which provides the user a variety of system analysis and real-time simulation data. Classical PID controllers cannot track a ramp change in a set point or disturbance for most systems. In order to achieve offset-free behavior a controller with an additional integral is required. A double integral controller which could be practically implemented as two standard PI controllers connected in series is suggested. Tuning correlations are developed to minimize the integral of the time-weighted absolute error for tracking of a set point ramp. Model Predictive Control is a common control strategy for industrial multivariable systems; however, it suffers from many of the same offset related problems as proportional control. MPC methods are described which use integral states and input-velocity weights to track steps, and in some cases ramps, without offset, while avoiding the complexity of previous tracking methods based on targets and disturbance estimation. A controller is also proposed to use the property of flatness for control of a swarm of wheeled mobile robots. The controller is augmentented with formation tracking and collision avoidance routines.