Training Package 1: Robust Control and PID
Robust control is needed in every industrial application from power train control to process control. While most applications have PID controls, most of the literature handles uncertainty via advanced controls such as sliding mode, MPC or adaptive control. Uncertainty and nonlinearity are rarely explicitly discussed in industrial applications especially when the controller in hand is PID.
In this training, we will cover the concept of uncertainty, part to par variability and nonlinearity. Robust PID control design and tuning that handles these issues will be discussed in details. The tradeoff between performance and stability will be shown. Simulation tools such as system identification and Monte-Carlo simulations will be discussed as means of validating the control design.
A hardware will be provided with Arduino-based controller. The hardware will serve as a test bed for the trainees. The development environment for the controller will be Matlab/Simulink. Furthermore, a nonlinear plant model will be provided to allow the trainees to extrapolate their learnings on the simple hardware to complex problems.
Training Package 2: Introduction to MPC Control
With the increased computing power on every machine, real time deployment of this computationally extensive control technique is feasible. This control technique is heavily underutilized in fast applications (where decisions need to be made in order of seconds). The main reason is usually the legacy process of control deployment.
In this 3-day training, we will cover the streamlined process of designing, tuning and deploying MPC. A hardware will be provided with Arduino-based controller. The hardware will serve as a test bed for the trainees.
The development environment for the controller will be Matlab/Simulink. Furthermore, a nonlinear plant model will be provided to allow the trainees to extrapolate their learnings on the simple hardware to complex problems.
A hardware will be provided with Arduino-based controller. The hardware will serve as a test bed for the trainees. The development environment for the controller will be Matlab/Simulink. Furthermore, a nonlinear plant model will be provided to allow the trainees to extrapolate their learnings on the simple hardware to complex problems.