Title: Advanced Control Theories
Course: 2016FA-MCO-110-401 > Section: Module 5: Control Theory

Click here for a downloadable version of this document:(EXTERNAL) Advanced Control Theories

Model Predictive Control (MPC)

Model Predictive Control aka Multivariable Predictive Control (MPC) is a control theory using a mathematical representation of the process to anticipate required changes in system output that is updated in real time. In MPC control multiple process measurements are used and various outputs are all controlled at the same time by executing a process model. Some MPC controllers are capable of adaptive functions similar to a feedback tool.

Statistical Process Control (SPC)

Statistical Process Control (SPC) is when statistics are used to control a process. It is usually used with an open loop control system and often happens after a statistical quality control (SQC) analysis. In other words, feedback in this system comes in the form of statistics gained from analysis [3].

Intelligent Control

The use of control techniques that utilize artificial intelligence and computing approaches is known as intelligent Control. In other words, intelligent control involves both control theory and intelligence [8].

Fuzzy Logic

Fuzzy logic is the term that describes logic allowing for ambiguous or imprecise answers to questions. Fuzzy logic can be said to have led to computer programming designed to mimic human intelligence [9]. Fuzzy logic has allowed for fuzzy control, which is a means for machine decision making based on the human operator’s knowledge [10].

Neural Networks

Neural networks are computer programs that work similarly to the human brain’s neural network. These work by distributing information throughout the network (instead of more traditional methods of housing information in programming).

Objectives met:
- C5
- 5.5