Introduction to Intelligent Control

There are many kinds of intelligent phenomena in nature, such as the cognitive process of the human brain, bird migration, and lions foraging. So can machines be programmed to imitate the thought processes of these animals? The answer is yes, and this technology that uses programs to simulate natural phenomena in nature to serve the control process is intelligent control technology.

It mainly talks about expert control, fuzzy control, artificial neural network control, genetic algorithm, and teaches MATLAB programming and SIMULINK knowledge to realize the above knowledge.

• Chapter 1：The emergence and development of intelligent control (14 minutes and 27 seconds)

• Chapter 2：The definition and characteristics of intelligent control (5 minutes and 50 seconds)

• Chapter 3：Research content of intelligent control (8 minutes and 33 seconds)

• Chapter 4：expert system (10 minutes and 26 seconds)

• Chapter 5：Expert control (14 minutes and 13 seconds)

• Chapter 6：Applications (11 minutes and 51 seconds)

• Chapter 7：Definition and representation of fuzzy sets (13 minutes and 58 seconds)

• Chapter 8：Basic operations of fuzzy sets (10 minutes and 47 seconds)

• Chapter 9：Membership degree and membership function (7 minutes and 46 seconds)

• Chapter 10：fuzzy relationship (9 minutes and 32 seconds)

• Chapter 11：Fuzzy reasoning (10 minutes and 46 seconds)

• Chapter 12：Mamdani reasoning (11 minutes and 45 seconds)

• Chapter 13：Applications (9 minutes and 26 seconds)

• Chapter 14：Basic principles of fuzzy control (5 minutes and 30 seconds)

• Chapter 15：The composition of fuzzy controller (17 minutes and 53 seconds)

• Chapter 16：Design of Fuzzy Controller (8 minutes and 41 seconds)

• Chapter 17：Applications (13 minutes and 25 seconds)

• Chapter 18：Overview of Artificial Neural Networks (10 minutes and 56 seconds)

• Chapter 19：Neurons and Mathematical Models (14 minutes and 26 seconds)

• Chapter 20：Artificial neural networks (11 minutes and 44 seconds)

• Chapter 21：Neural Network Learning Overview (5 minutes and 18 seconds)

• Chapter 22：neural network learning algorithm (12 minutes and 0 seconds)

• Chapter 23：BP neural network (13 minutes and 0 seconds)

• Chapter 24：type of learning (6 minutes and 57 seconds)

• Chapter 25：Neural network system identification (9 minutes and 48 seconds)

• Chapter 26：neural network control (7 minutes and 32 seconds)

• Chapter 27：Applications (15 minutes and 10 seconds)

• Chapter 28：Basic principles of genetic algorithm (11 minutes and 38 seconds)

• Chapter 29：Design of genetic algorithm and optimization of PID parameters (16 minutes and 29 seconds)

• Chapter 30：Applications (14 minutes and 23 seconds)

• Chapter 31：Introduction to MATLAB (12 minutes and 46 seconds)

• Chapter 32：Data types and operators (9 minutes and 55 seconds)

• Chapter 33：Matrices and operations (10 minutes and 21 seconds)

• Chapter 34：MATLAB programming basics (15 minutes and 16 seconds)

• Chapter 35：Use of SIMULINK simulation platform (13 minutes and 47 seconds)

• Chapter 36：MATLAB graphics output (7 minutes and 36 seconds)

• Chapter 37：Introduction to MATLAB GUI (14 minutes and 34 seconds)

• Chapter 38：Expert PID control experiment—experiment introduction (12 minutes and 26 seconds)

• Chapter 39：Expert pid control experiment - experimental procedure flow chart (3 minutes and 18 seconds)

• Chapter 40：Expert pid control experiment-experimental process (13 minutes and 4 seconds)

• Chapter 41：Signal tracking for fuzzy control—experimental introduction (5 minutes and 43 seconds)

• Chapter 42：Signal tracking for fuzzy control - building a simulation module (13 minutes and 46 seconds)

• Chapter 43：Signal tracking of fuzzy control - fuzzy control input and output settings (12 minutes and 35 seconds)

• Chapter 44：Signal tracking for fuzzy control - fuzzy control inferencer settings (11 minutes and 22 seconds)

• Chapter 45：Signal tracking for fuzzy control—simulation using Simulink (11 minutes and 2 seconds)

• Chapter 46：Neural network recognition simulation experiment—experiment introduction (6 minutes and 3 seconds)

• Chapter 47：Neural network recognition simulation experiment-experimental process (18 minutes and 37 seconds)

• Chapter 48：Neural network recognition simulation experiment - experimental program design (10 minutes and 15 seconds)

• Chapter 49：Genetic algorithm to find the maximum value of a function - experimental introduction (4 minutes and 35 seconds)

• Chapter 50：Genetic algorithm to find the maximum value of a function - experimental process (13 minutes and 16 seconds)

• Chapter 51：Research Background (18 minutes and 46 seconds)

• Chapter 52：Structure and design of PEMFC-UPS system (6 minutes and 42 seconds)

• Chapter 53：Analysis of factors affecting PEMFC output performance (9 minutes and 16 seconds)

• Chapter 54：Fuel cell power generation system modeling (10 minutes and 47 seconds)

• Chapter 55：Comprehensive intelligent control of fuel cell power generation system (13 minutes and 58 seconds)

• Chapter 56：Comprehensive intelligent control of fuel cell power generation system (14 minutes and 57 seconds)