Intelligent control system

An intelligent control system is an automatic control system that uses various artificial intelligence-based computing methods, such as fuzzy logic control systems, genetic algorithm-based control systems, and neural network-like control systems.

• Chapter 1：Course Introduction (8 minutes and 54 seconds)

• Chapter 2：Introduction to intelligent control systems 1. Automatic control system (13 minutes and 41 seconds)

• Chapter 3：Introduction to Intelligent Control Systems 2. Computational Intelligence (8 minutes and 23 seconds)

• Chapter 4：Introduction to Intelligent Control Systems 3. Fuzzy Logic System (8 minutes and 46 seconds)

• Chapter 5：Introduction to Intelligent Control Systems 4. Evolutionary Computation (10 minutes and 10 seconds)

• Chapter 6：Introduction to Intelligent Control Systems 5. Neural Networks (8 minutes and 58 seconds)

• Chapter 7：Fuzzy set 1. Explicit set (11 minutes and 40 seconds)

• Chapter 8：Fuzzy set 2. Fuzzy set (17 minutes and 47 seconds)

• Chapter 9：Fuzzy sets 3. Basic concepts of fuzzy sets (11 minutes and 37 seconds)

• Chapter 10：Fuzzy set 4. Fuzzy belonging function (10 minutes and 23 seconds)

• Chapter 11：Fuzzy set 5. Operations of fuzzy sets (10 minutes and 46 seconds)

• Chapter 12：Fuzzy logic 1. Clear relationship (16 minutes and 32 seconds)

• Chapter 13：Fuzzy logic 2. Fuzzy relationship (17 minutes and 34 seconds)

• Chapter 14：Fuzzy logic 3. Extension principle (12 minutes and 43 seconds)

• Chapter 15：Fuzzy logic 4. Linguistic variables (13 minutes and 34 seconds)

• Chapter 16：Fuzzy logic 5. Fuzzy rules (11 minutes and 4 seconds)

• Chapter 17：Fuzzy logic 6. Fuzzy inference (16 minutes and 52 seconds)

• Chapter 18：Fuzzy control system (1) 1. Fuzzy inference system (12 minutes and 15 seconds)

• Chapter 19：Fuzzy control system (1) 2. Matlab programming (11 minutes and 12 seconds)

• Chapter 20：Fuzzy control system (1) 3. Fuzzy control of air conditioner (17 minutes and 23 seconds)

• Chapter 21：Fuzzy control system (1) 4. Fuzzy control of washing machine (16 minutes and 44 seconds)

• Chapter 22：Fuzzy control system (1) 5. Sugeno fuzzy model (12 minutes and 54 seconds)

• Chapter 23：Fuzzy control system (2) 1. DC motor fuzzy control (18 minutes and 17 seconds)

• Chapter 24：Fuzzy control system (2) 2. Inverted pendulum fuzzy control (18 minutes and 37 seconds)

• Chapter 25：Fuzzy control system (2) 3. Fuzzy control of reversing and warehousing (16 minutes and 41 seconds)

• Chapter 26：Fuzzy control system (2) 4. Robot fuzzy control (18 minutes and 50 seconds)

• Chapter 27：TS fuzzy control system (1) 1. TS fuzzy model (18 minutes and 54 seconds)

• Chapter 28：TS fuzzy control system (1) 2. Parallel distribution compensation (11 minutes and 32 seconds)

• Chapter 29：TS fuzzy control system (1) 3. Lyapunov stability theorem (12 minutes and 15 seconds)

• Chapter 30：TS fuzzy control system (1) 4. Stability theorem of closed-loop TS fuzzy system (11 minutes and 51 seconds)

• Chapter 31：TS fuzzy control system (1) 5. Stability theorem of closed-loop TS fuzzy system (17 minutes and 9 seconds)

• Chapter 32：TS fuzzy control system (2) 1. Linear matrix inequality (13 minutes and 35 seconds)

• Chapter 33：TS fuzzy control system (2) 2. Decline rate TS fuzzy controller design (11 minutes and 30 seconds)

• Chapter 34：TS fuzzy control system (2) 3. Inverted pendulum TS fuzzy control (12 minutes and 28 seconds)

• Chapter 35：TS fuzzy control system (2) 4. Bidirectional charger and discharger TS fuzzy control (17 minutes and 18 seconds)

• Chapter 36：TS fuzzy control system (2) 5. Robot TS fuzzy control (18 minutes and 5 seconds)

• Chapter 37：Binary genetic algorithm (1) 1. Gradient descent method (17 minutes and 45 seconds)

• Chapter 38：Binary genetic algorithm (1) 2. Characteristics of genetic algorithm (11 minutes and 39 seconds)

• Chapter 39：Binary genetic algorithm (1) 3. Binary encoding and decoding (16 minutes and 43 seconds)

• Chapter 40：Binary Gene Algorithm (1) 4. Initial Population (11 minutes and 19 seconds)

• Chapter 41：Binary genetic algorithm (1) 5. Fitness function (12 minutes and 23 seconds)

• Chapter 42：Binary genetic algorithm (2) 1. Natural selection operation (17 minutes and 46 seconds)

• Chapter 43：Binary genetic algorithm (2) 2. Mating operation (17 minutes and 49 seconds)

• Chapter 44：Binary genetic algorithm (2) 3. Mutation operation (11 minutes and 44 seconds)

• Chapter 45：Binary Gene Algorithm (2) 4. Elite Policy (11 minutes and 34 seconds)

• Chapter 46：Binary genetic algorithm (2) 5. Parameter analysis of genetic algorithm (12 minutes and 6 seconds)

• Chapter 47：Control system based on genetic algorithm 1. Function extreme value based on genetic algorithm (16 minutes and 28 seconds)

• Chapter 48：Control system based on genetic algorithm 2. Control system time domain response and PID controller (18 minutes and 10 seconds)

• Chapter 49：Control system based on genetic algorithm 3. Optimal PID control based on genetic algorithm (15 minutes and 46 seconds)

• Chapter 50：Control system based on genetic algorithm 4. Robust PID control based on genetic algorithm (17 minutes and 55 seconds)

• Chapter 51：Advanced genetic algorithm 1. Real number type genetic algorithm (18 minutes and 58 seconds)

• Chapter 52：Advanced genetic algorithm 2. Control system based on real number genetic algorithm (16 minutes and 29 seconds)

• Chapter 53：Advanced genetic algorithm 3. Gray coding (11 minutes and 10 seconds)

• Chapter 54：Advanced genetic algorithm 4. Linear scaling of adaptation function (11 minutes and 16 seconds)

• Chapter 55：Advanced genetic algorithm 5. Fitness function standard deviation scaling (13 minutes and 40 seconds)

• Chapter 56：Control system based on particle swarm optimization method 1. Principle of particle swarm optimization method (18 minutes and 41 seconds)

• Chapter 57：Control system based on particle swarm optimization method 2. Function extreme value based on particle swarm optimization method (16 minutes and 26 seconds)

• Chapter 58：Control system based on particle swarm optimization method 3. Parameter analysis of particle swarm optimization method (11 minutes and 27 seconds)

• Chapter 59：Control system based on particle swarm optimization method 4. PID control based on particle swarm optimization method (11 minutes and 42 seconds)

• Chapter 60：Control system based on particle swarm optimization method 5. Robust PID control based on particle swarm optimization method (13 minutes and 57 seconds)

• Chapter 61：Fuzzy control system based on evolutionary computing 1. Spindle motor servo system (12 minutes and 32 seconds)

• Chapter 62：Fuzzy control system based on evolutionary computation 2. Fuzzy control based on genetic algorithm (12 minutes and 16 seconds)

• Chapter 63：Fuzzy control system based on evolutionary computing 3. Robotic arm control system (11 minutes and 44 seconds)

• Chapter 64：Fuzzy control system based on evolutionary computation 4. TS fuzzy control based on genetic algorithm (11 minutes and 36 seconds)

• Chapter 65：Fuzzy control system based on evolutionary computing 5. Based on maglev control system (11 minutes and 51 seconds)

• Chapter 66：Fuzzy control system based on evolutionary calculation 6. TS fuzzy control based on particle swarm optimization method (13 minutes and 12 seconds)

• Chapter 67：Single-layer neural network 1. Neuron-like model (15 minutes and 15 seconds)

• Chapter 68：Single layer neural network 2. Perceptron (17 minutes and 16 seconds)

• Chapter 69：Single-layer neural network 3. Perceptron application case (13 minutes and 1 seconds)

• Chapter 70：Single-layer neural network 4. Adapt to linear components (18 minutes and 15 seconds)

• Chapter 71：Single-layer neural network 5. Application examples adapted to linear components (15 minutes and 28 seconds)

• Chapter 72：Multi-layer neural network 1. Multi-layer neural network architecture (14 minutes and 52 seconds)

• Chapter 73：Multi-layer neural network 2. Backpropagation algorithm (17 minutes and 25 seconds)

• Chapter 74：Multi-layer neural network 3. XOR gate (12 minutes and 22 seconds)

• Chapter 75：Multi-layer neural network 4. Function approximation (12 minutes and 58 seconds)

• Chapter 76：Multi-layer neural network 5. Multi-layer neural network application examples (20 minutes and 1 seconds)

• Chapter 77：Neural network-like control system (1) 1. Neural network-like control system (19 minutes and 18 seconds)

• Chapter 78：Neural network-like control system (1) 2. Neural network-like pattern predictive control (17 minutes and 39 seconds)

• Chapter 79：Neural network-like control system (1) 3. Engine neural network-like temperature control (17 minutes and 33 seconds)

• Chapter 80：Neural network-like control system (1) 4. DC motor neural network-like control (19 minutes and 14 seconds)

• Chapter 81：Neural network-like control system (2) 1. Neural network-like model reference control (15 minutes and 40 seconds)

• Chapter 82：Neural network-like control system (2) 2. Robot arm system identification (13 minutes and 10 seconds)

• Chapter 83：Neural network-like control system (2) 3. Neural network-like control of robot arm (13 minutes and 16 seconds)

• Chapter 84：Neural network-like control system (2) 4. Neural network control for reversing and warehousing (15 minutes and 22 seconds)

• Chapter 85：Fuzzy neural network control system 1. Adaptive neuro-fuzzy inference system (14 minutes and 27 seconds)

• Chapter 86：Fuzzy neural network control system 2. Hybrid learning algorithm (12 minutes and 17 seconds)

• Chapter 87：Fuzzy neural network control system 3. Discrete dynamic control system (12 minutes and 50 seconds)

• Chapter 88：Fuzzy neural network control system 4. Reversing and warehousing control system (15 minutes and 4 seconds)