The chapter "fuzzy logic" deals with fuzyy sets, linguistic variables and fuzzification, operators between fuzzy sets, fuzzy relations, fuzzy implication, defuzzification, fuzzy blocks according to Mamdani and Sugeno-Takagi.
The chapter "fuzzy control" compares conventional P/PD/PI/PID controllers including output constraints and anti rest windup with different variants of fuzzy P/PD/PI/PID controllers. Also, the structures of fuzzy state feedback controllers and fuzzy extensions for conventional controllers are discussed. Simulations with the MATLAB fuzzy logic toolbox are shown.
The chapter "Neural Nets" deals with types of neurons, net layers, net structures, training methods (perceptron, delta rule, backpropagation), typical feedforward nets (multilayer perceptron, deedforward nets with sigmoid neurons, RBF nets, RCE nets) and examples for nets with feedback. Nets for unsupervised learning (self-organising map) are only mentioned. The realisation of nonlinear dynamics by a neural net with additional integrators or differentiators or with time-discrete storages is considered, too.
A further subject is the application of neural nets for control and system identification. Training and application are shown with the MATLAB neural net toolbox.
The chapter "special problems in industrial control" discusses typical control loop problems, methods of control loop performance monitoring and a short survey on "advanced control" in industry.