An introduction to fuzzy control
An introduction to fuzzy control
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Stability analysis of fuzzy control systems
Fuzzy Sets and Systems
Foundations of Fuzzy Control
Robust Control Design with MATLAB® (Advanced Textbooks in Control and Signal Processing)
Robust Control Design with MATLAB® (Advanced Textbooks in Control and Signal Processing)
Robust stability of single input fuzzy system for control of industrial plants with time delay
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Theoretical advances of intelligent paradigms
Design and stability analysis of single-input fuzzy logiccontroller
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Technical Communique: H∞ stability robustness of fuzzy control systems
Automatica (Journal of IFAC)
Brief Robust stability of fuzzy control systems based on conicity conditions
Automatica (Journal of IFAC)
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The robustness of the systems with fuzzy logic controllers (FLC) has lately focused the attention of researchers in relation with the expansion of their industrial application. The contemporary complex, nonlinear, time varying processes with time delay and various disturbances and the high demands for their control require to account for system stability and robustness in the FLC's design. The simplicity of the design is of great importance in connection to its easy practical application. The aim of the present investigation is to develop a generalised procedure for the design of various PI-like FLCs with regard to system performance robustness and to compare the robustness of the control systems. The approach is developed for PI incremental and position FLCs based on the single input fuzzy controller (SI FC), Popov stability and Morari robustness and considers the control of industrial plants with time delay and model uncertainty. The main contributions are: 1) a generalised design procedure for FLCs accounting for system stability and robustness; 2) FLCs' general tuning algorithm. The results are applied for the stabilisation of the air temperature in a furnace using MATLAB™. The performance of the designed FLC systems is assessed and compared to the performance of control systems with internam model controller via simulations.