Pub. online:1 Jan 2005Type:Research ArticleOpen Access
Volume 16, Issue 4 (2005), pp. 571–586
Due to high nonlinearities and time-varying dynamics of today's control systems fuzzy learning controllers find appliance in practice. The present paper proposes a method for the synthesis of the learning fuzzy controllers where an expert knowledge about a process is applied to form a learning mechanism that is used to acquire information for the knowledge base of the main fuzzy controller. According to the proposed method an expert knowledge is used to describe how the controller should learn to control rather than to control the process. The results of experiments on heating system and level/pressure system prove the practical relevance of the design strategy of a learning fuzzy controller.
Pub. online:1 Jan 2003Type:Research ArticleOpen Access
Volume 14, Issue 3 (2003), pp. 323–336
This paper analyses coupled control of a nonlinear, time‐varying plant. Uncoupled and coupled direct adaptive controllers, based on fuzzy logics, are synthesized to control the water level and the air pressure in a closed tank. The satisfactory efficiency of the controllers is experimentally demonstrated running the plant under the different working conditions. Coupled fuzzy controllers are compared with the uncoupled fuzzy controllers.
Pub. online:1 Jan 2002Type:Research ArticleOpen Access
Volume 13, Issue 3 (2002), pp. 287–298
This paper analyses the control of nonlinear plant with the changing dynamics. Adaptive controllers, based on fuzzy logics, are synthesized for the control of air pressure and water level. Their satisfactory efficiency is experimentally demonstrated under different working conditions. Fuzzy controllers are compared to conventional PI and PID controllers.