Nonlinear systems analysis (2nd ed.)
Nonlinear systems analysis (2nd ed.)
A supervisor for control of mode-switch processes
Automatica (Journal of IFAC)
Stable fuzzy adaptive control for a class of nonlinear systems
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Predictive functional control based on fuzzy model for heat-exchanger pilot plant
IEEE Transactions on Fuzzy Systems
Brief paper: Implementation of self-tuning regulators with variable forgetting factors
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
A new pattern of knowledge based on experimenting the causality relation
INES'10 Proceedings of the 14th international conference on Intelligent engineering systems
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
EKF-Based Localization of a Wheeled Mobile Robot in Structured Environments
Journal of Intelligent and Robotic Systems
A new systematic design for Habitually Linear Evolving TS Fuzzy Model
Expert Systems with Applications: An International Journal
Iterative performance improvement of fuzzy control systems for three tank systems
Expert Systems with Applications: An International Journal
Signatures: Definitions, operators and applications to fuzzy modelling
Fuzzy Sets and Systems
Stable and convergent iterative feedback tuning of fuzzy controllers for discrete-time SISO systems
Expert Systems with Applications: An International Journal
Evolutionary optimization-based tuning of low-cost fuzzy controllers for servo systems
Knowledge-Based Systems
Fuzzy Control of a Helio-Crane
Journal of Intelligent and Robotic Systems
Hybrid-fuzzy modeling and identification
Applied Soft Computing
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The paper presents the identification issues of the self-tuning nonlinear controller ASPECT (Advanced control algorithmS for ProgrammablE logiC conTrollers). The controller is implemented on a simple PLC platform with an extra mathematical coprocessor, but is intended for the advanced control of complex processes. The model of the controlled plant is obtained by means of experimental modelling. A special batch-wise algorithm that is based on the Takagi-Sugeno model and uses ''fuzzy instrumental variables'' technique is described in the paper. Many robustness problems of the classical adaptive approaches can be circumvented to some extent by the proposed batch-wise approach combined with a supervisory mechanism. The paper also includes some experimental results on the hydraulic pilot plant and some simulation case studies.