Fuzzy modeling and control of multilayer incinerator
Fuzzy Sets and Systems - Special issue: Dedicated to the memory of Richard E. Bellman
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Dynamic parallel distributed compensation for Takagi-Sugeno fuzzy systems: An LMI approach
Information Sciences: an International Journal - Special issue analytical theory of fuzzy control with applications
Fuzzy Modeling for Control
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Foundations of Fuzzy Systems
Fuzzy Model Identification for Control
Fuzzy Model Identification for Control
Application of adaptive control to the fluctuation of engine speed at idle
Information Sciences: an International Journal
Fuzzy logic and neuro-fuzzy modelling of diesel spray penetration: A comparative study
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Information Sciences: an International Journal
On-line fuzzy modeling via clustering and support vector machines
Information Sciences: an International Journal
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
Computational intelligence approach to PID controller design using the universal model
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
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Air management for diesel engines is a major challenge from the control point of view because of the highly nonlinear behavior of this system. For this reason, linear control techniques are unable to provide the required performance, and nonlinear controllers are used instead. This article discusses two fundamental steps when designing a control system. Firstly, a methodology to identify Takagi-Sugeno (T-S) structures using experimental data is proposed. Secondly, the design of a fuzzy controller in PDC structure (Parallel Distributed Compensation) is presented. The parameters of this controller are obtained from a LMI (Linear Matrix Inequalities) minimization problem.