This paper describes a control system architecture for cement milling that uses a control strategy that controls the feed flow based on Fuzzy Logic for adjusting the fresh feed. Control system architecture (CSA) consists of: a fuzzy controller, Programmable Logic Controllers (PLCs) and an OPC (Object Linking Embedded for Process Control) server. The paper presents how a fuzzy controller for a cement mill is designed by defining its structure using Fuzzy Inference System Editor [1]. Also,  the paper illustrates the structure of the implemented control system together with the developed PLC program and its simulation. Finally, the dynamic behavior of the cement mill is simulated using a MATLAB-Simulink scheme and some simulation results are presented.

/pdf/control-system-architecture-for-a-cement-mill-based-on-fuzzy-4rqm2mf9ug.pdf

Control System Architecture for a Cement Mill Based on Fuzzy Logic

The problem of fuzzy robust tracking control is investigated for uncertain nonlinear time-delay systems. The nonlinear time-delay system is modeled as uzzy Takagi-Sugeno (T-S) system, and fuzzy logic systems are used to eliminate the ncertainties of the system. A sufficient condition for the existence of fuzzy controller s given in terms of linear matrix inequalities (LMIs) and adaptive law. Based on yapunov stability theorem, the fuzzy control scheme guarantees the desired tracking erformance in sense that all the closed-loop signals are uniformly ultimately bounded (UUB). Simulation results of 2-link manipulator demonstrate the effectiveness of the eveloped control scheme.

/pdf/fuzzy-robust-tracking-control-for-uncertain-nonlinear-time-twgwbohzwj.pdf

Fuzzy Robust Tracking Control for Uncertain Nonlinear Time-Delay System

The problem of tracking control is addressed for a class of nonlinear systems with uncertainties. The original nonlinear systems are approximated by a fuzzy T-S model based on which a state-feedback controller is constructed by using the linear matrix inequalities. The approximating error is eliminated by an adaptive compensator based on fuzzy logic systems. The effectiveness of the proposed control scheme is demonstrated by a simulation example. The main advantage is that the designer makes milder constraint assumption for the approximation error and the uncertainties in nonlinear systems.

/pdf/a-new-approach-to-nonlinear-tracking-control-based-on-fuzzy-3649eb272f.pdf

A New Approach to Nonlinear Tracking Control Based on Fuzzy Approximation

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A New Approach to Nonlinear Tracking Control Based on Fuzzy Approximation