A Decoupled Parameters Estimators for in Nonlinear Systems Fault diagnosis by ANFIS

This paper presents a new and efficient Adaptive Neural Fuzzy Inference Systems approach for satellite’s attitude control systems (ACSs) fault diagnosis. The proposed approach formulates the fault modelling problem of system component into an on-line parameters estimation The learning  ability of the adaptive neural fuzzy inference system allow as to decoupling the effect of each fault from the estimation of the others.  Our solution provides a method to detect, isolate, and estimate various faults in system components, using Adaptive Fuzzy Inference Systems Parameter Estimators (ANFISPEs) that are designed and based on parameterizations related to each class of fault. Each ANFISPE estimates the corresponding unknown Fault Parameter (FP) that is further used for fault detection, isolation and identification purposes. Simulation results reveal the effectiveness of the developed FDI scheme of an ACSs actuators of a 3-axis stabilized satellite.DOI:http://dx.doi.org/10.11591/ijece.v2i2.22

Sliding mode speed control for multi-motors system

Continuous processes in the plastics, textile paper and other industries, require several drives working in synchronism. The aim of this paper is to control speed of the multi motors system, and to maintain a constant mechanical tension between the rollers of the system. Several controllers are considerer, including Proportional-Integral (PI) and sliding-mode control (SMC). Since the PI control method can be applied easily and is widely known, it has an important place in control applications. But this method is insensitive to parameter changes. The advantage of an SMC is its robustness and ability to handle the non-linear behaviour of the system, and is indicated in comparison with traditional proportional-integral (P1) control scheme. Theoretical analysis and simulation results are provided to evaluate the consistency and performances of this control technique (SMC)

Linear Speed Control for Multi-Machine system Using Fuzzy-Sliding Mode

In this contribution, a control scheme based on multi input multi output Fuzzy Sliding Mode control (MIMOFSMC) for linear speed regulation of multi-motors system is proposed. Once the decoupled model of the multi- motors system is obtained, a smooth control function with a threshold was chosen to indicate how far the state from to the sliding surface is. However, the magnitude of this control function depends closely on the upper bound of uncertainties, and this generates chattering. So, this magnitude has to be chosen with great care to obtain high performances. Usually the upper bound of uncertainties is difficult to known before motor operation, so, a Fuzzy Sliding Mode controller is investigated to solve this difficulty; a simple Fuzzy inference mechanism is used to reduce the chattering phenomenon by simple adjustments. A simulation study is carried out and shows that the proposed controller has great potential for use as an alternative to the conventional sliding mode contro

Decentralized PI controller for multimotors web winding system

Web winding systems allow the operations of unwinding and rewinding of various products including plastic films, sheets of paper, sheets, and fabrics. These operations are necessary for the development and the treatment of these products. Web winding systems generally consist of the same machine elements in spite of the diversity of the transported products. Due to the wide rang variation of the radius and inertia of the rollers the system dynamic change considerably during the winding/ unwinding process. Decentralized PI controller for web tension control and linear speed control are presented in this paper. The PI control method can be applied easily and is widely known, it has an important place in control applications. Simulation results show the effectiveness of the proposed linear speed and tension controller for web winding multi motors systems