Sharif Digital Repository

One of the main challenges of hybrid simulation is developing integration methods that not only provide accurate and stable results but also are compatible with the hybrid simulation circumstances. This paper presents a novel enhanced integration technique for hybrid simulation termed “modified operator splitting” (MOS) method. The main aim of the MOS technique is to improve the precision of the operator splitting (OS) method by reducing the corrector step length, where initial stiffness is utilized instead of actual stiffness. For this purpose, a new algorithm is proposed, which makes a more precise estimation of the predictor displacement; thus minimizes the effect of the corrective... 

One of the main challenges of hybrid simulation is developing integration methods that not only provide accurate and stable results but also are compatible with the hybrid simulation circumstances. This paper presents a novel enhanced integration technique for hybrid simulation termed “modified operator splitting” (MOS) method. The main aim of the MOS technique is to improve the precision of the operator splitting (OS) method by reducing the corrector step length, where initial stiffness is utilized instead of actual stiffness. For this purpose, a new algorithm is proposed, which makes a more precise estimation of the predictor displacement; thus minimizes the effect of the corrective... 

One of the main challenges of hybrid simulation is developing integration methods that not only provide accurate and stable results but also are compatible with the hybrid simulation circumstances. This paper presents a novel enhanced integration technique for hybrid simulation termed “modified operator splitting” (MOS) method. The main aim of the MOS technique is to improve the precision of the operator splitting (OS) method by reducing the corrector step length, where initial stiffness is utilized instead of actual stiffness. For this purpose, a new algorithm is proposed, which makes a more precise estimation of the predictor displacement; thus minimizes the effect of the corrective... 

Fuzzy sliding mode control (FSMC) as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. The performance of the proposed method has been evaluated for both single input single output (SISO) and MIMO nonlinear systems through its application in three severely nonlinear processes that are frequently used as benchmarks of nonlinear process control strategies. The evaluation shows that, despite its lack of dependence on the process model, the proposed method performs almost the same as conventional sliding mode control alternatives that utilize all the information that exists in the mathematical model of the process....