In this paper, the optimal power flow (OPF) problem is augmented to account for the costs associated with the loadfollowing stability of a power network. Load-following stability costs are expressed through the linear quadratic regulator (LQR). The power network is described by a set of nonlinear differential algebraic equations (DAEs). By linearizing the DAEs around a known equilibrium, a line...

اثرات ویرانگر بلایای طبیعی، اهمیت لجستیک و برنامه‌ریزی منابع انسانی را در مراحل قبل بعد از بحران نشان می‌دهد. هنگام بروز به ‌منظور امدادرسانی سریع، شبکه سلسله ‌مراتبی سلامت که شامل درمانگاه‌ها بیمارستان‌ها است، فعال می‌شود. این پژوهش با استفاده مدل ریاضی مختلط عدد صحیح درنظرگرفتن موقعیت فعلی درمانگاه‌ها، مکان‌های بهینه‌ای عنوان «مراکز درمان موقت» تعیین نحوه تخصیص بهینه مصدومان ناحیه‌های شهری مر...

The tuning of Linear Quadratic regulator (LQR) controllers is a challenge for researchers and plant operators. This paper presents a optimization and comparison of time response specification between Traditional ZN Tuning & Modified ZN Tuning controllers with Linear Quadratic Regulator (LQR) for a speed control of a separately excited DC motor. The goal is to determine which control strategy de...

In this paper we investigate the finite horizon linear quadratic regulation (LQR) problem for a linear continuous time system with time-varying delay in control input and a quadratic criterion. We assume that the time-varying delay is of a known upper bound, then the LQR problem is transformed into the optimal control problem for systems with multiple input channels, each of which has single co...

طلتخملا رطيسملل ميمصت مدقي ثحبلا اذه نا LQR/H-infinity .ةدكؤملا ريغو تاريغتملا ةددعتم ةمظنلأل مت ةفلك ةلاد ىلع ادامتعا ةعجارلا ةيذغتلا ةلاح تباوثل ىلثملا ميقلا داجيا ضرغل يئيزجلا دشحلا ةيلثما ةقيرط مادختسا تاددحم نيب طيلخ نع ةرابع يه ةحرتقملا ةفلكلا ةلاد نا.ةحرتقم LQR و H-infinity حرتقملا رطيسملا نا. ريغتملا ةددعتم ةمظنلأا ضوعي نا ةياع ةءافكبو عيطتسي رطيسملا ةوق تابثا ضرغل .ةيدكؤملا مدع دوجوب ...

Although it is well known that fuzzy learning controller is powerful for nonlinear systems, it is very difficult to apply a learning method if they are unstable. An unstable system diverges for impulse input. This divergence makes it difficult to learn the rules unless we can find the initial rules to make the system stable prior to learning. Therefore, we introduced LQR(Linear Quadratic Regula...

Linear Quadratic Regulator (LQR) is an optimal multivariable feedback control approach that minimizes the excursion in state trajectories of a system while requiring minimum controller effort. The behaviour of a LQR controller is determined by two parameters: state and control weighting matrices. These two matrices are main design parameters to be selected by designer and greatly influence the ...