Tamer Shaqarin - Academia.edu (original) (raw)
Research interests:• Flow control (Separation Control, Mixing layer control, and Drag reduction).• Closed-loop control (Robust control, LPV control, and non-linear control).• Process Control (Chemical CSTR, Granulation, Bio-CSTR)• Optimization-based Control (PSO, Extremum seeking, Genetic algorithm)• Renewable energy systems control (MPPT, Pitch control, supervisory control)
less
Uploads
Papers by Tamer Shaqarin
Flow, Turbulence and Combustion, 2014
Flow Turbulence and Combustion
Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a dedicat... more Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a dedicated large scale, low speed wind-tunnel facility. The flow is manipulated by an array of fluidic micro-valve actuators integrated into the trailing edge of a splitter plate. Sensing is performed using a rake of hot-wire probes downstream of the splitter plate in the mixing layer. The control goal is the manipulation of the local fluctuating energy level. The mixing layer's response to the control is tested with open-loop forcing with a wide range of actuation frequencies. Results are discussed for different closed-loop control approaches, such as: adaptive extremum-seeking and in-time POD mode feedback control. In addition, we propose Machine Learning Control (MLC) as a model-free closed-loop control method. MLC arrives reproducibly at the near-optimal in-time control.
Flow, Turbulence and Combustion, 2014
Parezanović et al. dition, we propose Machine Learning Control (MLC) as a model-free closed-loop ... more Parezanović et al. dition, we propose Machine Learning Control (MLC) as a model-free closed-loop control method. MLC arrives reproducibly at the near-optimal in-time control. Keywords shear flow • turbulence • active flow control • extremum seeking • POD • machine learning • genetic programming * from ANR project name: "TUrbulence COntrol using Reduced-Order Models"
Flow, Turbulence and Combustion, 2014
Flow Turbulence and Combustion
Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a dedicat... more Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a dedicated large scale, low speed wind-tunnel facility. The flow is manipulated by an array of fluidic micro-valve actuators integrated into the trailing edge of a splitter plate. Sensing is performed using a rake of hot-wire probes downstream of the splitter plate in the mixing layer. The control goal is the manipulation of the local fluctuating energy level. The mixing layer's response to the control is tested with open-loop forcing with a wide range of actuation frequencies. Results are discussed for different closed-loop control approaches, such as: adaptive extremum-seeking and in-time POD mode feedback control. In addition, we propose Machine Learning Control (MLC) as a model-free closed-loop control method. MLC arrives reproducibly at the near-optimal in-time control.
Flow, Turbulence and Combustion, 2014
Parezanović et al. dition, we propose Machine Learning Control (MLC) as a model-free closed-loop ... more Parezanović et al. dition, we propose Machine Learning Control (MLC) as a model-free closed-loop control method. MLC arrives reproducibly at the near-optimal in-time control. Keywords shear flow • turbulence • active flow control • extremum seeking • POD • machine learning • genetic programming * from ANR project name: "TUrbulence COntrol using Reduced-Order Models"