Abstract. The Switched Reluctance Motor (SRM) Drives have attracted the attention of many researchers in the recent past because of advantages like simple mechanical structure, adaptability to harsh environments like coal mining etc. But it has one main disadvantage of high torque ripple due to its double saliency structure. The Direct Torque Control (DTC) technique can minimize the torque ripp...

In this paper two robust H∞ feedback control laws are designed, one for active wing bending damping, and one for active damping of the wing and hull bending modes. For the latter, not only symmetrically commanded ailerons are used, but also the elevator and direct lift control (DLC) flaps. The control objective of these feedback laws is the reduction of fatigue of the wing roots, as well as the...

In this paper, an adaptive control strategy is proposed for the inverters of renewable energy source (RES) to simultaneously control the load voltage, grid current and the amount of instantaneous injected power to the grid in the presence of grid voltage distortions and nonlinearity of load current. In the proposed control strategy, the power quality of the local load can be settled based on th...

the management of sedimentation problems in rivers and reservoirs depend greatly on the sediment yield from the catchment land surface. in this research the effects of biological measures and ranges enclose on suspended load in two sub-catchments of kakhk experimentalwatershed in gonabad has been studied. this catchment contains both control and experimental sub-catchments. these sub-catchments...

This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based ...

This paper considers a demand response agent that must find a near-optimal sequence of decisions based on sparse observations of its environment. Extracting a relevant set of features from these observations is a challenging task and may require substantial domain knowledge. One way to tackle this problem is to store sequences of past observations and actions in the state vector, making it high...