Recommendations of Optimal Sampling Rates for Periodic Output Feedback Based Discrete Mode PSS

In this paper, an attempt is made to recommend the optimal sampling time period for Periodic Output Feedback (POF) based discrete mode power system stabilizer (DPSS). Various collection of input and output sampling time interval has been used in the designing of POF based DPSS. The Particle Swarm Optimization (PSO) technique is used to obtain the optimal gain matrix of the POF controller as well as the optimal sampling time intervals. The effectiveness of POF based DPSS over continuous mode lead-lag PSS is certified using small-signal stability studies. The parameters of lead-lag type continuous mode PSS is also tuned using the PSO technique. The PSS is designed using POF technique for single machine infinite bus (SMIB) system, considering a variety of sampling time intervals at input-output port. Finally, a trial is made to propose an optimum input and output sampling time period for SMIB test power system, through simulation studies.

Seasonal fluctuation and host species affect Tobacco ringspot virus detection

Tobacco ringspot virus (TRSV) is a pathogen with a wide host range that can cause disease in many perennial species. Yet detection of this virus can be insistent and unreliable, complicating disease management. In this study we asked whether seasonal effects changed the titer and distribution of the virus in Vitis vinifera, Malus domestica, and Prunus armeniaca. We developed an RT-qPCR assay and used it to monitor TRSV accumulation in leaves, stems, and roots over the course of a year. TRSV titer, and the tissues in which it accumulated, changed throughout the year in a host-specific manner which may be due to host plant growth patterns and temperature. These data will aid in determining optimal sampling time, and which tissues to collect to have confidence in diagnostic results.

Optimization Procedure for Computing Sampling Time for Induction Machine Parameter Estimation

This paper presents a method for selecting the sampling time for induction machine parameter estimation from the machine line start measurements. the metaheuristic optimization method is used to find the optimal Prony exponential series approxiamtion of the line start transient current. From the optimal approximation, poles of the linearized induction machine model are computed and used to determine the optimal sampling time. the results show that sampling frequencies needed for parameter estimation are much lower than 1–15 kHz commonly used today. This reduces the necessary amount of collected data and the computing power needed for the estimation. the optimal sampling time is computed for the simulated and for the measured data. Referenced parameter estimation technique is tested for the measured transient showing benefits of using the optimal sampling time.

Discrete-time feedback stabilization

This paper presents an algorithm for designing dynamic compensator for infinitedimensional systems with bounded input and bounded output operators using finite dimensional approximation. The proposed method was then implemented in order to find the control function for thin rod heating process. The optimal sampling time was found depending on discrete output measurements.