A new calculation method of fractional order [proportional integral ]( FO [PI ]) controller parameters is proposed. And the systematic design schemes of fractional order [proportional integral ]( FO[PI]) controllers b...A new calculation method of fractional order [proportional integral ]( FO [PI ]) controller parameters is proposed. And the systematic design schemes of fractional order [proportional integral ]( FO[PI]) controllers based on vector method are discussed in detail. The FO[PI]controller parameters algorithm based on the vector method can be programmed in MATLAB. According to MATLAB programs of the FO[PI]controller parameters algorithm,the FO[PI] controllers are designed following the different phase margins,different gain crossover frequency and different plants,respectively. From the simulation results,the calculated parameters based on MATLAB program is unique and the designed FO[PI] controllers work efficiently.展开更多
A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in th...A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.展开更多
基金Sponsored by the Basic Research Program of Jilin Provincial Science & Technology Department(Grant No.20130102025JC)
文摘A new calculation method of fractional order [proportional integral ]( FO [PI ]) controller parameters is proposed. And the systematic design schemes of fractional order [proportional integral ]( FO[PI]) controllers based on vector method are discussed in detail. The FO[PI]controller parameters algorithm based on the vector method can be programmed in MATLAB. According to MATLAB programs of the FO[PI]controller parameters algorithm,the FO[PI] controllers are designed following the different phase margins,different gain crossover frequency and different plants,respectively. From the simulation results,the calculated parameters based on MATLAB program is unique and the designed FO[PI] controllers work efficiently.
文摘A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.
