Introducing a System-on-Chip （SoC） microcontroller （C8051F350） into a ceramic pressure sensor has resulted in the design of a intelligent sensor. An improved algorithm for digital phassensitive detection is used ...Introducing a System-on-Chip （SoC） microcontroller （C8051F350） into a ceramic pressure sensor has resulted in the design of a intelligent sensor. An improved algorithm for digital phassensitive detection is used to perform lock-in amplification of the sensor signal. The compensation for the sensor error is realized by the detection of the sensor＇s supply voltage and working temperature. The system also has the function of short/open circuit fault detection and can ommamicate with other digital equipment through an RS-485 communication interface. In the design, full utilization of the SoC microcontroller＇ s internal resource results in the simple hardware structure. Experimental results show that the error of the sensor is less than 0.5% at range ratio 1 ： 10. Employing the microcontroller and using lock-in amplification algorithm are an effective method for achieving an intelligent sensor of slowly-varying physical quantities, thereby improving the measuring accuracy and performance.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.展开更多
基金supported by Research Project of "SUSTSpring Bud"(No.2008BWZ042)from Shandong University of Science and Technology
文摘Introducing a System-on-Chip （SoC） microcontroller （C8051F350） into a ceramic pressure sensor has resulted in the design of a intelligent sensor. An improved algorithm for digital phassensitive detection is used to perform lock-in amplification of the sensor signal. The compensation for the sensor error is realized by the detection of the sensor＇s supply voltage and working temperature. The system also has the function of short/open circuit fault detection and can ommamicate with other digital equipment through an RS-485 communication interface. In the design, full utilization of the SoC microcontroller＇ s internal resource results in the simple hardware structure. Experimental results show that the error of the sensor is less than 0.5% at range ratio 1 ： 10. Employing the microcontroller and using lock-in amplification algorithm are an effective method for achieving an intelligent sensor of slowly-varying physical quantities, thereby improving the measuring accuracy and performance.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
