PID controllers were used for the hydraulic servo system of sliding gate and the tundish weight control system in continuous caster.These two loops were synthesized in mould level controller based on model reduction a...PID controllers were used for the hydraulic servo system of sliding gate and the tundish weight control system in continuous caster.These two loops were synthesized in mould level controller based on model reduction and internal model control strategy.Satisfactory control performance of this synthetic mould level controller was demonstrated by simulations and on-line experiments.展开更多
An electromagnetic parametrically excited rolling pendulum energy harvester with self-tuning mechanisms subject to multi-frequency excitation is proposed and investigated in this paper.The system consists of two uncou...An electromagnetic parametrically excited rolling pendulum energy harvester with self-tuning mechanisms subject to multi-frequency excitation is proposed and investigated in this paper.The system consists of two uncoupled rolling pendulum.The resonance frequency of each the rolling pendulum can be automatically tuned by adjusting its geometric parameters to access parametric resonance.This harvester can be used to harvest the energy at low frequency.A prototype is developed and evaluated.Its mathematical model is derived.A cam with rolling follower mechanism is employed to generate multi-frequency excitation.An experimental study is conducted to validate the proposed concept.The experimental results are confirmed by the numerical results.The harvester is successfully tuned when the angular velocity of the cam is changed from 1.149 to 1.236 Hz.展开更多
This paper presents a control strategy for maglev system based on the sliding mode controller with auto-tuning law. The designed adaptive controller will replace the conventional sliding mode control (SMC) to eliminat...This paper presents a control strategy for maglev system based on the sliding mode controller with auto-tuning law. The designed adaptive controller will replace the conventional sliding mode control (SMC) to eliminate the chattering resulting from the SMC. The stability of maglev system is ensured based on the Lyapunov theory. Simulation results verify the effectiveness of the proposed method. In addition, the advantages of the proposed controller are indicated in comparison with a traditional sliding mode controller.展开更多
This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID st...This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID structure according to the set point, error and error derivative of the process, respectively. The tuning of the PID controller is based on a fuzzy inference machine. The set of rules of the fuzzy inference machine was obtained by experts engineering. The system is tested in an austempering process but can be applied in any industrial plant. Besides, an analysis between the response of the process with a PID controller and the system of fuzzy auto-tuning for P1D proposed was made.展开更多
Reservoir simulation is known as perhaps the most widely used,accurate,and reliable method for field development in the petroleum industry.An integral part of a reliable reservoir simulation process is to consider rob...Reservoir simulation is known as perhaps the most widely used,accurate,and reliable method for field development in the petroleum industry.An integral part of a reliable reservoir simulation process is to consider robust and rigorous tuned EOS models.Traditionally,EOS models are tuned iteratively through arduous workflows against experimental PVT data.However,this comes with a number of drawbacks such as forcingly using weight factors,which upon alteration adversely affects the optimization process.The objective of the current work is thus to introduce an auto-tune PVT matching tool using NSGA-II multi-objective optimization.In order to illustrate the robustness of the presented technique,three different PVT samples are used,including two black-oil and one gas condensate sample.We utilize PengRobinson EOS during all the manual and auto-tuning processes.Comparison of auto-tuned EOS-generated results with those of experimental and computed statistical error values for these samples clearly show that the proposed method is robust.In addition,the proposed method,contrary to the manual matching process,provides the engineer with several matched solutions,which allows them to select a match based on the engineering background to be best amenable to the problem at hand.In addition,the proposed technique is fast,and can output several solutions within less time compared to the traditional manual matching method.展开更多
While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time...While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.展开更多
文摘PID controllers were used for the hydraulic servo system of sliding gate and the tundish weight control system in continuous caster.These two loops were synthesized in mould level controller based on model reduction and internal model control strategy.Satisfactory control performance of this synthetic mould level controller was demonstrated by simulations and on-line experiments.
文摘An electromagnetic parametrically excited rolling pendulum energy harvester with self-tuning mechanisms subject to multi-frequency excitation is proposed and investigated in this paper.The system consists of two uncoupled rolling pendulum.The resonance frequency of each the rolling pendulum can be automatically tuned by adjusting its geometric parameters to access parametric resonance.This harvester can be used to harvest the energy at low frequency.A prototype is developed and evaluated.Its mathematical model is derived.A cam with rolling follower mechanism is employed to generate multi-frequency excitation.An experimental study is conducted to validate the proposed concept.The experimental results are confirmed by the numerical results.The harvester is successfully tuned when the angular velocity of the cam is changed from 1.149 to 1.236 Hz.
文摘This paper presents a control strategy for maglev system based on the sliding mode controller with auto-tuning law. The designed adaptive controller will replace the conventional sliding mode control (SMC) to eliminate the chattering resulting from the SMC. The stability of maglev system is ensured based on the Lyapunov theory. Simulation results verify the effectiveness of the proposed method. In addition, the advantages of the proposed controller are indicated in comparison with a traditional sliding mode controller.
文摘This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID structure according to the set point, error and error derivative of the process, respectively. The tuning of the PID controller is based on a fuzzy inference machine. The set of rules of the fuzzy inference machine was obtained by experts engineering. The system is tested in an austempering process but can be applied in any industrial plant. Besides, an analysis between the response of the process with a PID controller and the system of fuzzy auto-tuning for P1D proposed was made.
文摘Reservoir simulation is known as perhaps the most widely used,accurate,and reliable method for field development in the petroleum industry.An integral part of a reliable reservoir simulation process is to consider robust and rigorous tuned EOS models.Traditionally,EOS models are tuned iteratively through arduous workflows against experimental PVT data.However,this comes with a number of drawbacks such as forcingly using weight factors,which upon alteration adversely affects the optimization process.The objective of the current work is thus to introduce an auto-tune PVT matching tool using NSGA-II multi-objective optimization.In order to illustrate the robustness of the presented technique,three different PVT samples are used,including two black-oil and one gas condensate sample.We utilize PengRobinson EOS during all the manual and auto-tuning processes.Comparison of auto-tuned EOS-generated results with those of experimental and computed statistical error values for these samples clearly show that the proposed method is robust.In addition,the proposed method,contrary to the manual matching process,provides the engineer with several matched solutions,which allows them to select a match based on the engineering background to be best amenable to the problem at hand.In addition,the proposed technique is fast,and can output several solutions within less time compared to the traditional manual matching method.
基金sponsored by the National Natural Science Foundation of China under Grant Nos.62022057,61832006,61632017,and 61872240.
文摘While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.
