A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper pr...A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.展开更多
Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion ...Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.展开更多
The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional ...The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.展开更多
Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system ...Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.展开更多
常规的轧钢加热炉煤气智能燃烧控制方法主要使用Fuzzy双交叉限幅控制器进行控制阶跃响应,易受温变超调作用的影响,导致燃烧效率偏低。基于此,提出一种基于比例-积分-微分(Proportion Integral Differential,PID)算法的轧钢加热炉煤气智...常规的轧钢加热炉煤气智能燃烧控制方法主要使用Fuzzy双交叉限幅控制器进行控制阶跃响应,易受温变超调作用的影响,导致燃烧效率偏低。基于此,提出一种基于比例-积分-微分(Proportion Integral Differential,PID)算法的轧钢加热炉煤气智能燃烧控制方法。生成轧钢加热炉煤气智能燃烧控制策略,利用PID算法设计轧钢加热炉煤气智能燃烧控制器,从而实现轧钢加热炉煤气智能燃烧控制。实验结果表明,设计的轧钢加热炉煤气智能燃烧PID算法控制方法在不同控制起始时间下的煤气智能燃烧效率均较高,控制性能良好,具有较高的实际应用价值。展开更多
在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算...在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算法的变频器节能控制系统设计。构建以微处理器为核心的变频器节能控制结构,将神经网络与PID控制器相结合,构造自适应PID控制器。结合变频器节能控制结构的能耗计算与反馈,通过自适应调节权值系数完成变频系数调整,降低各频段能耗,实现变频器节能控制研究。实验结果显示,该系统节能效果显著,能耗最高仅为20 J,且相较于对比文献,该系统运行稳定,运行时间短,为变频器节能控制运行提供了保障。展开更多
针对常规比例、积分和微分(proportional integral derivative,PID)控制器在无人艇航向控制系统中表现出的稳定性差、控制精度低等问题,文章提出一种将模糊控制与反向传播(back propagation,BP)神经网络相结合的控制算法;在MATLAB中对...针对常规比例、积分和微分(proportional integral derivative,PID)控制器在无人艇航向控制系统中表现出的稳定性差、控制精度低等问题,文章提出一种将模糊控制与反向传播(back propagation,BP)神经网络相结合的控制算法;在MATLAB中对比常规PID控制器、模糊PID控制器与模糊神经网络PID控制器在给定期望航向角下的航向控制性能,仿真结果表明模糊神经网络PID控制器对无人艇的航向控制性能最佳;在搭建的实验平台上对不同航向控制器下无人艇的航行轨迹和航向角进行比较,实验结果进一步验证了模糊神经网络PID航向控制算法的优越性。展开更多
基金Project supported bY the National Natural Science Foundation of China （Grant No.50375085）, and the Natural Science Foundation of Shandong Province （Grant No.Y2002F13）
文摘A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.
基金Civil Project of China Aerospace Science and Technology CorporationUniversity-Industry Collaborative Education Program of Ministry of Education of China(No.220906517214433)。
文摘Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.
基金National Natural Science Foundation of China(No.61374114)Natural Science Foundation of Liaoning Province,China(No.2015020022)the Fundamental Research Funds for the Central Universities,China(No.3132015039)
文摘The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.
文摘Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.
文摘常规的轧钢加热炉煤气智能燃烧控制方法主要使用Fuzzy双交叉限幅控制器进行控制阶跃响应,易受温变超调作用的影响,导致燃烧效率偏低。基于此,提出一种基于比例-积分-微分(Proportion Integral Differential,PID)算法的轧钢加热炉煤气智能燃烧控制方法。生成轧钢加热炉煤气智能燃烧控制策略,利用PID算法设计轧钢加热炉煤气智能燃烧控制器,从而实现轧钢加热炉煤气智能燃烧控制。实验结果表明,设计的轧钢加热炉煤气智能燃烧PID算法控制方法在不同控制起始时间下的煤气智能燃烧效率均较高,控制性能良好,具有较高的实际应用价值。
文摘在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算法的变频器节能控制系统设计。构建以微处理器为核心的变频器节能控制结构,将神经网络与PID控制器相结合,构造自适应PID控制器。结合变频器节能控制结构的能耗计算与反馈,通过自适应调节权值系数完成变频系数调整,降低各频段能耗,实现变频器节能控制研究。实验结果显示,该系统节能效果显著,能耗最高仅为20 J,且相较于对比文献,该系统运行稳定,运行时间短,为变频器节能控制运行提供了保障。
文摘针对常规比例、积分和微分(proportional integral derivative,PID)控制器在无人艇航向控制系统中表现出的稳定性差、控制精度低等问题,文章提出一种将模糊控制与反向传播(back propagation,BP)神经网络相结合的控制算法;在MATLAB中对比常规PID控制器、模糊PID控制器与模糊神经网络PID控制器在给定期望航向角下的航向控制性能,仿真结果表明模糊神经网络PID控制器对无人艇的航向控制性能最佳;在搭建的实验平台上对不同航向控制器下无人艇的航行轨迹和航向角进行比较,实验结果进一步验证了模糊神经网络PID航向控制算法的优越性。
