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
This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order m...This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.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
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
在传统比例积分微分(Proportional Integral Derivative,PID)控制的基础上,考虑到论域因子的误差,设计了一种函数型的变论域模糊PID控制策略。基于1/4车辆二自由度磁流变半主动悬架系统,首先,建立了磁流变阻尼器的正、逆模型;然后,根据...在传统比例积分微分(Proportional Integral Derivative,PID)控制的基础上,考虑到论域因子的误差,设计了一种函数型的变论域模糊PID控制策略。基于1/4车辆二自由度磁流变半主动悬架系统,首先,建立了磁流变阻尼器的正、逆模型;然后,根据车辆磁流变半主动悬架系统的振动特性建立了模糊推理规则;最后,基于变论域的思想,设计了模糊论域的伸缩因子,以获得最优的控制精度。利用Matlab/Simulink软件在随机路面和正弦路面分别对车辆磁流变半主动悬架进行了仿真分析,通过车身垂直加速度、悬架动挠度以及车轮动载荷进行悬架性能评价,结果表明,与被动悬架、模糊控制和模糊PID控制相比,变论域模糊PID控制使车辆磁流变半主动悬架各性能指标均得到有效改善。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
自动驾驶智能汽车逐渐普及,其在通过城市路面的沟渠、井盖和减速带等特殊路面时,制动与减速时的稳定性与乘坐舒适性较差,为改善这一状况,对悬架的设计提出了更高的要求。为了提高自动驾驶智能汽车制动与减速时的稳定性,通过融合比例积...自动驾驶智能汽车逐渐普及,其在通过城市路面的沟渠、井盖和减速带等特殊路面时,制动与减速时的稳定性与乘坐舒适性较差,为改善这一状况,对悬架的设计提出了更高的要求。为了提高自动驾驶智能汽车制动与减速时的稳定性,通过融合比例积分微分(Proportional Integral Derivative,PID)与模糊算法,设计了针对这些特殊路面的主动悬架模糊PID控制器,在Matlab/Simulink软件中搭建了半车主动悬架仿真模型,通过惯性测量单元(Inertial Measurement Unit,IMU)实车测量了沟渠路面的路面激励信息,并完成仿真试验。结果表明,当自动驾驶智能汽车在C级路面和沟渠路面行驶时,设计的主动悬架模糊PID控制器较单一算法的控制器更有效地降低了车身垂向加速度、车身俯仰角加速度、车轮动载荷和悬架动行程,改善了悬架性能。展开更多
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This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.
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。
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.
文摘在传统比例积分微分(Proportional Integral Derivative,PID)控制的基础上,考虑到论域因子的误差,设计了一种函数型的变论域模糊PID控制策略。基于1/4车辆二自由度磁流变半主动悬架系统,首先,建立了磁流变阻尼器的正、逆模型;然后,根据车辆磁流变半主动悬架系统的振动特性建立了模糊推理规则;最后,基于变论域的思想,设计了模糊论域的伸缩因子,以获得最优的控制精度。利用Matlab/Simulink软件在随机路面和正弦路面分别对车辆磁流变半主动悬架进行了仿真分析,通过车身垂直加速度、悬架动挠度以及车轮动载荷进行悬架性能评价,结果表明,与被动悬架、模糊控制和模糊PID控制相比,变论域模糊PID控制使车辆磁流变半主动悬架各性能指标均得到有效改善。
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.
文摘自动驾驶智能汽车逐渐普及,其在通过城市路面的沟渠、井盖和减速带等特殊路面时,制动与减速时的稳定性与乘坐舒适性较差,为改善这一状况,对悬架的设计提出了更高的要求。为了提高自动驾驶智能汽车制动与减速时的稳定性,通过融合比例积分微分(Proportional Integral Derivative,PID)与模糊算法,设计了针对这些特殊路面的主动悬架模糊PID控制器,在Matlab/Simulink软件中搭建了半车主动悬架仿真模型,通过惯性测量单元(Inertial Measurement Unit,IMU)实车测量了沟渠路面的路面激励信息,并完成仿真试验。结果表明,当自动驾驶智能汽车在C级路面和沟渠路面行驶时,设计的主动悬架模糊PID控制器较单一算法的控制器更有效地降低了车身垂向加速度、车身俯仰角加速度、车轮动载荷和悬架动行程,改善了悬架性能。