A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced eff...A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently.Simplified vector control,which has simple control structure,is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control.The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application.Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances.Furthermore,simplified vector control combined with genetic algorithm has a similar performance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.展开更多
The dividing wall column(DWC) is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control(MPC) is an advanced control strategy that has acquire...The dividing wall column(DWC) is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control(MPC) is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol,n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and temperature inferential control are considered. The multiobjective genetic algorithm function "gamultiobj" in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and temperature inferential control, resulting in a more stable and superior performance with lower values of integral of squared error(ISE).展开更多
Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS con...Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.展开更多
In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator tempera...In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator temperatures of FCCU in order to compare their performances. Control design was formulated as optimization problem to minimize infinity norm of weighted sensitivity functions subject to μ-interaction measure bound on diagonal complementary functions of the closed loop system. The optimization problem was solved using augmented Lagrangian genetic algorithm. Simulation results show that simultaneous and independent designs give good response with less overshoot and with no oscillation. Bound on μ-interaction measure is satisfied for both designs meaning that their nominal stabilities are guaranteed;however, it is marginal for simultaneous design. Simultaneous design outperforms independent design in term of robust performance while independent design gives the best performance in terms of robust stability. Sequential design gives the worst performance out of the three designs.展开更多
由于定风量空调机组(Constant Air Volume Air Handling Unit, CAVAHU)输出的新风量往往是固定的,当空调房间内的额定人员数量超员或不足时,会导致空调房间CO_(2)浓度测量值Cn高于室内CO_(2)浓度设定值Cn=Cn,set或新风负荷增大的状况。...由于定风量空调机组(Constant Air Volume Air Handling Unit, CAVAHU)输出的新风量往往是固定的,当空调房间内的额定人员数量超员或不足时,会导致空调房间CO_(2)浓度测量值Cn高于室内CO_(2)浓度设定值Cn=Cn,set或新风负荷增大的状况。对此提出了一种空调房间CO_(2)浓度二自由度内模分数阶PI控制策略和设计改进多目标人工蜂群算法(Improved Multi-Objective Artificial Bee Colony Algorithm, IMOABCA)对控制器参数实施整定的思路。首先,基于人工蜂群算法,分别对雇佣蜂和观察蜂引入自适应惯性权重和精英组策略,进行非线性递减和柯西变异的演变,并结合观察蜂搜索特性,将最小粒子角度引入外部档案集,获取相应的Pareto解集,设计IMOABCA,进而对控制器的3个参数进行整定,获得相应的最优值。最后,借助MATLAB工具,对该室内CO_(2)浓度的二自由度内模分数阶PI控制系统进行组态和仿真。结果表明:该室内CO_(2)浓度二自由度内模分数阶PI控制系统和IMOABCA是可行的,能够实现Cn=Cn,set的调节目的和获取控制器的3个参数最优值,提升室内CO_(2)浓度的调节品质。展开更多
针对采用直接电流控制策略的电压源换流器(voltage source converter,VSC)控制系统比例积分(PI)参数难以选取的问题,提出了一种优化外环PI控制器参数的方法。首先建立解耦后的外环参数整定模型,然后基于时间乘绝对误差积分(integral of ...针对采用直接电流控制策略的电压源换流器(voltage source converter,VSC)控制系统比例积分(PI)参数难以选取的问题,提出了一种优化外环PI控制器参数的方法。首先建立解耦后的外环参数整定模型,然后基于时间乘绝对误差积分(integral of time multiplied by the absolute value of error,ITAE)准则构造PI参数优化的性能泛函,针对此最优控制模型的特点,论文采用遗传算法进行求解,在PSCAD搭建VSC-HVDC模型进行仿真验证。展开更多
文摘A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently.Simplified vector control,which has simple control structure,is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control.The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application.Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances.Furthermore,simplified vector control combined with genetic algorithm has a similar performance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.
基金Supported by the National Natural Science Foundation of China(21676299,21476261and 21606255)
文摘The dividing wall column(DWC) is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control(MPC) is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol,n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and temperature inferential control are considered. The multiobjective genetic algorithm function "gamultiobj" in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and temperature inferential control, resulting in a more stable and superior performance with lower values of integral of squared error(ISE).
文摘Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.
文摘In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator temperatures of FCCU in order to compare their performances. Control design was formulated as optimization problem to minimize infinity norm of weighted sensitivity functions subject to μ-interaction measure bound on diagonal complementary functions of the closed loop system. The optimization problem was solved using augmented Lagrangian genetic algorithm. Simulation results show that simultaneous and independent designs give good response with less overshoot and with no oscillation. Bound on μ-interaction measure is satisfied for both designs meaning that their nominal stabilities are guaranteed;however, it is marginal for simultaneous design. Simultaneous design outperforms independent design in term of robust performance while independent design gives the best performance in terms of robust stability. Sequential design gives the worst performance out of the three designs.
文摘由于定风量空调机组(Constant Air Volume Air Handling Unit, CAVAHU)输出的新风量往往是固定的,当空调房间内的额定人员数量超员或不足时,会导致空调房间CO_(2)浓度测量值Cn高于室内CO_(2)浓度设定值Cn=Cn,set或新风负荷增大的状况。对此提出了一种空调房间CO_(2)浓度二自由度内模分数阶PI控制策略和设计改进多目标人工蜂群算法(Improved Multi-Objective Artificial Bee Colony Algorithm, IMOABCA)对控制器参数实施整定的思路。首先,基于人工蜂群算法,分别对雇佣蜂和观察蜂引入自适应惯性权重和精英组策略,进行非线性递减和柯西变异的演变,并结合观察蜂搜索特性,将最小粒子角度引入外部档案集,获取相应的Pareto解集,设计IMOABCA,进而对控制器的3个参数进行整定,获得相应的最优值。最后,借助MATLAB工具,对该室内CO_(2)浓度的二自由度内模分数阶PI控制系统进行组态和仿真。结果表明:该室内CO_(2)浓度二自由度内模分数阶PI控制系统和IMOABCA是可行的,能够实现Cn=Cn,set的调节目的和获取控制器的3个参数最优值,提升室内CO_(2)浓度的调节品质。
文摘针对采用直接电流控制策略的电压源换流器(voltage source converter,VSC)控制系统比例积分(PI)参数难以选取的问题,提出了一种优化外环PI控制器参数的方法。首先建立解耦后的外环参数整定模型,然后基于时间乘绝对误差积分(integral of time multiplied by the absolute value of error,ITAE)准则构造PI参数优化的性能泛函,针对此最优控制模型的特点,论文采用遗传算法进行求解,在PSCAD搭建VSC-HVDC模型进行仿真验证。
