Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-di...Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.展开更多
The control problem of trajectory based path following for passenger vehicles is studied. Comprehensive nonlinear vehicle model is utilized for simulation vehicle response during various maneuvers in MATLAB/Simulink. ...The control problem of trajectory based path following for passenger vehicles is studied. Comprehensive nonlinear vehicle model is utilized for simulation vehicle response during various maneuvers in MATLAB/Simulink. In order to follow desired path, a driver model is developed to enhance closed loop driver/vehicle model. Then, linear quadratic regulator(LQR) controller is developed which regulates direct yaw moment and corrective steering angle on wheels. Particle swam optimization(PSO) method is utilized to optimize the LQR controller for various dynamic conditions. Simulation results indicate that, over various maneuvers, side slip angle and lateral acceleration can be reduced by 10% and 15%, respectively, which sustain the vehicle stable. Also, anti-lock brake system is designed for longitudinal dynamics of vehicle to achieve desired slip during braking and accelerating. Proposed comprehensive controller demonstrates that vehicle steerability can increase by about 15% during severe braking by preventing wheel from locking and reducing stopping distance.展开更多
This paper focuses on the dynamic control of distillation column with side reactors(SRC) for methyl acetate production. To obtain the optimum integrated structure and steady state simulation, the systematic design app...This paper focuses on the dynamic control of distillation column with side reactors(SRC) for methyl acetate production. To obtain the optimum integrated structure and steady state simulation, the systematic design approach based on the concept of independent reaction amount is applied to the process of SRC for methyl acetate production. In addition to the basic control loops, multi-variable model predictive control modular with methyl acetate concentration and temperature of sensitive plate is designed. Then, based on process simulation software Aspen Plus, dynamic simulation of SRC for methyl acetate production is used to verify the effectiveness of the control scheme.展开更多
This study argues a dynamic optimal control approach for nonlinear systems with state and input delays.First,a feedback system identical to the delayed system is specified based on parallel control,enabling the dynami...This study argues a dynamic optimal control approach for nonlinear systems with state and input delays.First,a feedback system identical to the delayed system is specified based on parallel control,enabling the dynamic optimal control issue to be formulated in light of the L2 gain condition.The virtual controller developed using the backstepping integral technique makes the dynamic control feasible,with its design highlighting inertial-like features,so that the response speed of controller can be altered.Then,the optimal control of the physical system is further expanded to that of the augmented system composed of it,accomplishing the control goal through virtual and actual interaction.In the implementation,the critic-actor structure facilitates the control challenge to be settled online.Additionally,the stability of the system and the convergence of neural network weights are discussed,and the research conclusions are supported by simulation examples.展开更多
基金Supported by the National Natural Science Foundation of China(61333010,61134007and 21276078)“Shu Guang”project of Shanghai Municipal Education Commission,the Research Talents Startup Foundation of Jiangsu University(15JDG139)China Postdoctoral Science Foundation(2016M591783)
文摘Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.
文摘The control problem of trajectory based path following for passenger vehicles is studied. Comprehensive nonlinear vehicle model is utilized for simulation vehicle response during various maneuvers in MATLAB/Simulink. In order to follow desired path, a driver model is developed to enhance closed loop driver/vehicle model. Then, linear quadratic regulator(LQR) controller is developed which regulates direct yaw moment and corrective steering angle on wheels. Particle swam optimization(PSO) method is utilized to optimize the LQR controller for various dynamic conditions. Simulation results indicate that, over various maneuvers, side slip angle and lateral acceleration can be reduced by 10% and 15%, respectively, which sustain the vehicle stable. Also, anti-lock brake system is designed for longitudinal dynamics of vehicle to achieve desired slip during braking and accelerating. Proposed comprehensive controller demonstrates that vehicle steerability can increase by about 15% during severe braking by preventing wheel from locking and reducing stopping distance.
基金Supported by the National Natural Science Foundation of China(61673205,61503181,21727818)National Key R&D Program of China(2017YFB0307304)+1 种基金the Natural Science Foundation of Jiangsu Province(BK20141461,BK20140953)the State Key Laboratory of Materials-Oriented Chemical Engineering Open Subject(kl16-07)
文摘This paper focuses on the dynamic control of distillation column with side reactors(SRC) for methyl acetate production. To obtain the optimum integrated structure and steady state simulation, the systematic design approach based on the concept of independent reaction amount is applied to the process of SRC for methyl acetate production. In addition to the basic control loops, multi-variable model predictive control modular with methyl acetate concentration and temperature of sensitive plate is designed. Then, based on process simulation software Aspen Plus, dynamic simulation of SRC for methyl acetate production is used to verify the effectiveness of the control scheme.
基金supported by the National Key R&D Program of China(Nos.2024YFB4709100 and 2021YFE 0206100)the National Natural Science Foundation of China(Nos.62425310 and 62073321)+1 种基金the National Defense Basic Scientific Research Program(Nos.JCKY2019203C029 and JCKY2020130C025)the Science and Technology Development Fund,Macao SAR(Nos.FDCT-22-009-MISE,0060/2021/A2,and 0015/2020/AMJ).
文摘This study argues a dynamic optimal control approach for nonlinear systems with state and input delays.First,a feedback system identical to the delayed system is specified based on parallel control,enabling the dynamic optimal control issue to be formulated in light of the L2 gain condition.The virtual controller developed using the backstepping integral technique makes the dynamic control feasible,with its design highlighting inertial-like features,so that the response speed of controller can be altered.Then,the optimal control of the physical system is further expanded to that of the augmented system composed of it,accomplishing the control goal through virtual and actual interaction.In the implementation,the critic-actor structure facilitates the control challenge to be settled online.Additionally,the stability of the system and the convergence of neural network weights are discussed,and the research conclusions are supported by simulation examples.
