The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on t...The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.展开更多
A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from...A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from modeling to control synthesis and implementation.The Hybrid System Description Language is used to obtain a mixed-logical dynamical (MLD) model.Based on the MLD model,a model predictive controller is designed for an optimal speed regulation of the motor.For reducing computation complexity and computation time,the MPC controller is converted to its equivalent explicit piecewise affine form by multiparametric programming.Simulations and experiments show that good and robust control performance is achieved by the hybrid model predictive controller as compared with the linear quadratic regulator (LQR) and the PID controller.展开更多
逆变电路传统开关函数模型只能描述电路的控制变迁而忽略了电路的条件变迁,为此,建立了三相逆变电路混合逻辑动态(mixed logical dynamical,MLD)模型。在此基础上,将其作为预测模型,提出了电路的有限控制集模型预测控制(finite control ...逆变电路传统开关函数模型只能描述电路的控制变迁而忽略了电路的条件变迁,为此,建立了三相逆变电路混合逻辑动态(mixed logical dynamical,MLD)模型。在此基础上,将其作为预测模型,提出了电路的有限控制集模型预测控制(finite control set model predictive control,FCS-MPC)策略。FCS-MPC充分考虑了电路的离散特性,选择有限控制集中使目标函数值最小的开关状态作为电路开关管的控制信号,从而控制电路的输出电压,无需任何调制器,可简化MPC的优化问题。此外,基于全维状态观测器设计了电路负载电流观测器,增强了控制器的鲁棒性。仿真和实验结果验证了所提方法的有效性。展开更多
Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （ML...Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （MLD） system and use it in model predictive control （MPC） in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control （MMPC） algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output（MIMO） simulated pH neutralization process.展开更多
In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This ...In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This paper presents a full analysis of a PMSG system for wind turbines(WT)and proposes a fault detection method using correlation features.The proposed method is motivated by the balance among the three-phase currents both before and after an opencircuit fault occurs in a converter of the PMSG system.It is unnecessary to analyze the output waveforms of a converter during fault detection.In this study,two correlation features of stator currents,the mean and covariation,are extracted to train an artificial neural network(ANN),thereby enhancing the performance of the proposed method under different wind speed conditions.Moreover,additional sensors and the collection of a massive amount of data are not required.Model simulations of an ideal inverter and a PMSG system are conducted using PSCAD software.The simulation results show that the proposed method can detect the locations of faulty switches with a diagnostic rate greater than 99.4%for the ideal inverter,and the PMSG drives settings at different wind speeds.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51375212)Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions of China+1 种基金Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133227130001)China Postdoctoral Science Foundation(Grant No.2014M551518)
文摘The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.
基金supported by the Beijing Education Committee Cooperation Building Foundation Project (No. XK100070532)
文摘A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from modeling to control synthesis and implementation.The Hybrid System Description Language is used to obtain a mixed-logical dynamical (MLD) model.Based on the MLD model,a model predictive controller is designed for an optimal speed regulation of the motor.For reducing computation complexity and computation time,the MPC controller is converted to its equivalent explicit piecewise affine form by multiparametric programming.Simulations and experiments show that good and robust control performance is achieved by the hybrid model predictive controller as compared with the linear quadratic regulator (LQR) and the PID controller.
文摘逆变电路传统开关函数模型只能描述电路的控制变迁而忽略了电路的条件变迁,为此,建立了三相逆变电路混合逻辑动态(mixed logical dynamical,MLD)模型。在此基础上,将其作为预测模型,提出了电路的有限控制集模型预测控制(finite control set model predictive control,FCS-MPC)策略。FCS-MPC充分考虑了电路的离散特性,选择有限控制集中使目标函数值最小的开关状态作为电路开关管的控制信号,从而控制电路的输出电压,无需任何调制器,可简化MPC的优化问题。此外,基于全维状态观测器设计了电路负载电流观测器,增强了控制器的鲁棒性。仿真和实验结果验证了所提方法的有效性。
文摘Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （MLD） system and use it in model predictive control （MPC） in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control （MMPC） algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output（MIMO） simulated pH neutralization process.
文摘In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This paper presents a full analysis of a PMSG system for wind turbines(WT)and proposes a fault detection method using correlation features.The proposed method is motivated by the balance among the three-phase currents both before and after an opencircuit fault occurs in a converter of the PMSG system.It is unnecessary to analyze the output waveforms of a converter during fault detection.In this study,two correlation features of stator currents,the mean and covariation,are extracted to train an artificial neural network(ANN),thereby enhancing the performance of the proposed method under different wind speed conditions.Moreover,additional sensors and the collection of a massive amount of data are not required.Model simulations of an ideal inverter and a PMSG system are conducted using PSCAD software.The simulation results show that the proposed method can detect the locations of faulty switches with a diagnostic rate greater than 99.4%for the ideal inverter,and the PMSG drives settings at different wind speeds.
基金韩国国际合作项目(Development of Embedded Software and System for Automobile Electronics)重庆市科技攻关计划项目(CSTC+2 种基金2006AB2026)"面向汽车ABS嵌入式系统的专用开发平台及其应用"国家863计划项目(2006AA11A107-2)节能与新能源汽车-"长安混合动力汽车标定系统开发"国家863计划重点资助项目(2004AA1Z2380)"面向汽车电子控制的嵌入式系统开发平台及其应用"
