Intelligent control for large-scale variable speed variable pitch wind turbines

Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances. Automatic control is crucial for the efficiency and reliability of wind turbines. On the basis of simplified and proper model of variable speed variable pitch wind turbines, the effective wind speed is estimated using extended Kalman filter. Intelligent control schemes proposed in the paper mchde two loops which operate in synchronism with each other. At below-rated wind speed, the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture. At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power. The simulation shows the effectiveness of the intelligent control.     

Fault-tolerant control of variable speed limits for freeway work zone using likelihood estimation

Freeway work zone with lane closure can lead to disruption to local traffic and cause significant impacts on mobility, safety and environmental sustainability. To mitigate traffic congestion near work zone area, many variable speed limits (VSL) control approaches have been developed. However, VSL control system, as a critical transportation management system, is prone to the occurrence of traffic sensor faults. Faulty sensors can cause great deviations of traffic measurements and system degradation. Therefore, this study aims to develop a fault-tolerant VSL control strategy for freeway work zone with the consideration of the mainline sensor fault and ramp sensor fault. To analyze the traffic dynamics near work zone area, a traffic flow model has been built first. Then a sliding mode controller in the previous study has been utilized for VSL control. In addition to the traffic states estimated by a Kalman filter, two observers have been developed to provide analytical redundancy of traffic states estimation. By comparing the logarithm of the likelihood estimations from the Kalman filter and two observers, a fault diagnosis scheme has been designed to detect and identify the faults of mainline sensors and ramp sensors. Then the VSL controller can be reconfigured accordingly in case of sensor faults. The proposed system is implemented and evaluated under a realistic freeway work zone environment using traffic simulator SUMO. The results demonstrate that the developed system can accurately detect and identify the sensor faults in real time. Consistent improvements of mobility, safety and sustainability are also achieved under fault-free and sensor faults scenarios.     

Lyapunov-based feedback design and experimental verification of IC engine speed control

In this paper, the speed control problem of internal combustion engines is investigated based on mean-value engine models. The dynamics of internal combustion engines is a complicated nonlinear system, and usually, it is difficult to know the exact values of the physical parameters. First, a Lyapunov-based design method is shown without requiring the full information of the physical parameters. Then, to improve transient performance, the design method is extended to several cases under different operation conditions. Numerical simulation results are presented for comparing the proposed design methods. Finally, experiments are conducted on an engine test bench and the results demonstrate the validity of the proposed design methods. Recommended by Editorial Board member Myotaeg Lim under the direction of Editor Hyun Seok Yang. The authors are grateful to Kai Zheng for his assistance of the model identification experiments. Jiangyan Zhang received the B.E. and M.E. degrees in Electrical Engineering, Yanshan University, China, in 2005 and 2008, respectively. Now, she is a Ph.D. candidate with the Department of Engineering and Applied Sciences, Sophia University, Tokyo, Japan. Her current research interests include nonlinear system control theory and applications to powertrain system control. Tielong Shen received the Ph.D. degree in Mechanical Engineering from Sophia University, Tokyo, Japan, March, 1992. From April 1992, he has been a faculty member of the Chair of Control Engineering in Department of Mechanical Engineering, Sophia University, where he currently serves as professor of the Department of Engineering and Applied Science. His research interests include control theory and application in mechanical systems, power systems, and automotive powertrain. Currently, he is an Associate Editor for the IEEE Control System Society Conference Editorial Board, and is serving as Associate Editor of Journal of Control Theory and Applications, and the Regional Editor Asia-Pacific for International Journal of Modeling, Identification and Control etc. Junichi Kako received the B.E. degree from Nagoya Institute of Technology, Nagoya, Japan. He joined Toyota Motor Corporation, Tokyo, Japan in 1989. He worked on various aspects of automotive powertrain control. From 1989 to 1994, he took part in the team for the development of Laboratory Automation (LA) system, Engineering Office Automation (EOD) system, and embedded system of powertrain control. During 1995–2001, he focused on the engine control systems in Powertrain Management Engineering Division. In 2002, he was with Future Project Division in which he was responsible for the R&D of model-based engine control system. Currently, he is developing engine control systems in the Powertrain Management Engineering Division, Toyota Motor Corporation. Shozo Yoshida received the M.S. degree in Engineering from Kyoto University, Kyoto, Japan. He joined Toyota Motor Corporation, Tokyo, Japan in 2000. From 2000 to 2004, he was with Future Project Division and worked on physical combustion modeling for Model-based Control Development. Since 2005, he has been with the Powertrain Management Engineering Division Toyota Motor Corporation, and is a member of the R&D of Model-based Engine Calibration.     

废气再循环–可变几何截面涡轮增压柴油发动机 燃气双环系统建模及协同控制

针对废气再循环(EGR)与可变几何截面涡轮增压(VGT)的柴油发动机,作者联合考虑其燃油动力转速调节回路与气体回路,提出了内外双环稳定动态反馈的控制策略.其中,内环回路是利用Lyapunov函数设计的控制器,控制燃油质量流量来跟踪柴油发动机转速;外环回路则设计EGR–VGT控制器,跟踪气体回路的进排气歧管压力及压气机空气质量流量,并克服了柴油发动机建模中的不稳定零动态问题.同时,研究了气体流量与EGR和VGT阀门开度之间的关系,通过设计流量开度转换模块实现了两者控制的转换.最后,通过专业发动机软件AMESim与仿真软件MATLAB/Simulink的联合仿真试验,验证了该控制策略对柴油发动机燃油动力转速调节与气体回路控制的有效性.     

船舶电站柴油机双脉冲H∞调速器的研究

船舶电力系统频率的稳定性主要取决于船舶电站柴油机调速系统的转速响应特性．为了抑制负荷的扰动,提高柴油机双脉冲调速器的动态精度,本文将H_∞控制理论应用于柴油机调速系统的设计,将系统的性能要求转化为标准H_∞控制问题．建立了采用双脉冲H_∞调速器的柴油机调速系统的数学模型,针对外部干扰和模型的不确定性,双脉冲H_∞调速器的设计可以归结为混合灵敏度问题．计算机仿真实验结果表明,本文设计的双脉冲H_∞调速器能在充分考虑系统模型不确定性的情况下,有效提高系统的动态精度和抑制扰动的能力,改善船舶电力系统频率的稳定性．     

高速公路主线限速与匝道融合的协调控制

为缓解高速公路的交通拥挤,主线限速、匝道融合等常被应用,因主线限速和匝道融合经各自优化获得的控制策略可能存在矛盾,故二者协调是必须的,而如何建立和求解二者的协调控制模型还没有有效方法.本文基于宏观交通流理论和多agent技术研究了此协调控制问题.为此首先阐述了高速公路的一般宏观交通流模型;然后分析主线限速、匝道融合的交通特性,建立了主线限速-匝道融合交通流模型;并协调主线限速和匝道融合,建立了协调控制模型.最后,基于多agent技术和分层递阶结构提出了协调控制模型的求解算法,并给出了应用此方法控制仿真高速公路的一个实例.     

船舶电站柴油机双脉冲H∞调速器的研究

船舶电力系统频率的稳定性主要取决于船舶电站柴油机调速系统的转速响应特性.为了抑制负荷的扰动, 提高柴油机双脉冲调速器的动态精度, 本文将H_∞控制理论应用于柴油机调速系统的设计,将系统的性能要求转化为标准H_∞控制问题.建立了采用双脉冲${\rm H}_\infty$调速器的柴油机调速系统的数学模型,针对外部干扰和模型的不确定性, 双脉冲H_∞调速器的设计可以归结为混合 灵敏度问题.计算机仿真实验结果表明, 本文设计的双脉冲H_∞调速器能在充分考虑系统模型不确定性的情况下,有效提高系统的动态 精度和抑制扰动的能力,改善船舶电力系统频率的稳定性.     

柴油机的模糊PID调速控制策略研究

研究了一种基于模糊PID算法的柴油机调速控制策略。提出了一种模糊控制改进算法,对电子调速器PID参数按调速系统过渡过程进行在线实时模糊自整定。Matlab/Simulink仿真结果表明,该系统超调量控制效果明显得到改善,动、静态控制效果要好于常规PID控制,具有控制灵活、响应速度快和适应性强等优点。     

Adaptive coordinated control of engine speed and battery charging voltage

In this paper, the control problem of auxiliary power unit (APU) for hybrid electric vehicles is investigated.An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the powerconverter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.     

Adaptive coordinated control of engine speed and battery charging voltage

In this paper, the control problem of auxiliary power unit （APU） for hybrid electric vehicles is investigated. An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the power-converter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.     

Power conversion optimization for hydraulic systems controlled by variable speed drives

Pumps are widely used in various domestic and industrial applications, such as in water and waste water, food and beverage, and oil and gas applications. In most cases, a pump is controlled by an asynchronous motor which converts the electrical power into the mechanical power required for the pump operation. The motor can be either connected directly to the mains (DOL) or controlled by a variable speed drive (VSD). The energy management of a global pumping system becomes very important to reduce the energy cost of the installations and optimize the maintenance cost, for instance, by increasing the lifetime of the equipment. A VSD is essential to increase the energy efficiency of the overall pump system. A VSD allows delivering all possible mechanical working points (speed, torque), and consequently, only the mechanical power required by the system. Furthermore, a VSD plays an important role in optimizing the electrical energy consumed by the motor as a function of the mechanical energy provided to the pump. This is achieved by minimizing the electrical heat energy losses. In this paper, we propose an original method for electrical energy optimization for a complete pump system including a motor and drive. The objective is to determine the optimal pump speed that minimizes the electrical energy consumption for a hydraulic operating system point. We model the system including a VSD, a motor, a pump, and the hydraulic application. Subsequently, we define the process optimization problem for a single pump and multiple pumps systems. For the single pump system, we demonstrate that the solution of the optimization problem is equivalent to minimization of the drive and motor losses. For the multiple pumps system, we show that we must also optimize the pump losses. For the hydraulic system using multiple pumps, the process demand is actually shared between these pumps. Thus, the speed of each pump is set such that the total energy consumption of the global pumping system is optimized. The simulation and experimental results exhibit the relevance of this power optimization approach for hydraulic pumping systems.     

Nonlinear internal model controller design for wastegate control of a turbocharged gasoline engine

Internal Model Control (IMC) has a great appeal for automotive powertrain control in reducing the control design and calibration effort. Motivated by its success in several automotive applications, this work investigates the design of nonlinear IMC for wastegate control of a turbocharged gasoline engine. The IMC design for linear time-invariant (LTI) systems is extended to nonlinear systems. To leverage the available tools for LTI IMC design, the quasi-linear parameter-varying (quasi-LPV) models are explored. IMC design through transfer function inverse of the quasi-LPV model is ruled out due to parameter variability. A new approach for nonlinear inversion, referred to as the structured quasi-LPV model inverse, is developed and validated. A fourth-order nonlinear model which sufficiently describes the dynamic behavior of the turbocharged engine is used as the design model in the IMC structure. The controller based on structured quasi-LPV model inverse is designed to achieve boost-pressure tracking. Finally, simulations on a validated high-fidelity model are carried out to show the feasibility of the proposed IMC. Its closed-loop performances are compared with a well-tuned PI controller with extensive feedforward and anti-windup built in. Robustness of the nonlinear IMC design is analyzed using simulations.     

Soft sensor design for variable time delay and variable sampling time

Often industrial variables can be difficult to measure due to such factors as extreme conditions or complex compositions. In such cases, soft sensors have been developed that use available system information and measurements to estimate these difficult-to-obtain variables. In practice, the measurements that are to be estimated by a soft sensor are often infrequently measured or delayed. Occasionally, these sampling times or delays are time varying. At present, most research has considered these parameters to be time invariant, and thus, there is a need to consider the time-varying case. Therefore, this paper will evaluate the impact of time-varying delays and sampling times for the design of a data-driven soft sensor. Modifications will be proposed that will increase the robustness and performance of the soft sensor. The reliability of the estimate will be shown using the Bauer–Premaratne–Durán Theorem. Furthermore, the proposed soft sensor system will be tested using simulations of a continuous stirred tank reactor (CSTR) and an reverse osmosis plant. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate for the CSTR and reverse osmosis plant.     

Linear parameter varying PID controller design for charge control of a spark-ignited engine

This paper presents the design and experimental test of a fixed-structure LPV controller for the charge control of a spark-ignition engine. A nonlinear model of the plant is transformed into an affine LPV model in the form of an LFT representation. Using a hybrid evolutionary-algebraic synthesis approach that combines LMI techniques based on K-S iteration with evolutionary search, a scheduled PID controller is designed. To reduce conservatism, the technique of quadratic separators is used in the analysis step. To improve tracking behavior, the gain scheduled feedback controller is supported by an LTI feedforward controller. The controller has been implemented on a standard electronic control unit, and experimental results on a test car illustrate that it meets the performance requirements in a wide range of operation.     

Robust control design of an air‐breathing engine for a supersonic vehicle using backstepping and UKF

This paper presents an efficient robust control design approach for an air‐breathing engine for a supersonic vehicle using the Lyapunov stability theory based nonlinear backstepping control, augmented with unscented Kalman filter (UKF). The primary objective of the control design is to ensure that the thrust produced by the engine tracks the commanded thrust by regulating the fuel flow to the combustion chamber. Moreover, as the engine operates in a supersonic range, an important secondary objective is to manage the shock wave location in the intake for maximum pressure recovery with adequate safety margin by varying the throat area of the nozzle simultaneously. To estimate the states and parameters as well as to filter out the process and sensor noises, a UKF has been incorporated for robust output feedback control computation. Furthermore, independent control designs for the actuators have been carried out to assure satisfactory performance of the engine. Additionally, a guidance loop is designed to generate a typical flight trajectory of the representative vehicle using a nonlinear suboptimal input constrained model predictive static programming formulation for testing the performance of the engine. Simulation results clearly indicate quite successful robust performance of the engine during both climb and cruise phases.     

变循环发动机部件法建模及性能仿真

在变循环发动机部件建模优化的研究中,双涵道变循环发动机具有多个参数可调的几何部件,所有部件的可调参数和固定参数必须满足一定的匹配关系,才能使变循环发动机正常工作,为整机建模、性能仿真以及求解设计点参数带来了一定的困难。为解决上述问题,提出将各部件视为独立整体,采用部件法自底向上构建部件级模型,并构建整机的变几何稳态仿真系统,仿真执行亚音速巡航和超音速巡航两种典型工作模式。结合7个发动机平衡方程,提出一种"先全局后局部"的改进式迭代算法来求解两种模式下的设计点参数。仿真结果表明,使用部件法建模具有很高的灵活性,有利于模型的修改和扩展;使用改进式迭代算法能够更快更精确的得到设计点参数。     

A physical model for engine control design via role state variables

The present paper describes a model representation of the multi-cyclic phenomena of a multi-cylinder engine system. The model is simplified for the implementation of a practical engine controller. The simplified model is described by physically meaningful state variables, which enables controller designers to effectively consider practical objectives and constraints. The proposed approach consists of two steps. First, an approximate analytical discrete-crank angle model, which is a periodic state equation, is derived from the gas equations, the conservation laws, and the motion dynamics. Second, the concept of role state variables is proposed to transform the periodic state equation into a time-invariant state equation. The stabilizability and detectability of the time-invariant state equation are shown to be equivalent to those of the periodic state equation. The time-invariant state equation is used to design cold start feedforward and feedback controllers.     

基于模糊自整定PID开关磁阻电机速度控制系统的建模与仿真研究

在Matlab 2008a/Simulink环境下,建立了三相(6/4极)的开关磁阻电机的速度控制系统动态仿真模型,对基于模糊自整定PID的开关磁阻电机速度控制系统进行了仿真研究,并与基于常规PID的开关磁阻电机速度控制系统仿真结果进行了对比。对比结果表明,采用模糊自整定PID控制算法,系统速度控制性能明显优于常规PID控制算法。     

车用汽油发动机电子控制系统研究现状与展望

发动机电子控制系统是高性能、高可靠性发动机开发的核心研究内容,是保证发动机动力性、经济性和排放性的重要因素之一.针对车用汽油发动机,本文首先分析了典型的车用汽油发动机电子控制系统结构,然后围绕电子节气门控制系统、燃油喷射控制系统、点火控制系统、空燃比控制系统、怠速控制系统、涡轮增压控制系统、爆震检测与控制系统以及汽油机先进燃烧模式控制这8项关键问题展开论述,并着重介绍了近年来国内外的研究内容和研究成果.最后对车用汽油发动机电子控制系统的发展前景和发展方向进行了展望.     

Modeling and control of the air system of a turbocharged gasoline engine

In order to reduce CO₂ emissions in the automotive industry, there is a trend to decrease the size of the engines and add turbocharging technologies to increase the engine efficiency while keeping performances. In this context, numerous studies have focused on the improvement of turbocharger control strategies. The strategy proposed in this paper is based on constrained motion planning and feedback linearization applied to a simplified model of the system. It takes advantage of the whole system bandwidth and requires a limited calibration effort. Thanks to its structure, it offers an interesting potential for generalization to more complex turbocharging systems. Extensive experimental tests are reported for a four-cylinder gasoline engine.