大推力氢氧补燃发动机推力闭环控制设计

提出了大推力氢氧补燃发动机推力闭环控制系统的软硬件平台,为建立液体火箭发动机综合控制系统奠定了坚实的基础。首先,建立了氢氧补燃发动机实时动态非线性模型,在此基础上得到了设计点线性化模型并验证;其次,在线性模型的基础上采用根轨迹法设计了推力闭环控制器,将控制器与非线性模型联合仿真验证了算法的有效性;最后,介绍了发动机硬件在回路系统的软硬件配置,并进行了控制器的平台验证,从操作和实现方式上验证了软硬件平台。该设计满足算法需求且界面人性化,易于操作。     

某特种动力发动机控制器设计

以某特种固体火箭发动机研制为工程应用背景,基于DSP+ FPGA主协处理器方案设计了发动机控制器,安全可靠地完成了发动机转级控制,基于PID控制方案实现燃气发生器压强闭环控制.该发动机控制器完成了大量发动机地面试车试验.试验结果表明系统具有使用方便、稳定性高等特点,为该发动机的探索研究建立起了工程实用的压强控制实验装置.     

模糊自适应整定PID在航空发动机中的应用研究

模糊控制对于解决模型不确定性问题具有较好的优势。对于航空发动机这样复杂的系统,其数学模型具有较大的不确定性,经典的PID算法难以对其实现良好控制。因此,运用模糊控制理论就具有较好的实践意义。该文将模糊控制与自适应控制理论相结合,运用模糊推理方法,实现了对PID参数的在线最佳调整。最后,通过数字仿真,对比了经典PID控制和运用模糊自适应控制的PID,证明了其在航空发动机控制中应用的可能性。     

Nonlinear Fly‐By‐Throttle H∞ Control Using Neural Networks

A neural network approach to gain scheduling H∞ controllers for propulsion controlled aircraft (PCA) systems is introduced. The PCA system is applied to backup control of aircraft experiencing control surface failure. The H∞ technology is applied to the problem of matching the crippled aircraft and the nominal model. Various H∞ controllers at various flight conditions are used to train radial basis function networks (RBFN), which can then be used as the nonlinear controller. Simulation on an L‐1011 under fly‐by‐throttle control demonstrates that the RBFN controller can stabilize the crippled airplane to obtain the desired model and possesses robustness against the engine delay.     

水下涡轮发动机推进系统闭环控制设计

水下航行器涡轮发动力推进系统在偏离设计工况时敏感性大,因而对涡轮机动力系统实施转速闭环控制具有重要意义;从系统物理特性、可实现性出发,通过分析涡轮机动力系统工作机理,建立了适用于系统特性和控制律综合的系统数学模型,利用燃料泵排量闭环控制的控制方法,获得了针对工质秒耗量的控制律,完成了涡轮机推进系统闭环控制设计;仿真计算结果表明,控制方法能够较好地兼顾系统的运行效率和平稳性,且在整个工况变动范围内控制律满足设计指标要求。     

基于二自由度PI的微型涡喷发动机转速闭环控制

针对传统PI控制无法使微型涡喷发动机的扰动抑制性能与设定值跟踪性能同时最佳的问题,开展了微型涡喷发动机二自由度（Two-Degree-of-Freedom,2-DOF）PI控制研究。首先基于Speedgoat实时目标机搭建了快速原型试验系统。根据发动机开环试验数据辨识得到不同稳态点下的传递函数模型,在此基础上设计了2-DOF PI控制器,并进行仿真验证。最后将控制算法部署至Speedgoat中开展实物试验。结果表明,设计的2-DOF PI控制器能够使微型涡喷发动机的扰动抑制性能与设定值跟踪性能同时最佳,并在发动机较大的工作范围内有良好的控制性能。     

基于PSO-PID的盾构机纠偏控制研究

针对盾构机在掘进过程中容易受到复杂地质条件以及负载多变的影响,从而导致前进方向发生偏离,难以控制的情况。提出一种基于粒子群算法(Particle Swarm Optimization)优化PID控制器参数的纠偏控制策略。首先,研究盾构机液压推进系统机理,建立液压缸推力、盾构机所受阻力、阻力矩、液压缸位移之间的关系模型,得到盾构机液压推进系统模型,然后结合PSO和PID控制理论,设计了以液压推进系统的纠偏控制器。仿真结果显示,所设计的PSO-PID控制器能够满足纠偏控制的需要,具有更小的超调性能,可以实现纠偏控制的快速响应。     

Robust Surge Avoidance Control for a Low Pressure Compressor of a Turbojet Engine

The aim of this paper is to improve the efficiency of a low pressure compressor within a turbojet engine. For this purpose a new feedback controller will be introduced which compares the actual compressor surge margin to a given reference value. Then, this new feedback controller calculates a deviation on the existing nozzle area schedule such that the overall efficiency of the controller is improved at steady state condition. The major contribution of this work consists in a robust control design approach leading to improved robustness properties and reduced calibration efforts for the controllers of future unmanned aircraft propulsion systems.     

Delay-dependent guaranteed cost control for state-delayed system with disturbance and its application to engine idle speed control

This paper proposes a delay-dependent guaranteed cost control scheme for engine idle speed control （ISC） with induction-to-torque delay and external load disturbance. An augmented linearization model of engine at idle speed operating mode was developed based on physical principle and experiment data. To provide a compromise between disturbance rejection and other performance requirements of ISC, a multi-objective cost function upper bound was given, which can help us to take into account the fuel economy and disturbance rejection performance together in ISC. Poles constraint was added to the closed-loop system to guarantee convergence rates of state. The whole optimization solution to ISC can be solved under the framework of LMI. A commercial engine model was utilized to assess the performance of the controller. Simulation results on this model show us that designed controller can achieve desired performance.     

Direct multivariable controller tuning for internal combustion engine test benches

Dynamical test benches are typically used in the development phase of engine systems and require tracking controllers with a high performance. Unfortunately, during such a work the components or operation parameters of the engine system are changed very frequently, making the use of classical model based control approaches very time-consuming. Against this background, this paper proposes a direct data-driven design approach for multivariable control of rotational speed and shaft torque of an internal combustion engine at a test bench based on an extended version of a recently introduced method for non-iterative direct data-driven tuning of multivariable controllers. This extension allows employing data collected in a closed-loop experiment in the direct identification of the controller parameters. The effectiveness of the proposed approach is shown on a test bench equipped with a production light duty Diesel engine. A comparison with the industrial state-of-the-art controller is provided on both a dynamically challenging test and a typical driving cycle as measured on an instrumented vehicle with the same internal combustion engine. The results confirm that the new method recovers the performance of the well-tuned industrial control, but can be developed in a fraction of the time as no explicit model of the system is needed.     

A hardware-in-the-loop dynamics simulator for motorcycle rapid controller prototyping

The purpose of this research is to develop an innovative hardware-in-the-loop simulator for the purpose of motorcycle power train rapid controller prototyping. Proposed control algorithms can be validated using the developed setup. Such an in-lab validation saves time and development cost and thus is preferable during power train controller development process. The developed simulator includes an engine, a transmission, and a rear wheel from a real motorcycle. A powder brake is rigidly coupled to the rear wheel for road loading generation. A central computer is used to control the operation of the system and the measurement of system dynamics variables. An xPC system is also integrated in the system to provide the feasibility of power train control algorithm rapid prototyping. Comparison between field tests and simulation results show that the simulator can be used to evaluate the performance of different control algorithms for controller rapid prototyping in the laboratory. An example of power train control algorithm development featuring engine fuel injection control using the above rapid prototyping setup is also described.     

Neural Network Controller Development and Implementation for Spark Ignition Engines With High EGR Levels

Past research has shown substantial reductions in the oxides of nitrogen (NO_x) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate control loop was designed for controlling EGR levels. The stability analysis of the closed-loop system is given and the boundedness of the control input is demonstrated by relaxing separation principle, persistency of excitation condition, certainty equivalence principle, and linear in the unknown parameter assumptions. Online training is used for the adaptive NN and no offline training phase is needed. This online learning feature and model-free approach is used to demonstrate the applicability of the controller on a different engine with minimal effort. Simulation results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller when implemented on an engine model that has been validated experimentally. For a single cylinder research engine fitted with a modern four-valve head (Ricardo engine), experimental results at 15% EGR indicate that cyclic dispersion was reduced 33% by the controller, an improvement of fuel efficiency by 2%, and a 90% drop in NO_x from stoichiometric operation without EGR was observed. Moreover, unburned hydrocarbons (uHC) drop by 6% due to NN control as compared to the uncontrolled scenario due to the drop in cyclic dispersion. Similar performance was observed with the controller on a different engine.     

一种面向异构并行系统的最大功耗管理方法

高功耗已成为制约高性能计算机发展的重要问题之一.近年来,大量研究关注于如何在满足系统功耗约束的条件下优化系统执行性能.然而,已有方法大都针对同构系统,未考虑异构处理器之间的功耗或速度差异,难以高效应用于基于加速器的异构系统.对当前异构并行系统执行模型进行了抽象,并提出了融合两级功耗控制机制的系统功耗管理框架,自顶向下依次为系统级功耗控制器和异构处理引擎功耗控制器.在异构处理引擎功耗控制中,针对类OpenMP 并行循环,首先分析了异构多处理器在满足功耗约束条件下达到性能最优的条件.基于该结果,给出了功耗受限的并行循环划分算法,该方法通过协调并行循环调度和动态电压频率调节技术以优化异构并行处理.在系统级功耗控制中,建立了异构处理引擎效能评估方法,以此作为功耗划分的依据,在兼顾并发应用公平性的同时,提高系统整体执行效能.最后,基于典型CPU-GPU 异构系统验证了方法的有效性.     

On the supremal controllable sublanguage in the discrete-eventmodel of nondeterministic hybrid control systems

This paper is concerned with the logical control of hybrid control systems (HCS). It is assumed that a discrete-event system (DES) plant model has already been extracted from the continuous-time plant. The problem of hybrid control system design can then be solved by applying logical DES controller synthesis techniques to the extracted DES plant. Traditional DES synthesis methods, however, are not always applicable since the extracted plant DES will often exhibit nondeterministic transitions. This paper presents an extension of certain DES controller synthesis techniques to the nondeterministic control automaton found in HCS. In particular, this paper derives a formula computing the supremal controllable sublanguage of a given specification language under the assumption that the DES plant exhibits nondeterministic transitions     

Fuzzy logic based full-envelope autonomous flight control for an atmospheric re-entry spacecraft

An intelligent and autonomous flight control system for an atmospheric re-entry vehicle is investigated, based on fuzzy logic control and aerodynamic inversion computation. A common PD-Mamdani fuzzy logic controller is designed for all the five re-entry flight regions characterized by different actuator configurations. A linear transformation to the controller inputs is applied to tune the controller performance for different flight regions while using the same fuzzy rule base and inference engine. An autonomous actuator allocation algorithm is developed, based on the aerodynamic inversion computation, to cover all the five actuator configurations with the same fuzzy logic controller. Simulation results of tracking both a bench mark trajectory and a given nominal re-entry trajectory are presented to evaluate the control performance.     

Model based approach to closed loop control of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts to assess performance and therefore determine suitable hardware. The transient response is a key driver in the selection process which in most cases requires closed loop control of the model to ensure operation within prescribed physical limits and tracking of reference signals. Since the controller effects the system performance a systematic procedure which achieves close-to-optimal performance is desired, if the full potential of a given hardware configuration is to be properly assessed. For this purpose a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). The system is also tested for operation at high altitude conditions to demonstrate the ability of the controller to respect specified physical constraints. As an example this study is focused on the transient response of a light-duty automotive Diesel engine. For the cases examined the proposed controller design gives a more systematic procedure than other ad hoc approaches that require considerable tuning effort.     

Adaptive internal model control with application to fueling control

This paper presents an adaptive internal model controller for stable but not necessarily minimum-phase SISO plants and its application to the air/fuel ratio control system of a spark-ignited engine. The internal model of the controller is formulated in an output-error structure that can be adapted by using standard adaptive laws. The method is applied to an air/fuel ratio control system with a reduced-order internal model and unknown sensor dynamics. Experiments on an engine test bench demonstrate the capability of the adaptive controller to recover the performance and robustness properties of the control system in the case of an aged oxygen sensor.     

Multi-objective model-based control for an automotive catalyst

A model-based feedforward/feedback air fuel ratio controller that optimizes the oxygen storage capacity of the three-way catalyst in automotive emission control systems is presented. This work incorporates a simplified dynamic catalyst model that describes the physical behavior of oxygen chemisorption and reversible deactivation in the catalyst system. A novel aspect of this work is the use of the oxygen storage capability of the catalyst not only to minimize vehicle emissions but also to optimize engine performance and fuel economy during transient engine demand. The feedback/feedforward controller is a nonlinear model predictive controller that incorporates catalyst, engine air fuel ratio controller, and fuel system models to determine the optimal air fuel ratio target trajectory. Feedback is provided by a nonlinear moving horizon estimation strategy for the determination of the oxygen storage level of the catalyst based on air fuel ratio sensors.     

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.     

Backstepping sliding mode control with functional tuning based on an instantaneous power approach applied to an underwater vehicle

In this paper, we present a modified backstepping sliding mode control to deal with Euler–Lagrange systems. The controller is applied in an underwater vehicle in order to show the effectiveness of the approach proposed. Instantaneous power data provided by the propulsion system are used to tune the controller in order to guarantee robust performance and energy saving. Thanks to the combination of an internal Proportional Integral and Derivative (PID) controller, it is possible implement high gains to deal with the influence of disturbances and uncertainties. A comparative study among this backstepping sliding mode controller and standard sliding mode controls is presented.