基于遗传算法非线性PID的柴油机共轨压力控制

高压共轨柴油机共轨压力随不同工况的调节能力及其压力的稳定性,从根本上影响着柴油机系统的燃油经济性与排放性能;针对共轨压力的控制,给出了在起动、过渡、正常、停机以及故障等工况下的轨压控制策略,设计了带预控制的积分分离非线性PID控制器,采用遗传算法对PID参数进行了在线自适应整定,实现了在不同柴油机工况下对不同轨压变化的优化控制;台架实验结果表明,在不同工况下采取的控制策略是适用的,采用的积分分离技术能减少控制超调,预控制技术能缩短轨压稳定时间并减少轨压波动,遗传算法对非线性PID控制器参数的在线优化,平均可在柴油机起动后6.7s内完成,所设计的非线性PID控制器可把轨压控制偏差稳定在1.4%以下。     

无人驾驶飞行器姿态的非线性扰动抑制控制

本文研究了无人驾驶飞行器(unmanned aerial vehicle,UAV)的姿态跟踪控制问题.针对在飞行器姿态跟踪时存在的系统模型不确定性和外界扰动,提出了一种基于四元数的姿态跟踪控制方法,基于UAV的姿态误差模型分别设计系统的观测器和控制器.首先,以四元数为姿态参数建立系统的非线性误差模型;在此基础之上,设计一种非线性干扰观测器(nonlinear disturbance observer,NDOB)用以在线估计误差模型中的复合扰动,并在控制输入端进行相应的补偿.然后通过设计非线性广义预测控制律设镇定误差系统,实现姿态跟踪.最后基于频域理论分析了非线性干扰观测器的扰动抑制性能.仿真与实验结果表明本文提出的方法在系统存在复合扰动的情况下能使系统姿态有效的跟踪期望值.     

一类互联机器人系统鲁棒分散自适应控制

研究一类存在模型不确定性和外部扰动的互联机器人系统的控制问题.控制器由一般线性控制器,线性自适应控制器和非线性自适应控制器综合构成.通过Lyapunov理论证明设计的鲁棒分散自适应控制器能够有效地克服不确定性对系统的影响,实现闭环系统的渐近轨迹跟踪控制.最后给出一个仿真例子进一步验证控制器的有效性.     

高精度伺服系统的模糊CMAC补偿控制

针对伺服系统存在非线性和参数不确定性,PID等常规控制器几乎无法获得高精度控制性能的问题,提出了一种基于FCMAC的补偿控制器,将其应用于伺服系统的速度闭环控制.FCMAC补偿控制器能够实时在线学习系统的非线性,对参数变化及扰动等因素进行实时补偿.将FCMAC补偿控制器与模型参考跟踪控制结合,能有效地改善伺服系统的鲁棒性.仿真结果进一步表明,该控制策略能降低系统时参数变化和外界扰动等不确定性的灵敏度,即使在持续正弦信号干扰下也具有良好的性能.     

柴油机共轨压力模糊自适应PID控制研究

柴油机高压共轨燃油系统中,共轨压力决定了燃油喷射压力,共轨压力随不同工况的调节能力及其压力的稳定性从根本上影响着系统性能。针对共轨压力控制,设计了模糊PID控制器,增加了积分分离与轨压预控制技术,给出了共轨压力的控制策略和实现方法。通过对PID参数的在线自适应整定,实现了在不同柴油机工况下对不同共轨压力变化的最佳控制。台架实验结果表明,共轨压力随柴油机转速与单次喷油量的增加应相应提高;当柴油机转速较高时,PID控制器应采用较大的控制参数;轨压预控制可有效地减少轨压波动和缩短轨压稳定时间;提出的控制策略和实现方法可把轨压控制偏差稳定在1.7%以下。     

采用扰动估计的气动人工肌肉系统非线性控制

气动人工肌肉系统凭借其材质轻便、输出力大及柔顺性好等优势, 其运动控制研究近年来逐渐成为热点问题. 然而, 气动人工肌肉(pneumatic artificial muscle, PAM)系统所固有的特性(如迟滞、蠕变、非线性时变等), 为其控制方法设计与实现带来了挑战. 考虑到实际工作过程中, 系统往往遭受未知干扰的影响, 本文针对气动人工肌肉系统, 提出了一种基于干扰估计的非线性控制策略, 可在系统存在持续不确定干扰的情况下, 在线进行扰动抑制, 实现精确的跟踪控制. 具体而言, 本文先通过模型变换, 将系统不确定性、未建模动态、外部扰动等处理成集总扰动的形式. 随后, 结合自适应更新律及正则化最小二乘算法, 在线估计未知系统参数及扰动; 在精确扰动代数估计的基础上, 通过所提基于干扰估计的非线性控制器, 消除未知扰动对系统造成的影响, 并确保跟踪误差收敛至零. 此外, 经稳定性分析证明了跟踪误差的渐近收敛性. 最后, 通过硬件实验验证了本文方法的有效性及鲁棒性.     

基于滑模变结构的永磁同步直线电机控制系统研究

永磁同步直线电机具有非线性、耦合性、负载扰动、时变不确定性等特点,简单PID控制很难做到精确的控制.针对永磁同步直线电机PID控制动态响应慢、抗干扰能力差等不足,提出用滑模控制器代替PID控制器的控制策略.实验仿真结果表明,相对于PID控制器,滑模控制器系统在快速性及稳定性方面得到很大的提高.     

DVD循轨重复控制器的设计及参数优化

在DVD循轨伺服控制系统中,碟片的偏心会对循轨误差信号TE(tracking errors)产生周期性的扰动.随着光盘转速的大大提高,该周期扰动会降低激光光头循轨的性能.为了有效的抑制该干扰,DVD循轨伺服控制系统引入了重复控制器.本文在稳定性条件的基础上设计重复控制器并提出参数优化的办法,通过仿真验证重复控制器能显著有效地抑制频率已知周期干扰信号.     

一类具有凸多面体不确定性的非线性变参数系统鲁棒H_(∞)控制EI北大核心CSCD

针对具凸多面体不确定性的非线性变参数(NPV)系统,本文研究了其非线性鲁棒H_(∞)控制问题.基于Lya-punov稳定性理论和多项式平方和(SOS)方法,对该系统设计了非线性鲁棒状态反馈镇定控制器.在此基础上,进一步考虑存在外部扰动情形,给出相应的非线性鲁棒H_(∞)控制可解性条件.该条件以状态和时变参数依赖的线性矩阵不等式形式(LMIs)给出,可借助凸优化工具进行有效检验.最后,通过数值仿真验证了所得方法的有效性和优势.     

基于模型信息的电静液作动器降阶线性自抗扰控制

针对电静液作动器(electro-hydrostatic actuators, EHA)系统存在内外部扰动、参数不确定性和变控制增益等问题,提出一种基于模型信息的降阶线性自抗扰位置控制方法.首先,基于系统模型信息选取控制增益.其次,通过降阶线性扩张观测器对系统总扰动进行估计,并在控制器中加入扰动项进行补偿.利用奇异摄动理论证明所提控制器可使闭环系统是半全局最终一致有界的,并且当观测器带宽足够大时,所提出的控制器理论上可以使系统输出以所需精度跟踪期望轨迹.仿真结果表明,所提控制方法响应速度较快,控制精度较高,对外部扰动和参数不确定性具有较强的鲁棒性.     

Terminal sliding mode control of rail pressure for gasoline direct injection engines

The desired fuel rail pressure is a crucial factor for guaranteeing the gasoline direct injection (GDI) engine to work stably. In order to solve the rail pressure control problem, the detailed nonlinear model of GDI is derived and reasonable simplification of this model is carried out for the following controller design. Terminal sliding mode control strategy is proposed to design the rail pressure controller with Lyapunov stability. The designed approach with the fast terminal sliding mode surface makes the system have the capacity of global fast convergence and achieves precise tracking control. To demonstrate the validity of the designed control method, simulations are conducted by tracking the different reference rail pressures. Results show that the designed controller tracks the given reference accurately and has strong robustness.     

Control of the common rail pressure in gasoline engines through an extended state observer based MPC

In this paper, a model predictive control (MPC) solution, assisted by extended state observer (ESO), is proposed for the common rail pressure control in gasoline engines. The rail pressure dynamic, nonlinear with large uncertainty, is modeled as a simple first order system. The discrepancy of the model from the real plant is lumped as ``total disturbance'', to be estimated in real-time by ESO and then mitigated in the nonlinear MPC, assuming the total disturbance does not change in the prediction horizon. The nonlinear MPC problem is solved using the Newton/generalized minimum residual (GMRES) algorithm. The proposed ESO-MPC solution, is compared with the conventional proportional-integral-differential (PID) controller, based on the high-fidelity model provided in the benchmark problem in IFAC-E-CoSM. Results show the following benefits from using ESO-MPC relative to PID (benchmark): 1) the disturbance rejection capability to fuel inject pulse step is improved by 12% in terms of recovery time; 2) the transient response of rail pressure is improved by 5% in terms of the integrated absolute tracking error; and 3) the robustness is improved without need for gain scheduling, which is required in PID. Additionally, increasing the bandwidth of ESO allows reducing the complexity of the model implemented in MPC, while maintaining the disturbance rejection performance at the cost of high noise-sensitivity. Therefore, the ESO-MPC combination offers a simpler and more practical solution for common rail pressure control, relative to the standard MPC, which is consistent with the findings in simulation.     

A model-based gain scheduling approach for controlling the common-rail system for GDI engines

The progressive reduction in vehicle emission requirements have forced the automotive industry to invest in research for developing alternative and more efficient control strategies. All control features and resources are permanently active in an electronic control unit (ECU), ensuring the best performance with respect to emissions, fuel economy, driveability and diagnostics, independently from engine working point. In this article, a considerable step forward has been achieved by the common-rail technology which has made possible to vary the injection pressure over the entire engine speed range. As a consequence, the injection of a fixed amount of fuel is more precise and multiple injections in a combustion cycle can be made. In this article, a novel gain scheduling pressure controller for gasoline direct injection (GDI) engine is designed to stabilise the mean fuel pressure into the rail and to track demanded pressure trajectories. By exploiting a simple control-oriented model describing the mean pressure dynamics in the rail, the control structure turns to be simple enough to be effectively implemented in commercial ECUs. Experimental results in a wide range of operating points confirm the effectiveness of the proposed control method to tame efficiently the mean value pressure dynamics of the plant showing a good accuracy and robustness with respect to unavoidable parameters uncertainties, unmodelled dynamics, and hidden coupling terms.     

基于系统辨识的航空发动机稳态燃油自抗扰控制

自抗扰控制技术应用于航空发动机稳态燃油控制存在两个难点：发动机中的高频不确定动态导致扩张状态观测器(Extended State Observer,ESO)增益过高和名义控制系数整定困难。针对此现状,提出一种基于系统辨识的航空发动机稳态燃油自抗扰控制器。首先,使用经典Gram-Schmidt(Classical Gram-Schmidt,CGS)算法对控制系数和发动机未知动态进行辨识,将辨识信息加入ESO中设计改进ESO (Improved ESO,IESO),从而使总扰动中包含较少的高频动态,降低观测器增益。其次,基于IESO设计航空发动机稳态燃油自抗扰控制器,并根据辨识结果快速整定名义控制系数。最后,分析IESO观测误差的收敛性和闭环系统的稳定性。仿真结果表明,所提方法可以快速整定名义控制系数,有效降低观测器增益,进而提高系统的鲁棒性。     

Rail pressure controller design of GDI basing on predictive functional control

Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system.     

基于PD-ADRC的四旋翼控制器设计

针对四旋翼无人机强耦合、非线性的控制难点,研究设计了一种基于自抗扰控制和比例微分控制的双闭环控制器。首先,分析了小型四旋翼飞行器动力学模型,确定四旋翼无人机的六自由度方程。然后,利用自抗扰控制技术对强耦合、非线性的姿态模型进行了解耦,设计扩张状态观测器对其总扰动进行观测与补偿。其次,设计比例微分控制器对解耦后的系统进行位置跟踪,从而与姿态控制器组成双闭环系统。最后,通过仿真及试飞实验测试系统性能。仿真和试飞结果表明该系统能够完成对控制指令的实时跟踪,并且对干扰具有极强的抑制力。     

Cyclic moving average control approach to cylinder pressure and its experimental validation

Cyclic variability is a factor adversely affecting engine performance. In this paper a cyclic moving average regulation approach to cylinder pressure at top dead center （TDC） is proposed, where the ignition time is adopted as the control input. The dynamics from ignition time to the moving average index is described by ARMA model. With this model, a one-step ahead prediction-based minimum variance controller （MVC） is developed for regulation. The performance of the proposed controller is illustrated by experiments with a commercial car engine and experimental results show that the controller has a reliable effect on index regulation when the engine works under different fuel injection strategies, load changing and throttle opening disturbance.     

Nonlinear Observer-based Control Design and Experimental Validation for Gasoline Engines with Exhaust Gas Recirculation

This paper presents a nonlinear observer-based control design approach for gasoline engines equipped with exhaust gas recirculation (EGR) system. A mean value engine model is designed for control which includes both the intake manifold and exhaust manifold dynamic focused on gas mass flows. Then, the nonlinear feedback controller based on the developed model is designed for the state tracking control, and the stability of the close loop system is guaranteed by a constructed Lyapunov function. Since the exhaust manifold pressure is usually unmeasurable in the production engines, a nonlinear observer-based feedback controller is proposed by using standard sensors equipped on the engine, and the asymptotic stability of the both observer dynamic system and control dynamic system are guaranteed with Lyapunov design assisted by the detail analysis of the model. The experimental validations show that the observer-based nonlinear feedback controller is able to regulate the intake pressure and exhaust pressure state to the desired values during both the steady-state and transient conditions quickly by only using the standard sensors.     

Robust nonlinear control of atomic force microscope via immersion and invariance

This paper reports an immersion and invariance (I&I)–based robust nonlinear controller for atomic force microscope (AFM) applications. The AFM dynamics is prone to chaos, which, in practice, leads to performance degradation and inaccurate measurements. Therefore, we design a nonlinear tracking controller that stabilizes the AFM dynamics around a desired periodic orbit. To this end, in the tracking error state space, we define a target invariant manifold, on which the system dynamics fulfills the control objective. First, considering a nominal case with full state measurement and no modeling uncertainty, we design an I&I controller to render the target manifold exponentially attractive. Next, we consider an uncertain AFM dynamics, in which only the displacement of the probe cantilever is measured. In the framework of the I&I method, we recast the robust output feedback control problem as the immersion of the output feedback closed‐loop system into the nominal full state one. For this purpose, we define another target invariant manifold that recovers the performance of the nominal control system. Moreover, to handle large uncertainty/disturbances, we incorporate the method of active disturbance rejection into the I&I output feedback control. Through Lyapunov‐based analysis of the closed‐loop stability and robustness, we show the semiglobal practical stability and convergence of the tracking error dynamics. Finally, we present a set of detailed, comparative software simulations to assess the effectiveness of the control method.     

Introduction to the benchmark challenge on common rail pressure control of gasoline direct injection engines

As one of the most important actuators for gasoline direct injection technology, common rail systems provide the requested rail pressure for fuel injection. Special system characteristics, such as coupled discrete-continuous dynamic in the common rail system, limited measurable states, and time-varying engine operating conditions, impel the combination of advanced methods to obtain the desired injection pressure. Therefore, reducing the pressure fluctuation and satisfying engineering implementation have become noteworthy issues for rail pressure control (RPC) systems. In this study, the benchmark problem and the design specification of RPC proposed by 2018 IFAC E-CoSM Committee are introduced. Moreover, a common rail system model is provided to the challengers, and a traditional PI control is applied to show the problem behaviors. Finally, intermediate results of the challengers are summarized briefly.