基于自适应模型预测的无人车跟踪控制方法研究

针对避障工况下现有控制方法难以同时满足跟踪精度和稳定性的问题，设计了一种考虑滑移约束的自适应模型预测控制方法，能够在不同避障工况自适应匹配最优时域参数和稳态转角约束，提高控制器的适应能力和动态响应性能。首先由实验测试获取优化的时域参数表，并综合考虑滑移边界内的稳态转角约束，设计参数自适应机制，然后在联合仿真平台进行了双移线工况的仿真实验来模拟避障场景，验证了所设计的自适应模型预测控制器的有效性，最后基于实车平台进行了实际避障场景的路径跟踪实验。实验结果表明，与传统模型预测控制相比，所设计的自适应模型预测控制器在跟踪精度和稳定性方面都有较大改善。     

汽车自动变速器换挡的控制

为进一步提升用户对汽车的驾乘体验感，解决汽车自动变速器换挡过程时的延时性和顿挫感，在对汽车自动变速器结构研究和对换挡控制分析的基础上，设计了基于SIMTH控制器的目标跟踪控制分系统和抑制扰动控制分系统，并完成了相应控制器的设计。对所设计控制器对自动变速器在不同工况下的换挡控制效果进行验证，取得理想结果。     

基于深度学习工况预测的稳压器控制优化

为了优化传统核电站稳压器控制，本文将深度学习方法引入PID控制器。将长短期记忆（Long Short-Term Memory,LSTM）模型使用传统PID控制仿真数据训练后，为PID控制器提供工况预测数据，弥补因为传感器信号传输以及PID控制器计算带来的反馈延迟，从而使得PID控制器能够依据更实时的工况进行控制信号的计算。在验证实验中，对基于上述方法的智能PID控制器进行了功能验证和复杂工况运行验证。实验结果表明，智能PID控制器能够有效降低传统PID控制过程中的超调量（最高可降低80.7%），同时可以将传统PID控制达到稳态的时间缩短最多60.73s。该控制器的控制性能虽然受工况变化影响仍然较大，但是为核电站稳压器的智能优化方法进行了有益探索，为后续进一步利用人工智能方法改进传统核电站仪控方法提供了借鉴。     

汽车底盘测功机快速控制原型测控平台的设计

传统的汽车底盘测功机测控系统一般只对固有测试项目进行测试,不能满足科研试验对各种运行工况的要求,为了实现对不同运行工况的模拟和控制并有效缩短测控系统的开发周期,借助快速控制原型开发技术,设计开发了由快速原型控制器、全自动代码生成编译工具及实时监测标定软件构成的具有开放性的底盘测功机快速控制原型测控平台,借助模块化的Simulink模型与代码自动生成技术实现控制策略模型到代码的自动下载,完成所需工况的模拟和控制。实车试验结果验证了测控平台的可靠性和有效性。     

时变参数对象的多模型内模控制的研究

针对火电厂主汽温被控对象具有大迟延、大惯性、参数时变的特点提出一种基于多模型加权的内模控制策略,通过在不同工况辨识得到局部模型,根据加权因子计算出全局多模型内模控制器,从而实现全工况运行的自适应控制。仿真结果表明,该控制策略比常规的内模控制具有更好的控制品质。     

电液速度伺服系统的增益调度控制

0前言 对于动态特性随工作点而变化的过程，要求控制器在各种工况下均能满足指定的性能指标。为了补偿过程参数变化与非线性等不确定因素的影响，可针对过程的不同工作状态，将系统在一些特定的工作点进行线性化处理，然后在这些工作点采用合适的线性化设计方法设计相应的控制器，使闭环系统在各工作点的邻域内满足性能要求。在系统运行时，根据调度变量通过调度控制器增益使系统在不同的区域运行不同的控制律，以处理系统的非线性问题．这就是增益调度。增益调度控制器简单适用，在处理非线性系统方面获得了广泛的应用。     

一种用于ASM测试的改进RLS广义最小方差自适应控制

分析了稳态工况法排放测试中加速段的控制特点,建立了ASM控制的CARMAX模型,基于这一模型,提出了一种基于改进RLS的广义最小方差自适应控制方法,针对此算法分析了其优点,并进行了相应的控制器设计。以ASM两个工况的加速段的控制为对象,采用该方法进行了仿真。作为对比,同时采用了传统的PID控制进行对比研究。结果表明,两个不同工况下采用不同加载突变,该方法都能快速适应相应的变化,使系统的操作变得容易,从而显示了该方法具有实际应用价值。     

车用燃料电池混合动力系统自适应控制研究

在MATLAB/Simulink中建立了燃料电池/锂电池混合动力系统仿真模型,利用自适应反演滑模控制理论,设计了基于状态机能量管理策略的电流/电压控制器,使燃料电池尽可能工作在高效稳定区域,实现了混合动力系统在不同汽车运行工况下驱动与制动的可持续性。仿真结果表明,该控制器对燃料电池电流的追踪响应速度快,追踪精度高,抗干扰能力强,且混合动力系统在不同工况下燃料电池功率输出稳定、切换平滑,提高了燃料电池的耐久性。     

无刷直流电机驱动轨道车辆速度控制及其对垂向振动的影响

在MATLAB/Simulink环境下建立了某无刷直流电机模型和由其驱动的轨道车辆垂向振动模型。通过转速PI控制和电流滞环控制组成的双闭环控制器实现对无刷直流电机的控制,进而控制车辆速度。对车辆速度控制以及车辆在不同速度工况下的垂向振动响应进行了研究,研究结果显示:在双闭环控制器的作用下,无刷直流电机驱动车辆可以得到理想的速度控制效果;随着车辆运行速度的提高,车体浮沉运动的主振动频率会相应地增大;车辆的加速对车体的低频浮沉振动有一定的影响,而对高频浮沉振动的影响不明显。     

非线性系统的多模糊模型控制自动切换方法的研究

首先给出了非线性系统的线性多模糊模型表示 ,然后根据实际对象在不同运行点附近的状态 ,采用最大隶属度原则识别匹配模型。从而选择相应控制器的多模型控制方法。     

DYNAMIC BOUNDARY CONTROL OF BEAMS USING ACTIVE CONSTRAINED LAYER DAMPING

A globally stable boundary control strategy is developed to damp the vibration of beams fully treated with active constrained layer damping (ACLD) treatments. The devised boundary controller is compatible with the operating nature of the ACLD treatments where the strain induced generates a control force and moment acting at the boundary of the treated beam. The development of the boundary control strategy is based on a distributed-parameter model of the beam/ACLD system in order to avoid the classical spillover problems resulting from using ‘truncated’ finite element models. Such an approach makes the boundary controller capable of controlling all the modes of vibration of the ACLD-treated beams and guarantees that the total energy norm of the system is decreasing continuously with time. The control strategy is provided also with a dynamic compensator to shape the vibration damping characteristics of the ACLD in the frequency domain. The effectiveness of the ACLD in damping out the vibration of cantilevered beams is determined for different control gains and compared with the performance of conventional passive constrained layer damping (PCLD). The results obtained demonstrate the high damping characteristics of the boundary controller particularly over broad frequency bands.     

Control System Design for a Neutralization Process using Block Oriented Models

Abstract

This paper focuses on the development of a non‐linear controller for a neutralization process. Block oriented models, namely the Wiener and Hammerstein model structures, are used for the controller design. A neural network architecture that has the capability to model the steady state behavior of a complex non‐linear process is developed. The dynamic behavior is modeled with a linear model. The pH process considered in this study exhibits drastic changes in the gain, even over a small operating range. In this study, the performance of controllers designed using Weiner and Hammerstein models are compared with a PI controller for servo and regulatory changes. The comparison results based on integral square error (ISE) values shows that the Weiner model based controller is suitable for a pH process.     

Design and implementation of a gain scheduling controller for a water level control system

The design of a gain-scheduled proportional plus integral (PI) controller for a nonlinear water-tank level control system is presented. A novel approach of determining operating points in terms of interpolation error is also given. The controller is implemented in LABVIEW in the laboratory. The field test results of the system response at different operating conditions clearly illustrate the controller's improved performance over a fixed PI controller.     

Fuzzy model predictive control of non-linear processes using convolution models and foraging algorithms

In this paper, a fuzzy model predictive control (FMPC) approach is introduced to design a control system for nonlinear processes. The proposed control strategy has been successfully employed for representative, benchmark chemical processes. Each nonlinear process system is described by fuzzy convolution models, which comprise a number of quasi-linear fuzzy implications (FIs). Each FI is employed to describe a fuzzy-set based relation between control input and model output. A quadratic optimization problem is then formulated, which minimizes the difference between the model predictions and the desired trajectory over a predefined predictive horizon and the requirement of control energy over a shorter control horizon. The present work proposes to solve this optimization problem by employing a contemporary population-based evolutionary optimization strategy, called the Bacterial Foraging Optimization (BFO) algorithm. The solution of this optimization problem is utilized to determine optimal controller parameters. The utility of the proposed controller is demonstrated by applying it to two non-linear chemical processes, where this controller could achieve better performances than those achieved by similar competing controller, under various operating conditions and design considerations. Further comparisons between various stochastic optimization algorithms have been reported and the efficacy of the proposed approach over similar optimization based algorithms has been concluded employing suitable performance indices.     

大范围工况热工过程系统的多模型预测控制

文中讨论了基于多模型的预测控制方法。对于在工作范围内发生参数突变的被控热工对象,在典型工况下通过实验数据获得典型工作点的系统模型,从而建立多个局部模型表示,基于每个局部模型分别设计子DMC控制器。通过跟踪工况变化来对子控制器加权以获得控制增量。实验结果表明该方法对参数突变适应快,可取得令人满意的控制效果。     

Modeling and fuzzy control of the engine coolant conditioning system in an IC engine test bed

Mechanical and thermodynamical performance of internal combustion engines is significantly affected by the engine working temperature. In an engine test bed, the internal combustion engines are tested in different operating conditions using a dynamometer. It is required that the engine temperature be controlled precisely, particularly in transient states. This precise control can be achieved by an engine coolant conditioning system mainly consisting of a heat exchanger, a control valve, and a controller. In this study, constitutive equations of the system are derived first. These differential equations show the second-order nonlinear time-varying dynamics of the system. The model is validated with the experimental data providing satisfactory results. After presenting the dynamic equations of the system, a fuzzy controller is designed based on our prior knowledge of the system. The fuzzy rules and the membership functions are derived by a trial and error and heuristic method. Because of the nonlinear nature of the system the fuzzy rules are set to satisfy the requirements of the temperature control for different operating conditions of the engine. The performance of the fuzzy controller is compared with a PI one for different transient conditions. The results of the simulation show the better performance of the fuzzy controller. The main advantages of the fuzzy controller are the shorter settling time, smaller overshoot, and improved performance especially in the transient states of the system.     

联合收割机双闭环负荷控制系统的设计

联合收割机是一个高阶时变非线性系统,存在大滞后,工况复杂,简要分析联合收割机数学模型及作业期间可能存在的各种内部、外部扰动。针对收割机负荷控制系统中利用一个控制器综合多个扰动,各参数相互影响,参数调整困难,系统动态性能不够好的问题,提出一种双闭环负荷控制系统,将收割机系统分为行走、作业两部分,分别利用车速闭环和滚筒转速闭环进行控制。车速闭环采用单神经元比例积分微分(Proportion,integration,differentiation,PID)算法,根据车辆行走系统的工况变化不断调整控制参数,尽可能跟踪给定车速。滚筒转速闭环采用直接广义预测控制算法,也可自动适应系统参数和工况的变化,保证滚筒恒定在最佳转速。整个控制算法实时计算量较小,可保证系统具有足够高的实时性。仿真和试验证明双闭环负荷控制系统能获得较高的控制精度和优良的动态特性。     

Multi-linear model set design based on the nonlinearity measure and H-gap metric

This paper proposes a model bank selection method for a large class of nonlinear systems with wide operating ranges. In particular, nonlinearity measure and H-gap metric are used to provide an effective algorithm to design a model bank for the system. Then, the proposed model bank is accompanied with model predictive controllers to design a high performance advanced process controller. The advantage of this method is the reduction of excessive switch between models and also decrement of the computational complexity in the controller bank that can lead to performance improvement of the control system. The effectiveness of the method is verified by simulations as well as experimental studies on a pH neutralization laboratory apparatus which confirms the efficiency of the proposed algorithm.     

Submicrometer control of a traction drive using state feedback and estimation

Traction drives are direct-drive systems that are more sensitive to noise and disturbances than lead screws. Their performance using PID control is not always satisfactory. Therefore, there is a need to improve the tracking performance of traction drives while overcoming their inherent sensitivity to disturbances. To understand their behavior better, their operating characteristics are investigated and a system model is developed. Using this model, a state feedback regulator is designed. To eliminate steady-state errors to step commands and improve tracking performance, an outer PID loop is added. The performance of this controller is then compared with that of a PID controller. It is shown that the state feedback/PID scheme rejects disturbances more than three times as fast as the PID controller and reduces tracking errors by over 50%.     

蓄能器变压力供油电液位置控制系统的复合补偿控制

在一些特殊的工程应用中,常采用蓄能器作为动力源为电液位置控制系统提供压力油。与传统的电液位置控制系统不同,当采用蓄能器供油时,蓄能器出口的油液压力会逐渐降低,而压力的变化会对系统的控制性能产生较大的影响。针对这种变压力油源的电液位置控制系统,搭建了以蓄能器为动力源的电液位置控制系统实验平台,并建立了严格数学模型。通过实验手段确定了蓄能器供油压力与排油体积的关系、以及基于LUGRE模型的精确的系统摩擦力模型,以便实现系统运动过程中的有效动态补偿。构建了一种基于PID控制器+前馈补偿器+模糊控制器联合作用的复合补偿控制器,有效地降低了系统工作过程中供油压力降低、摩擦力变化等因素对实际控制性能造成的影响。通过与传统控制方法的对比实验,验证了所提出的控制算法的有效性。