Improving vehicle performance using adaptive control techniques

This paper reviews a collaborative research programme aimed at improving vehicle performance using adaptive control techniques. Initially the design of active suspension systems is considered, and the benefits of using a non-linear controller model with an adaptive control scheme are discussed. Adaptive schemes for active roll control are then considered, and the merits of incorporating a Smith predictor to accommodate for system delays are high-lighted. Preliminary research in adaptive cruise control and collision avoidance is discussed and plans for further developments are outlined. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, 19–21 January 1998     

Adaptive Active Fault Tolerant Control for Discrete‐Time Systems with Uncertainties

An active fault‐tolerant control scheme for discrete‐time systems is proposed to solve a difficult problem of fault‐tolerant controller design in the presence of partial loss of actuator effectiveness faults and structural parameter uncertainties assumed to be matched, using adaptive control techniques to help a faster and more accurate compensation of failure and uncertainty. An automated fault estimation scheme is developed together with an adaptive model parameter identification to obtain system parameter estimates. With these estimates fed back to the system, a model reference adaptive controller is constructed to achieve a desired tracking performance. Since parameters are obtained and updated online, the control system has an automatic failure compensation capability so as to recognize or reconfigure the control law in real time in response to failure indications. The stability and convergence follow from discrete‐time Lyapunov arguments. Simulation results from the linearized lateral dynamics model of the Boeing 747 airplane are presented to show the efficiency of proposed methods.     

汽车振动的一种模糊自适应控制

该文研究了一种汽车模糊自适应控制方法,并借助于一个二自由度的汽车动力学模型,探讨了该模糊自适应控制技术在汽车车身主动减振方面的控制问题。在测得汽车垂直振动强度,行驶速度等条件下,在保持各个状态变量和控制量的模糊集数量不变的情况下,通过自动调整模糊集的相应大小与相应中央位置,仿真研究表明,该自适应模糊控制器使汽车在不同路面波度大小,行驶速度等情况下的车身振动强度均能大幅度下降,达到主动减振的目的。其原理与方法可用于研制简单可靠的模糊控制主动悬架。     

A new model-free adaptive sliding controller for active suspension system

Active suspension systems are designed to provide better ride comfort and handling capability in the automotive industry. Since the active suspension system has nonlinear and time-varying characteristics, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, a functional approximation (FA) based adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The FA technique is employed to represent the unknown functions, which releases the model-based requirement of the sliding mode control. In addition, a fuzzy control scheme with online learning ability is employed to compensate for the modeling error of the FA with finite number of terms for reducing the implementation difficulty. To guarantee the control system stability, the update laws of the coefficients in the approximation function and the fuzzy tuning parameters are derived from the Lyapunov theorem. The proposed controller is employed on a quarter-car active suspension system. The simulation results and experimental results show that the proposed controller can suppress the oscillation amplitude of the sprung mass effectively. To evaluate the performance improvement of inducing a fuzzy compensator in this FA adaptive controller, the dynamic responses of the proposed hybrid controller are compared with those of FA-based adaptive sliding controller only.     

基于动态优化模型集的多模型自适应控制

针对多模型自适应控制的传统算法中固定模型集无法准确覆盖对象的不确定域的问题,提出了一种新型的能够在线动态优化模型集的方法。该方法能够在线自动添加、删除以及修改模型集中的模型,有效地控制模型数量以及优化模型集,使模型集对不确定域进行精确覆盖,并且在系统运行的稳定阶段可以停止优化模型集的动作,从而大幅减少计算量。该方法在优化控制性能的同时不会过分增加系统运算负担,仿真实验表明了此算法的优越性。     

一类直接模型参考Backstepping自适应控制

提出一种新的直接模型参考Backstepping自适应控制系统结构:谈系统在直接模型参考卓适应控制(MRAC)结构的基础上,增加了Beckstepping控制信号发生器,通过Backstepping方法的灵活设计获得良好的过渡过程品质,得到直接MRAC在稳定性和鲁棒性设计等方面的优点.采用高阶调节器设计了未具规范化的直接模型参考Backstepping自适应律,克服了传统自适应律引入规范化信号后使系统过渡过程品质下降的缺点.     

Adaptive Control of Piecewise Linear Systems with State Feedback for Output Tracking

A piecewise linear system consists of a set of linear time‐invariant (LTI) subsystems, with a switching sequence specifying an active subsystem at each time instant. This paper studies the adaptive control problem of single‐input, single‐output (SISO) piecewise linear systems. By employing the knowledge of the time instant indicator functions of system parameter switches, a new controller structure parametrization is proposed for the development of a stable adaptive control scheme with reduced modeling error in the estimation error signal used for parameter adaptive laws. This key feature is achieved by the new control scheme's ability to avoid a major parameter swapping term in the error model, with the help of indicator functions whose knowledge is available in many applications. A direct state feedback model reference adaptive control (MRAC) scheme is presented for such systems to achieve closed‐loop signal boundedness and small output tracking error in the mean square sense, under the usual slow system parameter switching condition. Simulation results on linearized NASA GTM models are presented to demonstrate the effectiveness of the proposed scheme.     

一种基于神经元强化学习的网络拥塞控制方法

提出了一种基于神经元强化学习(Neuron-based Reinforcement Learning,NRL)的自适应AQM算法,采用链路速率和队列长度作为拥塞指示,可根据网络环境的变化在线自动调整神经元参数,从而保持良好的队列长度稳定性和对网络负载波动的鲁棒性.该算法结构简单、易于实现,且不依赖对象的模型.仿真结果表明,该算法尤其适合于解决复杂不确定性网络的拥塞控制问题,并具有更好的队列稳定性和鲁棒性.     

基于模糊神经网络的二自由度主动悬架滑模控制系统设计

主动悬架滑模控制系统受到行驶路面影响,车体震动加速度功率谱密度与实际密度不一致,导致系统控制效果不佳,提出基于模糊神经网络的二自由度主动悬架滑模控制系统设计;基于二自由度硬件结构,在主动悬架液压伺服系统中安装蓄能器,减小空间内存;采用磁流变阻尼器,调整电流大小控制阻尼;设计自适应减振座椅悬架并计算阻尼值,实现了主动悬架的控制;考虑路面不规则度,构建二自由度主动悬架滑模控制模型,依据牛顿定律计算悬架弹性元件受力;采用模糊控制规则校正控制误差,采用模糊神经网络设计主动悬架滑膜控制方案,经迭代处理得到满足优化要求的解,实现滑膜控制;由试验结果可知,车体震动加速度功率谱密度与实际密度一致,从最初的0 ms^(-2)到最终的1.5 ms^(-2),具有良好控制效果,确保乘车的舒适性。     

Adaptive regulation—Rejection of unknown multiple narrow band disturbances (a review on algorithms and applications)

The paper addresses the problem of attenuation (rejection) of unknown and time varying multiple narrow band disturbances without measuring them. In this context the disturbance model is unknown and time varying while the model of the plant is known (obtained by system identification) and almost invariant. This requires to use an adaptive feedback approach. The term “adaptive regulation” has been coined to characterize this control paradigm. Application domains include: mechanical and mechatronics systems, active vibration and noise suppression systems, some types of bio-chemical reactors.The paper reviews the various techniques proposed for solving this problem. It will focus on the presentation of the direct and indirect adaptive regulation strategies using the internal model principle and the Youla–Kucera parametrization which have been extensively used in applications.The paper also reviews a number of applications including: active suspension systems, active vibration control systems, active noise control, bio-chemical reactors, distributed flexible mechanical structures and Blu-ray disc drives. Real time results obtained on various applications will illustrate the methodology.     

Experimental validation of an active heave compensation system: Estimation,prediction and control

This work presents a comprehensive active heave compensation (AHC) approach proposing estimation, prediction and control methods. The estimation concept covers the estimation of the attitude using sensor fusion as well as the estimation of heave which is obtained by applying adaptive filtering methods. Moreover, a prediction approach based on a Levinson recursive least squares (RLS) algorithm is proposed. The actuation concept consists of a model predictive trajectory planner and a model-based Two-Degree-of-Freedom (2-DOF) controller. It is based on a model of the hydraulically driven compensation winch. The overall compensation performance as well as the estimation and prediction accuracy are evaluated using a full-scale AHC test bench.     

液压釜温度自适应预测控制

详细介绍了液压釜温度系统自适应控制方案、误差分析及实际应用调试情况．应用全系数自适应控制理论及模型预测控制原理设计了一种新的自适应预测控制方案,并给出了控制算法的稳定性证明及闭环系统稳态误差和动态特性分析．实际应用表明,该方法对建模误差、系统延时及测量噪声具有较好的鲁棒性．     

液压釜温度自适应预测控制

详细介绍了液压釜温度系统自适应控制方案、误差分析及实际应用调试情况.应用 全系数自适应控制理论及模型预测控制原理设计了一种新的自适应预测控制方案,并给出了 控制算法的稳定性证明及闭环系统稳态误差和动态特性分析.实际应用表明,该方法对建模 误差、系统延时及测量噪声具有较好的鲁棒性.     

基于改进卡尔曼滤波器的扰动抑制无模型自适应控制方案

针对无模型自适应控制方法在测量扰动作用下控制效果不佳的问题, 本文提出了一种新的扰动抑制无模 型自适应控制方案. 首先基于受控系统的动态线性化数据模型及测量扰动的统计特性, 在最小方差估计准则下推导 了基于系统输入输出数据的改进卡尔曼滤波器. 然后基于此滤波器给出了一种新的扰动抑制无模型自适应控制方 案. 该方案仅需用到受控系统的输入输出数据, 即可实现在强测量扰动作用下系统的无模型自适应控制. 仿真结果 显示, 相比现有的扰动抑制无模型自适应控制方案, 该方案在系统跟踪常值参考信号、时变参考信号时均能有效地 抑制测量扰动, 适用性更好的同时可以获得更小的跟踪误差及更大的数据信噪比.     

A multivariable MRAC scheme with application to a nonlinear aircraft model

This paper revisits the multivariable model reference adaptive control (MRAC) problem, by studying adaptive state feedback control for output tracking of multi-input multi-output (MIMO) systems. With such a control scheme, the plant-model matching conditions are much less restrictive than those for state tracking, while the controller has a simpler structure than that of an output feedback design. Such a control scheme is useful when the plant-model matching conditions for state tracking cannot be satisfied. A stable adaptive control scheme is developed based on LDS decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. A simulation study of a linearized lateral-directional dynamics model of a realistic nonlinear aircraft system model is conducted to demonstrate the scheme. This linear design based MRAC scheme is subsequently applied to a nonlinear aircraft system, and the results indicate that this linearization-based adaptive scheme can provide acceptable system performance for the nonlinear systems in a neighborhood of an operating point.     

Coordinate independent adaptive attitude tracking control design for spacecraft robust to time-varying system uncertainties

In this paper, we consider the adaptive attitude control of spacecraft with time-varying inertial properties. We use a coordinate independent approach for the purpose of designing the control and estimation laws in terms of the rotation matrices representing the spacecraft body frame and reference tracking signals. This method helps to overcome the difficulties regarding the attitude representation on SO(3) such as ambiguities associated with quaternion representation and inherent singularities inside Euler parameters. We model the time variations in inertial parameters in two different ways, and design adaptive control schemes for each case. As the first uncertain dynamic model, we consider a setting of spacecraft with multiple moving appendages, and based on this model, design an adaptive control scheme with three different versions, where Frobenious norm is used in measuring the deviation of the estimated inertia tensors from their actual values. The proposed adaptive control scheme is later extended for the more direct model where the inertia tensor of the spacecraft has a nonlinear relation with the norm of the input moment. Further, we derive the allowable sets of initial conditions to ensure the convergence of the tracking error. Simulation results are provided to illustrate the effectiveness of our proposed approach.     

互质因子摄动系统最优l1鲁棒控制:连续性与自适应控制

针对具有互质因子摄动和未知干扰的离散时间系统研究了一种自适应鲁棒控制策略. 本文的主要工作包括三个方面.首先建立了互质因子摄动系统最优l1鲁棒控制设计的连续性. 然后,提出了一种带变死区的参数鲁棒估计投影算法.最后,结合所提出的参数估计算法和最优 l1鲁棒控制,利用确定性等价原理提出了互质因子摄动系统的一种新的自适应鲁棒控制方法.基 于本文建立的l1优化设计的连续性,证明了自适应鲁棒控制的全局稳定性,给出了自适应控制系 统稳定性的后验可计算条件.     

ROBUST ADAPTIVE CONTROL OF PIEZOELECTRIC ACTUATORS WITH AN APPLICATION TO INTRACYTOPLASMIC SPERM INJECTION

This paper describes a robust adaptive control method for positioning piezoelectric actuators (ultrasonic motor) to achieve highly precise motion. The model employed to describe the motor is a second‐order linear model plus a nonlinear part comprising predominantly of a dynamical hysteresis. Based on the model, the overall control algorithm uses a PID component and an adaptive robust component for estimating the parameters of the piezo motor model. The adaptive component is continuously refined based on just prevailing input and output signals. Real‐time experimental results are provided to verify the effectiveness of the proposed scheme when applied to high precision motion trajectory tracking such as Intracytoplasmic Sperm Injection (ICSI).     

Hierarchical neuro-fuzzy current control for a shunt active power filter

This paper presents the design of a hierarchical neuro-fuzzy current control scheme for a shunt active power filter compared with a single fuzzy controller scheme. A single fuzzy controller scheme is presented first and an ANFIS based neuro-fuzzy controller is connected hierarchically to the first one to improve the performance. Simulation results show that harmonic compensation is achieved with both schemes, however switching performance is superior for hierarchical scheme. The method of switching controller development in this paper is new and can be applied to other power electronic converter applications for improved performance.