基于Duhem前馈逆补偿的压电陶瓷迟滞非线性 自适应滑模控制

针对压电陶瓷的动态迟滞非线性,研究了基于Duhem逆模型前馈补偿的滑模自适应控制策略。首先,利用多项式逼近Duhem模型中的未知分段函数ｆ(.)和ｇ(.),采用递推最小二乘法进行系统辨识,并求取逆模型,将其作为前馈控制器,考虑压电陶瓷迟滞非线性随输入信号频率变化,且难以完全抵消,模型参数存在不确定性等问题,设计一种自适应滑模控制律。利用Lyapunov稳定性定理及仿真实验证明了该控制律可以使系统全局渐进稳定。最后,进行了压电陶瓷迟滞补偿实验和位移跟踪实验。实验结果表明,前馈逆补偿控制下的压电陶瓷位移迟滞量减小了96.1％,与直接控制相比,前馈逆补偿控制下位移跟踪的最大绝对误差减小了27.0％,平均绝对值误差减小了17.9％,具有更好的跟踪精度和动态性能。     

LS-SVM构造FLANN逆系统的传感器动态补偿方法

提出一种用最小二乘支持向量机（LS—SVM）构造函数链接型神经网络（FLANN）逆系统的传感器动态补偿新方法。介绍了相关原理和具体算法,并给出了传感器动态逆系统的数学模型。在该方法中,通过在传感器后串接逆系统模型来修正动态测试误差、提高传感器的动态特性。通过典型的传感器动态标定实验数据,该逆系统模型的传递函数可用LS—SVM—FLANN方法辨识得到。实验结果表明,LS—SVM—FLANN辨识逆系统模型的速度是BP—FLANN方法的两倍,而且该逆系统动态补偿误差仅为后者的10％。用LS—SVM构造FLANN的逆系统补偿器精度高、鲁棒性好、实现简单。     

针对一类双环回滞特性的建模与逆补偿控制方法研究

提出了一种新的鲁棒自适应分段隐逆补偿状态反馈控制方案,以缓解智能材料驱动器中的双环回滞现象。其中,分段隐逆补偿方案不是真正意义上的回滞逆补偿器,而是一种在线解耦机制,从设计的临时控制信号寻找近似实际的控制信号。此外,提出了一种新的双环relay算子,从而建立了一种新的双环回滞模型。最后,在介电弹性体驱动器运动控制平台上进行实验,实验结果证明了所提出的输出-反馈控制方案的有效性。     

循环神经网络前馈补偿的压电驱动器跟踪控制

压电驱动器固有的迟滞特性,以及其他动态特性严重地影响其跟踪性能.循环神经网络能够准确拟合非线性系统,并且具有记忆存储能力,本文设计了一种循环神经网络对压电驱动器的迟滞特性进行建模,进而得到能够准确模拟输出位移和输入电压之间关系的逆模型,并据此对压电驱动器进行前馈补偿.此外,考虑到建模误差以及其他扰动对驱动器跟踪精度的影...     

非线性控制系统综合的频域逆系统方法研究

提出一种不需已知系统微分方程模型的非线性系统综合方法。首先得到对象非线性传递函数的估计,然后利用非线性补偿算法构造前馈补偿器,使复合系统具有近似线性系统的特性,最后采用常规线性系统反馈控制的方法进行控制。仿真结果表明,所提出的频域逆系统综合方法比一般非线性系统自适应控制方法有效。     

SG3525在BOOST直流变换器中的应用

采用平均开关模型方法建立了CCMBoost变换器的小信号模型,得到了相应的交流小信号传递函数。由于传递函数中存在S平面右半平面的零点,使得系统成为非最小相位系统。利用SG3525实现有源超前滞后补偿网络对系统进行了校正,实验结果验证了模型和控制方法的合理性。     

一种感应电机多模型解耦控制方法研究

提出一种基于新型广义逆系统的感应电机多模型解耦控制方法.通过对电机输入空间进行划分,利用神经网络辨识得到其广义逆系统模型,并针对每个子逆模型设计相应的控制器,使得闭环控制系统的传递函数实现任意的零极点配置.通过对电机输入空间的训练数据进行聚类,计算参考信号对每个类的相异度以实现模型之间的切换.仿真实验表明,该方法可对电机的转速和磁链实现有效的解耦控制,整个控制系统具有良好的鲁棒性.     

基于ANN逆模型补偿的复合控制系统仿真

为对复杂非线性系统进行辨识建模和实施有效控制,分析了基于神经网络的非线性系统逆模型的辨识和控制原理,研究了基于神经网络的非线性系统逆模型补偿的复合控制方法。基于复合控制思想,时常规PID控制器＋前馈神经网络逆模型补偿的复合控制结构方案进行了仿真。仿真结果表明,基于神经网络的非线性系统逆模型补偿的复合控制结构方案是有效的、相对简单的网络结构,可提高逆模型的泛化能力和非线性系统的控制精度。     

一种气缸位移控制系统的设计

针对传统可控位置气缸成本高的问题,设计了一种低成本气缸位移控制系统。首先,利用红外测距传感器测量活塞实际位移量;其次,通过期望位移量与实际位移量得到误差量;最后,基于BP神经网络建立气缸位移控制系统误差模型,完成误差补偿工作。实验表明:系统通过BP神经网络误差补偿后,可得最大位移误差量控制在±2 mm。     

下肢康复机器人的运动控制设计

因下肢康复机器人结构设计的差异性,导致了其控制方法的多样化。针对本文的下肢康复机器人,提出了一种简单的控制方法使其沿规划轨迹进行运动。为进行控制器的设计,需要先求得机器人系统的固有传递函数。通过分析发现该系统为非线性系统,利用实验的方法近似求得其传递函数,从而转化为线性系统的控制问题。之后利用极点配置法将系统配置为一个临界阻尼二阶系统,逆推求得系统控制器的传递函数。通过对机器人的髋关节运动控制系统进行测试,测试结果表明:设计的控制器能够很好地满足实验要求。     

Adaptive inverse control for parametric strict feedback systems with unknown failures of hysteretic actuators

An adaptive compensation control scheme is proposed by using backstepping techniques for a class of uncertain nonlinear systems preceded by m hysteretic actuators, which exhibit unknown backlash nonlinearity and possibly experience unknown failures. An estimated smooth inverse of the actuator backlash is utilized in the controller design to compensate for the effects of the backlash and actuator failures. It is shown that the designed controllers can ensure all signals of closed‐loop system bounded for any failure pattern of hysteretic actuators and tracking performance is also maintained. Simulation studies confirm the effectiveness of the proposed controller, especially the improvement of system performances. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application

A direct adaptive approach is developed for control of a class of multi-input multi-output (MIMO) nonlinear systems in the presence of uncertain failures of redundant actuators. An adaptive failure compensation controller is designed which is capable of accommodating uncertainties in actuator failure time instants, values and patterns. A realistic situation is studied with fixed grouping of actuators and proportional actuation within actuator groups. The adaptive control system is analyzed, to show its desired stability and asymptotic tracking properties in the presence of actuator failure uncertainties. As an application, such an adaptive controller is used for actuator failure compensation of a twin otter aircraft longitudinal model, with design conditions verified and control structure and adaptive laws developed for a nonlinear aircraft dynamic model. The effectiveness of adaptive failure compensation is demonstrated by simulation results.     

Adaptive inverse compensation for actuator backlash with piecewise time-varying parameters

Existing adaptive inverse compensation methods for cancelling actuator backlash nonlinearity are all restricted to handle constant backlash parameters. In other words, when discontinuity and time variation as both ubiquitous phenomena in practical actuators exist, such inverse compensation methods are no longer applicable theoretically. So far, no result has been reported in addressing such an issue, regardless of its importance in practice. In this paper, we solve this problem by developing a new piecewise Lyapunov function analysis and using parameter projection adaptation mechanism. Based on such approaches, an adaptive inverse compensation control scheme is designed to compensate for piecewise time-varying actuator backlash nonlinearity. It is proved that all signals of closed-loop system are ensured bounded. Moreover, the steady-state error is bounded by an adjustable scalar approaching to zero arbitrarily. Simulation also illustrates the obtained theoretical results.     

Adaptive output rejection of unmatched input disturbances

To adaptively reject the effect of certain unmatched input disturbances on the output of a linear time-invariant system, a transfer function matching condition is needed. A lemma which presents a novel basic property of linear systems is derived to characterize system conditions for such transfer function matching. An adaptive disturbance rejection control scheme is developed for such systems with uncertain dynamics parameters and disturbance parameters. This adaptive control technique is applicable to control of systems with actuator failures whose failure values, failure time instants, and failure patterns are unknown. A solution is presented to this adaptive actuator failure compensation problem, which ensures closed-loop stability and asymptotic output tracking, in the presence of any up to m−1 uncertain failures of the total m actuators. Desired adaptive system performance is verified by simulation results.     

On matching conditions for adaptive state tracking control ofsystems with actuator failures

In this paper, new necessary and sufficient conditions are derived for actuator failure compensation for linear time-invariant systems with actuator failures characterized by unknown input signals at some unknown fixed values and time instants, for state tracking with state feedback. It is shown that the number of fully functional actuators is crucial in determining the actuation range, which specifies the compensation design conditions in terms of system actuation structure. Such conditions are required for both a nominal design using system knowledge and an adaptive design without system knowledge. An adaptive actuator failure compensation control scheme based on relaxed system actuation conditions is developed for systems with unknown dynamic parameters and actuator failure parameters including failure values, times, and patterns. Simulation results are presented to verify the desired system performance with failure compensation     

具有执行器故障的四旋翼无人机有限时间容错控制

本文主要研究了四旋翼无人机在外部干扰、执行器存在部分失效和偏置故障并发情况下有限时间轨迹跟踪的控制问题. 通过分析四旋翼无人机动力学特性, 构建了带有外部干扰、执行器机构故障的动力学模型. 基于鲁棒全局快速终端滑模控制算法, 设计了一种有限时间容错控制器, 提高了系统对故障的响应速度. 其次, 针对常值/时变故障和干扰,在控制器设计中采用改进的连续函数进行补偿, 减少了由切换函数引起的系统抖振, 并基于Lyapunov函数对控制器的稳定性进行了分析. 最后, 通过仿真实验验证了所设计控制器的有效性和可靠性, 同时存在执行器故障和外部干扰的情况下, 无人机能够实现较好的轨迹跟踪性能.     

飞翼飞行器的操纵面故障自适应补偿控制

本文针对具有操纵面卡死、失效故障以及执行器饱和的飞翼飞行器纵向运动,考虑系统的预定动态性能,提出了一种自适应反步补偿跟踪控制方案.设计预定动态性能(prescribed performance bound,PPB)边界以保证系统的跟踪误差,采用二阶指令滤波器限制执行器的饱和,通过控制分配避免执行器故障后对横侧向运动的影响.所设计的自适应反步补偿跟踪控制律能够保证系统对参考信号的渐近跟踪.仿真结果表明了本文方法的有效性.     

Simultaneous compensation of hysteresis and creep in a single piezoelectric actuator by open-loop control for quasi-static space active optics applications

Owing to their excellent properties piezoelectric actuators are studied as embedded elements for the quasi-statically active shape control of spatial optical mirrors. However, unwanted nonlinear effects in piezoelectric actuators, i.e., hysteresis and creep, severely limit their performance. This paper aims at developing a control methodology to compensate hysteresis and creep in a piezoelectric actuator simultaneously for quasi-static space active applications. In the methodology developed, hysteresis and creep behaviors are successively compensated by open-loop control. First, a derivative Preisach model is proposed to accurately portray the hysteresis while requiring relatively few measurements and describing the detachment between major and minor loops. The inverse derivative Preisach model is derived and inserted in open-loop to achieve hysteresis compensation. Then, the creep in the hysteresis compensated piezoelectric actuator is described by the use of a nonlinear viscoelastic model and a low pass filter is suggested to eliminate the effect of the inverse derivative Preisach model on the step reference input. To invert the creep model, the concept of “input relaxation” is implemented and an inverse multiplicative structure allows identifying the parameters of the inverse model while circumventing the difficulty of a mathematical computation. Finally, by cascading the low pass filter, the inverse model of creep and the inverse derivative Preisach model one after the other with the single piezoelectric actuator, the simultaneous compensation of hysteresis and creep is achieved. Experimental results show that in the case of step-like reference signals the hysteresis and the creep in a piezoelectric actuator can be significantly reduced at the same time. It implies that the developed methodology is effective and feasible in space active optics applications for which quasi-static distortions need to be compensated.     

Modeling and inverse adaptive control of asymmetric hysteresis systems with applications to magnetostrictive actuator

When uncertain systems are actuated by smart material based actuators, the systems exhibit hysteresis nonlinearities and corresponding control is becoming a challenging task, especially with magnetostrictive actuators which are dominated by asymmetric hystereses. The common approach for overcoming the hysteresis effect is inverse compensation combining with robust adaptive control. Focusing on the asymmetric hysteresis phenomenon, an asymmetric shifted Prandtl–Ishlinskii (ASPI) model and its inverse are developed and a corresponding analytical expression for the inverse compensation error is derived. Then, a prescribed adaptive control method is applied to mitigate the compensation error and simultaneously guaranteeing global stability of the closed loop system with a prescribed transient and steady-state performance of the tracking error without knowledge of system parameters. The effectiveness of the proposed control scheme is validated on a magnetostrictive actuated platform.     

Adaptive actuator failure compensation for multivariable feedback linearizable systems

A feedback linearization‐based adaptive control scheme is developed for multivariable nonlinear systems with redundant actuators subject to uncertain failures. Such an adaptive controller contains a direct adaptive actuator failure compensator to compensate the uncertain actuator failure, a nonlinear feedback to linearize the nonlinear dynamics, and a linear feedback to stabilize the linearized system. The key new design feature is the estimation of both the failure patterns and the failure values, for direct adaptive actuator failure compensation, newly developed for multivariable feedback linearizable nonlinear systems. With direct control signal adaptation, the adaptive failure compensation design ensures closed‐loop stability and asymptotic output tracking in the presence of actuator failure uncertainties. Simulation results from an application to attitude control of a near‐space vehicle dynamic model are presented to verify the desired system performance with adaptive actuator failure compensation. Copyright © 2015 John Wiley & Sons, Ltd.