基于间接自适应鲁棒的永磁同步电机电流控制器设计

针对永磁同步电机(PMSM)电流环非理想反电势的抑制问题,本文提出一种基于鲁棒最小二乘(RRLS)自适应律的间接自适应鲁棒控制(IARC)方法.该控制方法基于自适应鲁棒控制(ARC)理论,根据电机状态方程构造最小二乘型自适应律,加入修正因子增强自适应律对系统中扰动的鲁棒性.本文理论证明了该方法的稳定性.通过建立含有非理想反电势的电机模型,设计IARC电流控制器,并分析说明IARC具有比直接ARC更好的输出跟踪性能和扰动抑制能力.最后,通过仿真和实验验证了该方法的有效性.     

基于系统浸入和流形不变自适应方法的静止无功补偿器非线性鲁棒自适应控制方法

本文提出一种将系统浸入和流形不变(I&I)自适应控制方法与L2-增益抑制鲁棒控制方法相结合的静止无功补偿器(SVC)的非线性鲁棒自适应控制方法.所提方法首先通过参数估计误差和鲁棒控制律的设计,使得所构造的表示参数估计误差函数的流形不变且吸引,从而使参数估计误差在这一流形上收敛于零.然后,通过所设计的可调参数对参数估计误差的收敛性能进行控制,以此来保证参数估计器对不确定参数的自适应估计能力.最后,采用自适应逆推算法推导鲁棒控制律,并通过使不确定外部扰动满足从输入到输出的耗散性来保证系统对不确定扰动的鲁棒性.仿真结果表明,利用所提方法设计的SVC控制器和参数替换律在参数估计、发电机功角动态响应方面优于传统自适应逆推算法,从而提高了输电系统的稳定水平.     

基于参数估计误差的鲁棒自适应律设计及验证

针对传统自适应控制系统设计的自适应律参数收敛慢进而影响控制系统瞬态性能的问题,研究一类新的基于参数估计误差修正的鲁棒自适应律设计.首先引入滤波操作给出参数估计误差的提取方法,构建出含参数估计误差修正项的自适应律,进而将该自适应律用于控制器设计和分析中,可同时实现控制误差和参数估计误差指数收敛.对比分析了几类传统自适应律和所提出自适应律的收敛性和鲁棒性,并给出了保证参数收敛所需持续激励条件的一种直观、简便的在线判别方法.数值仿真及基于自制三自由度直升机系统俯仰轴实验结果表明,基于参数误差修正的自适应律及控制器可得到优于传统自适应方法的跟踪控制和参数估计性能.     

输入力矩受限的机器人鲁棒自适应跟踪控制

在输入力矩受限的情况下, 提出一种全新的简单鲁棒自适应跟踪控制算法, 当参数的估计范围包含其真实值时, 证明了闭环系统的渐近稳定跟踪;当有干扰存在, 常规参数估计自适应控制算法不能实现稳定控制时, 本算法仍然使系统稳定, 在本算法中, 所估计的参数在跟踪控制律前馈项中表现为非线性, 这是区别于常规参数估计自适应算法的一个最重要特征. 因此本算法控制器的设计更有灵活性, 另一方面获得更好的控制品质和鲁棒性, 特别是对参数域估计误差即参数范围估计错误的强鲁棒性, 均为仿真算例所验证.     

参数不确定非线性系统的自适应控制和鲁棒控制

研究一类参数不确定非线性系统的非自适应鲁棒控制及自适应控制问题。通过引入二人零和对策得到非自适应鲁棒控制律，并与参数估计结合得到自适应控制律。证明了参数估计有界和收敛时闭环系统Ｌｙａｐｕｎｏｖ稳定性和渐近稳定性。仿真结果说明了该方法的有效性及具体实现方法。     

不确定关联大系统对时变参数的自适应控制

考虑具有时滞的不确定非线性关联大系统的鲁棒控制问题．假设不确定时变参数为半线性或非线性系统的有界输出，通过对时变不确定参数设计自适应律，从而对不确定参数进行估计．利用线性矩阵不等式技术和自适应参数估计方法，设计出鲁棒自适应控制器，从而保证闭环系统渐近稳定．建立了可由线性矩阵不等式表示的镇定条件．仿真示例说明该方法是有效的．     

变结构神经网络自适应鲁棒控制

针对一类不确定非线性系统, 提出一种变结构神经网络自适应鲁棒控制(Variable structure neural network adaptive robust control, VSNNARC)方法. 其中变结构神经网络用于在线辨识系统未知非线性函数, 该网络利用节点激活与催眠技术进行动态调节, 减小网络规模与计算量; 自适应鲁棒控制用于网络权值学习与系统建模误差及外部扰动补偿. 采用Lyapunov稳定性分析法, 给出网络权值自适应律的形式以及鲁棒控制项的设计方法. 该方法不仅能保证系统的稳定性, 也能保证系统具有很好的瞬态性能. 将该方法应用到转台伺服系统的位置跟踪控制中, 实际运行结果表明, 该方法使系统具有很强的鲁棒性及良好的跟踪效果.     

一类基于模糊逻辑系统的非线性系统自适应跟踪控制

利用非线性不确定系统的动态数学模型和模糊逻辑系统，对不确定性的输出信息，设计出被控系统的自适应鲁棒跟踪控制器和模糊逻辑系统参数估计的自适应律．在较弱的假设条件下，证明了这种控制器能使被控系统的状态及参数估计误差一致终极有界．仿真实例表明，所提出的方法是有效的．     

一类不确定非线性系统基于特征模型的复合自适应控制

针对一类不确定非线性系统的跟踪控制问题,提出一种基于特征模型的复合自适应控制方法.该方法的创新性在于基于系统的误差特征模型,构建一种综合跟踪控制误差和模型估计误差的特征参量复合自适应律,该自适应律用于控制器设计和分析,可同时实现跟踪控制误差和模型估计误差的收敛.此外,为便于特征参量自适应律的设计和分析,根据特征参量的慢时变特性,将其视为未知标称常数项和时变误差项之和,并且选用其中常数项的估计量作为自适应控制参数.进一步,为抑制特征参量中时变误差项对系统稳定性和模型估计误差收敛性的影响,在控制器及复合自适应律设计中引入带饱和函数的非线性环节.理论分析证明闭环控制系统稳定,且跟踪控制误差和模型估计误差收敛到原点的一个邻域内.仿真结果表明,与现有仅根据模型估计误差调节的基于特征模型的自适应控制方法相比,所提出的复合自适应控制方法具有更好的控制性能.     

一类复杂控制系统分散自适应鲁棒控制器设计

基于模糊逻辑系统具有充分利用语言信息和逼近连续函数性质的思想,分析研究了一类非线性不确定复杂系统的自适应控制问题.利用系统的数学模型和模糊逻辑系统对不确定性的输出信息,设计出了复杂系统的分散自适应鲁棒控制器和模糊逻辑系统参数估计的自适应律,在较弱的假设条件下,证明了这种控制器使被控系统的状态及参数估计误差一致终极有界.仿真实例表明,所提出的方法是有效的.     

Observer‐based adaptive robust control of a class of nonlinear systems with dynamic uncertainties

In this paper, a discontinuous projection‐based adaptive robust control (ARC) scheme is constructed for a class of nonlinear systems in an extended semi‐strict feedback form by incorporating a nonlinear observer and a dynamic normalization signal. The form allows for parametric uncertainties, uncertain nonlinearities, and dynamic uncertainties. The unmeasured states associated with the dynamic uncertainties are assumed to enter the system equations in an affine fashion. A novel nonlinear observer is first constructed to estimate the unmeasured states for a less conservative design. Estimation errors of dynamic uncertainties, as well as other model uncertainties, are dealt with effectively via certain robust feedback control terms for a guaranteed robust performance. In contrast with existing conservative robust adaptive control schemes, the proposed ARC method makes full use of the available structural information on the unmeasured state dynamics and the prior knowledge on the bounds of parameter variations for high performance. The resulting ARC controller achieves a prescribed output tracking transient performance and final tracking accuracy in the sense that the upper bound on the absolute value of the output tracking error over entire time‐history is given and related to certain controller design parameters in a known form. Furthermore, in the absence of uncertain nonlinearities, asymptotic output tracking is also achieved. Copyright © 2001 John Wiley & Sons, Ltd.     

Adaptive robust control for four-motor driving servo system with uncertain nonlinearities

A novel adaptive robust control (ARC) is presented for the four-motor driving servo systems with the uncertain nonlinearities and actuation failures, such that the load tracking control is achieved with the proximate optimal-time. By applying the proposed scheme, several control objectives are achieved. First, the nonlinear synchronization algorithm is presented to maintain the velocity synchronization of each motor, which provides fast convergence without chatting. Moreover, the time-varying bias torque is applied to eliminate the effect of backlash and reduce the waste of energy. Then, the ARC is designed to achieve the proximate optimal-time output tracking with the transient performance in $L_2$ norm, where the friction and actuation failures are addressed by the adaptive scheme based on the norm estimation of unknown parameter vector. Finally, the extensive simulated and experimental results validate the effectiveness of the proposed method.     

伺服系统的复合自适应滑模控制

对于采用自适应方法的鲁棒跟踪控制系统,初始参数估计误差、参数突变、非持续激励等因素均可引起瞬态过程.瞬态性能的好坏对跟踪误差峰值及恢复时间有较大影响,是实现高性能跟踪控制的关键,而目前典型设计多采用直接自适应方法,其较差的瞬态特性制约了跟踪性能的进一步提高.针对该问题,以交流伺服系统为研究对象,将直接自适应、间接自适应及滑模控制相融合,提出一种基于有界增益遗忘最小二乘法的复合自适应滑模控制( CASMC)策略,Lyapunov分析表明该策略可实现持续激励条件下跟踪误差和参数估计误差在较大范围内的指数收敛,瞬态特性较清晰.最后,以某型火炮的方位轴伺服系统为应用背景进行仿真实验,结果显示,该控制策略在瞬态过程的误差峰值和持续时间方面均有显著改善,提高了伺服系统的跟踪性能.     

On fractional order composite model reference adaptive control

This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.     

Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

In this paper, the problem of robust adaptive fault‐tolerant tracking control with time‐varying performance bounds is investigated for a class of linear systems subject to parameter uncertainties, external disturbances and actuator failures. In order to ensure the norm of the tracking error less than the user‐defined time‐varying performance bounds, we propose a new control strategy which is predicated on the generalized restricted potential function. Compared with the existing result, a novel method which provides two design freedoms is developed to reduce the tracking error. According to the online estimation information provided by adaptive mechanism, a fault‐tolerant tracking control method guaranteeing time‐varying performance bounds is developed for robust tracking of reference model. It is shown that the closed‐loop signals are bounded and the tracking error within an a priori given, time‐varying performance bounds. A simulation result is provided to demonstrate the efficacy of the proposed fault‐tolerant tracking control method.     

未知时变惯量航天器自适应姿态跟踪容错控制

针对存在未知时变惯量不确定性、执行机构衰退故障和外部干扰力矩的非刚体航天器系统,研究了航天器自适应姿态跟踪容错控制问题,结合非线性鲁棒控制方法、自适应方法、容错控制理论和参数估计方法,提出了一种鲁棒自适应姿态跟踪容错控制器。所设计的控制器克服了执行器故障、惯量不确定性以及外界干扰对系统稳定性的影响,保证了航天器姿态及角速度能够跟踪上时变的期望状态,实现了跟踪误差系统最终一致有界稳定。最后通过数字仿真验证了所提方法的有效性,并且与已有方法进行了对比,说明了所提方法的优越性。     

Dynamical adaptive integral backstepping variable structure controller design for uncertain systems and experimental application

In this study, a dynamical adaptive integral backstepping variable structure control (DAIBVSC) system based on the Lyapunov stability theorem is proposed for the trajectory tracking control of a nonlinear uncertain mechatronic system with disturbances. In this control scheme, no prior knowledge is required on the uncertain parameters and disturbances because it is estimated by two types of dynamical adaptive laws. These adaptive laws are integrated into the dynamical adaptive integral backstepping control and variable structure control (VSC) parts of the DAIBVSC. The dynamical adaptive law in the dynamical adaptive integral backstepping control part updates parametric uncertainties, while the other in the VSC part adapts upper bounds of non‐parametric uncertainties and disturbances. In order to achieve a more robust output tracking and better parameter adaptation, the control system is extended by one integrator and sliding surface is augmented by an integral action. Experimental evaluation of the DAIBVSC is conducted with respect to performance and robustness to parametric uncertainties. Experimental results of the DAIBVSC are compared with those of a traditional VSC. The proposed DAIBVSC exhibits satisfactory output tracking performance, good estimation of the uncertain parameters and can reject disturbances with a chattering free control law. Copyright © 2017 John Wiley & Sons, Ltd.