控制方向未知的SISO非仿射系统间接自适应模糊输出反馈控制

针对一类单输入单输出(SISO)非仿射非线性系统控制方向未知时出现的控制器奇异问题,提出了一种间接自适应模糊控制方案.利用中值定理将非仿射系统转化为仿射系统,通过模糊逻辑系统逼近该仿射系统中的未知函数,并构造模糊控制器,同时利用Lyapunov稳定性定理设计自适应律,最终克服了控制器的奇异问题;在此基础上,通过构造观测器估计跟踪误差,设计输出反馈自适应模糊控制器,解决了状态不可测时系统控制器设计难题,采用Lyapunov稳定性定理证明控制器能使得跟踪误差收敛同时闭环系统所有信号均有界.仿真结果验证了所设计控制方案的可行性与有效性.     

Adaptive dynamic surface control for uncertain nonaffine nonlinear systems

This paper focuses on the problem of adaptive control for uncertain nonaffine nonlinear systems. The original nonaffine systems are transformed into the augmented affine systems via adding an auxiliary integrator, which makes the explicit control design possible. By introducing a modified sliding mode filter in each step, a novel adaptive dynamic surface controller is proposed, where the ‘explosion of complexity’ problem inherent in the backstepping design is avoided. It is proven rigorously that for any initial control condition, the proposed adaptive scheme is able to ensure the semiglobal uniformly ultimately boundedness of all signals in the closed loop. An illustrative example is carried out to verify the effectiveness of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.     

基于Backstepping 的非仿射非线性系统鲁棒控制

针对一类不确定非仿射非线性系统的跟踪控制问题, 提出一种鲁棒Backstepping 控制策略. 首先, 为利用仿 射非线性方法设计控制器, 给出一种适用于全局的非仿射非线性近似方法; 然后, 设计快速收敛非线性微分器以估计复合干扰和获取虚拟信号的微分, 进而给出不确定非仿射非线性系统的复合控制器, 其中鲁棒项和阻尼项分别用于减少逼近误差和近似方法中动态误差对系统跟踪的影响; 最后, 通过仿真实验验证了所提出方法的有效性.     

Decentralised direct adaptive output feedback fuzzy controller for a class of large-scale nonaffine nonlinear systems and its applications

A novel cooperation-based decentralised direct adaptive fuzzy control via output feedback is developed for a class of large-scale nonaffine uncertain nonlinear systems using a direct adaptive fuzzy approach in this article. Under assumption that all the controllers share their prior information about the subsystem reference models, the interconnections between subsystems are relaxed to arbitrarily strong nonlinearities without matching conditions. The assumption on input gains is extended from typical positive constants to highly nonlinear functions. The feedback and adaptation mechanisms require neither the typical observation error filtering nor the famous strictly positive-real condition. Based on Lyapunov's direct method, the tracking errors of the closed-loop large-scale system are guaranteed to converge to tunable neighbourhoods of the origin. The proposed algorithm is applied to controlling two mechanical large-scale systems and simulation results substantiate its effectiveness.     

基于预设性能的非仿射非线性系统自适应有限时间控制

针对一类具有死区的非仿射非线性系统,将预设性能控制与有限时间控制相结合,提出一种具有预设性能的自适应有限时间跟踪控制方法.基于Backstepping技术、模糊逻辑系统及有限时间Lyapunov稳定理论,给出使系统半全局实际有限时间稳定(semi-globally practically finite-time stable,SGPFS)的充分条件和设计步骤.该控制策略不仅使系统的输出误差在有限时间内收敛到一个预先设定区域,同时保证其收敛速度、最大超调量和稳态误差均满足预先设定的性能要求.最后通过仿真示例验证了所提出设计方法的有效性.     

Decentralised direct adaptive fuzzy control for a class of large-scale nonaffine nonlinear systems and application to AHS

A novel decentralised direct adaptive fuzzy controller design is presented for a class of large-scale nonaffine uncertain nonlinear systems in this article. By integrating a fuzzy logic system and H _∞ tracking technique, the designed controller is able to adaptively compensate for interconnections and disturbances with unknown bounds, but none of the control and adaptation laws contains a sign function so that control chattering can be shunned. The closed-loop large-scale system is guaranteed to be asymptotically stable and obtain good H _∞ tracking performance. The control approach developed is applied to the following control problem of a string of vehicles within an automated highway system (AHS) and simulation results verify its validity.     

一类输入饱和非仿射非线性系统的非线性动态逆控制

输入饱和是实际系统中经常遇到的问题,很多已有的控制方法要求被控系统具有仿射结构.本文针对一类具有输入饱和的非仿射纯反馈非线性系统提出了一种基于奇异值摄动理论的非线性动态逆控制方法.首先构建一个快变子系统,在慢时间尺度下将非仿射非线性系统转换为具有仿射结构的线性系统,从而应用已有的控制算法实现控制目的.为了消除输入饱和带...     

Multiple model adaptive control for a class of nonlinear systems with unknown control directions

This study introduces an improved multiple model adaptive control (MMAC) algorithm for a class of nonlinear discrete-time systems. The controller consists of a linear direct adaptive controller, a neural network-based nonlinear direct adaptive controller and a switching mechanism. The assumption of the nonlinear term is relaxed by incorporating a parameter estimator with an augmented error. The control direction of the system is not required to be known by employing a linear direct adaptive controller with the discrete Nussbaum gain and future output predictions. The stability of the closed-loop systems applying the proposed MMAC method is proved and the improved transient performance of the system is illustrated by the simulation results.     

一类不确定非线性系统的鲁棒自适应控制

针对一类MIMO不确定非线性系统的输出跟踪问题, 基于自适应反步法和滑模控制为其设计了鲁棒自适应控制器. 模型包含3种不确定性: 1) 参数不确定性; 2) 输入增益的不确定性; 3) 代表系统未建模动态和干扰的不确定函数, 该函数有界. 以非完整移动机械臂的输出跟踪控制为目标, 对其进行仿真实验, 实验结果表明所提出的控制算法是正确有效的.     

Robust adaptive self-structuring fuzzy control design for nonaffine,nonlinear systems

In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L ₂ tracking performance to stabilise the closed-loop system. This L ₂ tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.     

Direct adaptive control for a class of discrete‐time unknown nonaffine nonlinear systems using neural networks

In this paper, a direct adaptive state‐feedback control approach is developed for a class of nonlinear systems in discrete‐time (DT) domain. We study MIMO unknown nonaffine nonlinear DT systems and employ a two‐layer NN to design the controller. By using the presented method, the NN approximation is able to cancel the nonlinearity of the unknown DT plant. Meanwhile, pretraining is not required, and the weights of NNs used in adaptive control are directly updated online. Moreover, unlike standard NN adaptive controllers yielding uniform ultimate boundedness results, the tracking error is guaranteed to be uniformly asymptotically stable by utilizing Lyapunov's direct method. Two illustrative examples are provided to demonstrate the effectiveness and the applicability of the theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive robust asymptotic tracking control of nonaffine nonlinear systems

This article investigates the barrier lyapunov function-based adaptive robust control scheme for nonaffine nonlinear systems with unknown system dynamics. First, the nonaffine system is converted into affine system via a combination of first-order filter and coordinate transformation, then a high-gain observer is utilized to reconstruct the immeasurable states of the derived affine system. Second, a robust integral of the sign of the error (RISE) is incorporated into the control design to reject the unknown dynamics. Third, a barrier lyapunov function based design method is used to ensure that the input vector to the parameter estimation remain within a predefined region. Then, an adaptive robust control scheme with only one adaptive parameter by using the upper bound estimation is developed. Finally, numerical simulations validate the efficacy of the developed control scheme.     

时变时滞非仿射大系统的分散自适应控制

针对一类具有未知时变时滞的非仿射互联大系统基于神经网络的逼近能力, 提出了一种分散自适应神经网络控制方案。该方案利用中值定理对未知非仿射函数进行分离; 利用分离技术和Young's不等式放宽了对未知时滞及时滞互联不确定项的限制, 同时大大减少了在线调节参数的数量。此外, 利用Lyapunov Krasovskii 泛函补偿了未知时滞带来的不确定性。通过理论分析, 证明了闭环系统所有信号是有界的, 输出跟踪误差收敛到原点的一个小邻域内。最后, 仿真结果验证了所提控制方案的有效性。     

Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems

An adaptive fuzzy control approach is proposed for a class of multiple-input-multiple-output (MIMO) nonlinear systems with completely unknown nonaffine functions. The MIMO systems are composed of n subsystems and each of subsystems is in the nested lower triangular form. It is difficult and complicated to control this class of systems due to the existence of unknown nonaffine functions and the couplings among the nested subsystems. This difficulty is overcome by introducing some special type Lyapunov functions and taking advantage of the mean-value theorem, the backstepping design method and the approximation property of the fuzzy systems. The proposed control approach can guarantee that all the signals in the closed-loop system are bounded. A simulation experiment is utilized to verify the feasibility of the proposed approach.     

不确定非线性系统自适应镇定的充要条件

研究了一类相当广泛的包含未知参数的非线性控制系统的自适应鲁棒控制问题,这类系统的标称系统包含一些非最小相位非线性系统和一些不存在相对阶的非线性系统．其未知定常参数是线性的．在一定假设条件下,对该类系统给出了存在自适应控制器的充要条件,并采用backstepping方法给出了控制器的设计步骤．所得主要结论没有用到增长性假设、最小相位假设和相对阶的假设．同时,还给出了不存在相对阶及非最小相位的非线性系统的例子,对于后者给出了控制器的设计过程．     

Switched adaptive control for a class of switched nontriangular nonlinear systems with vanishing control gains

In this paper, the adaptive control problem for a class of switched nontriangular nonlinear systems is investigated, which allows the control gains to vanish at some points. Neither the triangular structure nor the solvability of the adaptive control problem is required for each subsystem. A key point of this work is to solve the adaptive control problem of switched nontriangular nonlinear systems with vanishing control gains by the dual design of the controllers and switching signals. To this end, firstly, a hysteresis‐type control gains‐dependent switching law is designed, which makes the control gain of the active subsystem not vanish and thus the associated designed control input can enter into the active subsystem. Moreover, the designed switching law guarantees a dwell time between any adjacent switching instants, which rules out the Zeno behavior. Secondly, when the adaptive control problem of each subsystem is unsolvable, a sufficient condition ensuring the solvability of the adaptive control problem of switched nontriangular nonlinear systems is developed even if no control input can enter into subsystems at some points. Finally, the effectiveness of the proposed result is illustrated by two examples.     

Sliding mode adaptive control for a class of nonlinear time‐varying systems

In this work, the problem of designing a control scheme capable of controlling dynamical systems with unknown time‐varying parameters and disturbances is proposed. In contrast with other works, based on two techniques, ie, adaptive backstepping and sliding modes, an improved method that guarantees the output asymptotic tracking of a smooth reference signal, the stability of the closed‐loop system, and the identification errors' boundedness is developed. By means of sliding mode observers, the adaptation errors' required information is extracted and injected to adaptive laws. The behavior of the proposed control scheme is analyzed by the Lyapunov method. The performance of the proposed system is verified with an academic example.     

Robust decentralized adaptive fuzzy control for a class of large‐scale MIMO nonlinear systems

In this paper, a novel decentralized robust adaptive fuzzy control scheme is proposed for a class of large‐scale multiple‐input multiple‐output uncertain nonlinear systems. By virtue of fuzzy logic systems and the regularized inverse matrix, the decentralized robust indirect adaptive fuzzy controller is developed such that the controller singularity problem is addressed under a united design framework; no a priori knowledge of the bounds on lumped uncertainties are being required. The closed‐loop large‐scale system is proved to be asymptotically stable. Simulation results confirmed the validity of the approach presented. Copyright © 2011 John Wiley & Sons, Ltd.     

Robust adaptive neural control for a class of uncertain MIMO nonlinear systems

In this paper, a novel robust adaptive neural control scheme is proposed for a class of uncertain multi-input multi-output nonlinear systems. The proposed scheme has the following main features: (1) a kind of Hurwitz condition is introduced to handle the state-dependent control gain matrix and some assumptions in existing schemes are relaxed; (2) by introducing a novel matrix normalisation technique, it is shown that all bound restrictions imposed on the control gain matrix in existing schemes can be removed; (3) the singularity problem is avoided without any extra effort, which makes the control law quite simple. Besides, with the aid of the minimal learning parameter technique, only one parameter needs to be updated online regardless of the system input–output dimension and the number of neural network nodes. Simulation results are presented to illustrate the effectiveness of the proposed scheme.     

一类非线性离散系统的直接自适应模糊控制

针对一类含延迟非线性离散系统,提出了一种直接自适应模糊控制器设计的新方案．将系统用T-S模糊模型来表示,并基于并行分布补偿(PDC)基本思想设计了一种具有未知参数的模糊控制器,同时采用梯度下降算法对该控制器的参数进行在线辨识．通过输入到状态稳定(ISS)方法,证明了系统输出和参考输出的误差有界且满足一定的平均性能．仿真表明本方法的有效性．