共查询到20条相似文献,搜索用时 15 毫秒
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In this paper, we develop novel results on self-triggered control of nonlinear systems, subject to perturbations, and sensing/computation/actuation delays. First, considering an unperturbed nonlinear system with bounded delays, we provide conditions that guarantee the existence of a self-triggered control strategy stabilizing the closed-loop system. Then, considering parameter uncertainties, disturbances and bounded delays, we provide conditions guaranteeing the existence of a self-triggered strategy that keeps the state arbitrarily close to the equilibrium point. In both cases, we provide a methodology for the computation of the next execution time. We show on an example the relevant benefits obtained with this approach in terms of energy consumption with respect to control algorithms based on a constant sampling with a sensible reduction of the average sampling time. 相似文献
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Shubo Wang 《国际强度与非线性控制杂志
》2023,33(1):559-573
》2023,33(1):559-573
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. 相似文献
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In industrial process control, computer control, which makes the closed‐loop system a sampled‐data one containing both continuous‐ and discrete‐time signals, is widely used. In contrast with traditional approximation methods, sampled‐data synthesis, a direct digital controller design procedure without approximation, has received increasing attention during the past few years. However, many of the existing results cannot be applied to sampled‐data control design for the uncertain systems. In this paper, a result of robust asymptotic stability of sampled‐data systems with constraints on the state is presented based on a result on practical stability for these systems. Then the robust sampled‐data control for a class of uncertain nonlinear systems with constraints on the output is developed. The problem is formulated from vehicle steering control with constraint on the side slip angle of body. The result is described by some matrix inequalities which could be solved by an iterative algorithm based on the linear matrix inequality technique. Finally, a numerical example is presented to demonstrate the result. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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不确定非线性系统自适应镇定的充要条件 总被引:1,自引:0,他引:1
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. 相似文献
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In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator. 相似文献
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This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with a novel control architecture. A nonlinear state feedback controller is designed for a synchronous machine using the proposed method. The design provides improved stability and transient response in the presence of uncertainty and nonlinearity in the system and also provides a guaranteed bound on the cost function. An automatic voltage regulator to track reference terminal voltage is also provided by a state feedback equivalent robust nonlinear proportional integral controller. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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针对一类单输入单输出不确定非线性控制系统提出了一种自适应鲁棒控制算法. 由于最小均方支持向量回归机(LS-SVRM)的最终解可以化为一个具有线性约束的二次规划问题, 不存在局部极小, 所以该算法在不要求假设系统的状态向量是可测的条件下通过设计基于LS-SVRM的观测器来估计系统的状态向量; 同时在算法中假设LS-SVRM的最优逼近参数向量和标称参数向量之差的范数和逼近误差的界限是未知的, 因此可通过对未知界限估计的调节来提高系统的鲁棒性. 考虑到LS-SVRM本身参数对LS-SVRM性能的影响, 本文应用一种新的免疫优化算法对LS-SVRM的参数进行优化, 从而提高LS-SVRM的逼近能力. 理论研究和仿真例子证实了所提方法的可行性和有效性. 相似文献
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基于神经网络的严反馈块非线性系统的鲁棒控制 总被引:9,自引:0,他引:9
针对非匹配不确定性的严反馈块非线性系统,基于神经网络提出一种鲁棒控制方法.利用Lyapunov稳定性定理推导出RBF神经网络的全调节律,用于处理系统中的非线性参数不确定性,提高了神经网络的在线逼近能力;采用神经网络和鲁棒控制方法,利用已知信息的同时,对控制系数矩阵未知时的设计问题进行处理,避免了控制器可能的奇异问题;引入非线性跟踪微分器,解决了Backstepping设计中的“计算膨胀”问题.运用Lyapunov稳定性定理证明了闭环系统的所有信号均最终一致有界. 相似文献
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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. 相似文献
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This article is concerned with operator-based robust control for nonlinear feedback system with unknown perturbations with simplified robust right coprime factorisation method. By the designed simplified robust controllers, the Bezout identity for the nominal nonlinear system and the perturbed nonlinear system are guaranteed to be simply satisfied, which means that not only the nonlinear system with nominal plant but also that with perturbed plant can be stabilised. Moreover, the plant output can be guaranteed to asymptotically track the reference output. The effectiveness of the proposed design scheme is verified by the simulation results. 相似文献
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A new integral inequality and its applications to robust control problems of uncertain nonlinear systems 下载免费PDF全文
Hansheng Wu 《国际强度与非线性控制杂志
》2018,28(15):4584-4603
》2018,28(15):4584-4603
In this paper, a new integral inequality is presented. By combining this integral inequality with adaptive approach, new design methods can be developed to synthesize some adaptive robust control schemes for a large class of uncertain nonlinear systems and to deal with well the unknown nonlinearities appearing in uncertain nonlinear control dynamical systems. As an application of the presented integral inequality to control theory, the robust stabilization problem is considered for a class of uncertain strict‐feedback nonlinear systems with both time‐delay and unknown dead‐zone input nonlinearities. It is shown that there are two main merits in the design method based on the integral inequality presented in this paper. The first one is that one need not estimate and know the unknown nonlinearities to synthesize some stabilizing control schemes. The second one is that the resulting feedback control schemes have rather simple structure. 相似文献
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A new robust state‐feedback controller is designed to solve the tracking problem of a class of nonlinear uncertain systems. The contributions of our paper are threefold: Firstly, a new robust state‐feedback controller with a simple structure is derived. Owing to its simplicity, less computation is needed. What is more, for polynomial‐type uncertainties, a much simpler controller can be derived directly without the need of computing partial derivatives. Secondly, a technique that leaves positive functions used in the nonlinear damping terms to be chosen freely is introduced which may enable us to find out a good one among all candidate positive functions to reduce the control effort and to design a ‘softer’ controller. Thirdly, the assumption made in non‐adaptive robust control schemes where the bounding functions are required to be exactly known is relaxed, and the assumption on the reference signal is relaxed too. When our robust controller is applied, the simulations show that better performance can be achieved with less control effort. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
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A new approach to design a Nonlinear Model Predictive Control law that employs an approximate model, derived directly from data, is introduced. The main advantage of using such models lies in the possibility to obtain a finite computable bound on the worst‐case model error. Such a bound can be exploited to analyze the robust convergence of the system trajectories to a neighborhood of the origin. The effectiveness of the proposed approach, named Set Membership Predictive Control, is shown in a vehicle lateral stability control problem, through numerical simulations of harsh maneuvers. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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We investigate the global robust tracking problem via output feedback for a class of cascade nonlinear systems with dynamic uncertainties and non-vanishing disturbances. It does not require a priori knowledge of the sign of the high-frequency gain. A recursive design scheme is presented using the ideas of pseudosign function, Nussbaum-type gain technique and the deadzone method. It is shown that under some conditions, the tracking error can be guaranteed asymptotic to the interval [?ε, ε]?? with arbitrary prescribed ε>0 after a finite time, while keeping all signals of the resulting closed-loop systems bounded. The simulation results demonstrate the effectiveness of the proposed algorithm. 相似文献