A global state feedback output regulating control for uncertain systems in strict feedback form

A family of single-input, single-output, nonlinear systems in strict feedback form with uncertain constant parameters which appear linearly and belong to a known compact set Π is considered. A global robust output regulation problem via state feedback is addressed and solved under the assumptions that the regulator equations are solvable in Π, the output equation does not depend on uncertain parameters, no modelled disturbances affect the system and the output reference signal is generated by a known exosystem whose state is bounded and available for feedback. Robust adaptive techniques are used to guarantee closed loop boundedness and to achieve, without requiring persistency of excitation, global asymptotic output regulation for a class of feedback linearizable systems which may have unbounded uncertain tracking dynamics or may not have a well-defined global relative degree.     

Lyapunov design of global state and output feedback trackers for non-holonomic control systems

In this paper, new results are obtained for the global tracking of a class of non-holonomic dynamic systems via state and output feedback. The tracking controllers are systematically constructed on the basis of a recursive technique and a full exploitation of the system structure. When disturbances occur in a non-holonomic chained system, it is shown how to modify the controller design procedure to yield robust tracking control laws. The proposed method is demonstrated and discussed by means of a benchmark non-holonomic knife-edge mechanical system.     

Suboptimal model-matching control of large-scale systems

The decentralized technique is used to investigate the stability of the large-scale system in the presence of each isolated subsystem with optimal model matching. The optimal model matching of the isolated subsystem is first obtained by applying the parameter optimization technique to minimize a meaningful measure of model matching, then a sufficient condition is derived such that the compensators stabilize the overall system using a functional analysis technique. Moreover, a necessary and sufficient condition for the existence of such a compensator is derived by using the Nevanlinna-Pick interpolation. Finally, an optimal design algorithm is proposed to attenuate the effect of interconnection between subsystems.     

基于快速输出采样反馈的网络控制系统滑模控制

针对网络控制系统的网络诱导时延问题,提出了一种新的滑模控制方法。通过快速采样被控对象输出,建立了具有线性时不变被控对象的网络控制系统的离散模型。在此基础上,用极点配置法给出了滑模切换面参数,设计了输出反馈离散滑模控制器。仿真结果验证了该控制方法的有效性。     

Robust output feedback control of nonlinear stochastic systems using neural networks

We present an adaptive output feedback controller for a class of uncertain stochastic nonlinear systems. The plant dynamics is represented as a nominal linear system plus nonlinearities. In turn, these nonlinearities are decomposed into a part, obtained as the best approximation given by neural networks, plus a remaining part which is treated as uncertainties, modeling approximation errors, and neglected dynamics. The weights of the neural network are tuned adaptively by a Lyapunov design. The proposed controller is obtained through robust optimal design and combines together parameter projection, control saturation, and high-gain observers. High performances are obtained in terms of large errors tolerance as shown through simulations.     

Exact pole assignment using direct or dynamic output feedback

This note addresses the problem of the assignability of the eigenvalues of the matrixA + BPCby choice of the matrixP. This mathematical problem corresponds to pole assignment in the direct output feedback control problem, and by proper changes of variables it also represents the pole assignment problem with dynamic feedback controllers. The key to our solution is the introduction of the new concept of local complete assignability which in loose terms is the arbitrary perturbability, of the eigenvalues ofA + BPCby perturbations ofP. If nxis the order of the system, we show that ifA + BP_{0}Chas distinct eigenvalues, a necessary and sufficient condition for local complete assignability at P0is that the matricesC[A + BP_{0}C]^{i-1}Bbe linearly independent, for1 leq i leq n_{x}. In special cases, this condition reduces to known criteria for controllability and observability. Although these latter properties are necessary conditions for assignability, we also address the question of the assignability of uncontrollable or unobservable systems both by direct output feedback and dynamic compensation. The main result of this note yields an algorithm that assigns the closed-loop poles to arbitrarily chosen values in the direct and in the dynamic output feedback control problems.     

Quantized output feedback control for networked control systems

This paper addresses the problem of output feedback control for networked control systems (NCSs) with limited communication capacity. Firstly, we propose a new model to describe the non-ideal network conditions and the input/output state quantization of the NCSs in a unified framework. Secondly, based on our newly proposed model and an improved separation lemma, the observer-based controller is developed for the asymptotical stabilization of the NCSs, which are shown in terms of nonlinear matrices inequalities. The nonlinear problems can be computed through solving a convex optimization problems, and the observed and controller gains could be derived by solving a set of linear matrix inequalities. Thirdly, two simulation examples are given to demonstrate the effectiveness of the proposed method.     

Finite‐time consensus tracking for harmonic oscillators using both state feedback control and output feedback control

This paper investigates the distributed finite‐time consensus‐tracking problem for coupled harmonic oscillators. The objective is to guarantee a team of followers modeled by harmonic oscillators to track a dynamic virtual leader in finite time. Only a subset of followers can access the information of the virtual leader, and the interactions between followers are assumed to be local. We consider two cases: (i) The followers can obtain the relative states between their neighbors and their own; and (ii) Only relative outputs between neighboring agents are available. In the former case, a distributed consensus protocol is adopted to achieve the finite‐time consensus tracking. In the latter case, we propose a novel observer‐based dynamic protocol to guarantee the consensus tracking in finite time. Simulation examples are finally presented to verify the theoretical analysis. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive output feedback control for nonlinear time-delay systems using neural network

This paper extends the adaptive neural network （NN） control approaches to a class of unknown output feedback nonlinear time-delay systems. An adaptive output feedback NN tracking controller is designed by backstepping technique. NNs are used to approximate unknown functions dependent on time delay, Delay-dependent filters are introduced for state estimation. The domination method is used to deal with the smooth time-delay basis functions. The adaptive bounding technique is employed to estimate the upper bound of the NN approximation errors. Based on Lyapunov- Krasovskii functional, the semi-global uniform ultimate boundedness of all the signals in the closed-loop system is proved, The feasibility is investigated by two illustrative simulation examples.     

Sliding mode control design for mismatched uncertain systems using output feedback

International Journal of Control, Automation and Systems - This paper develops an output feedback sliding mode control law for linear MIMO systems having mismatched parameter uncertainties along...     

Adaptive hierarchical control for output feedback systems

In this paper, we address the problem of adaptive hierarchical control for a class of so-called uncertain output feedback systems. The proposed approach is to design an adaptive output interface dynamic by estimating the uncertainties. With the interface connected to the uncertain nonlinear system and a linear abstract system, the system could track approximately the abstraction. Finally, two examples are presented to illustrate our approach.     

基于模型的输出反馈网络控制系统反馈调度研究

针对基于模型的网络控制系统缺乏应对动态变化的网络负载问题,设计反馈调度器,依据实际的网络拥塞情况,调整基于模型的网络控制系统的状态更新时间.为应对状态不完全可测的情况,在控制结构中使用了状态观测器,并证明了所提出系统在可变更新时间情况下的稳定性.仿真结果验证了稳定性条件的正确性和新网络控制系统结构的有效性.     

Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.     

Distributed adaptive consensus control of Lipschitz nonlinear multi-agent systems using output feedback

This paper addresses output-feedback-based distributed adaptive consensus control of multi-agent systems having Lipschitz nonlinear dynamics. Distributed dynamic protocols are designed based on the relative outputs of neighbouring agents and the adaptive coupling weights, under which consensus is reached between the nonlinear systems for all undirected connected communication topologies. Extension to the case of Lipschitz nonlinear multi-agent systems subjected to external disturbances is further studied, and a robust adaptive fully distributed consensus protocol is suggested. By application of a decoupling technique, necessary and sufficient conditions for the existence of these consensus protocols are provided in terms of linear matrix inequalities. Finally, numerical simulation results are demonstrated to validate the effectiveness of the theoretical results.     

Finite‐time tracking control of uncertain nonholonomic systems by state and output feedback

This paper studies the finite‐time tracking control of nonholonomic systems in chained form with parameter uncertainties, unknown output gains, and mismatched uncertainties. To achieve the finite‐time tracking control of uncertain nonholonomic systems, we propose 2 types of controllers by state and output feedback, respectively. Both of the proposed 2 types of controllers can achieve the finite‐time output tracking control of the nonholonomic systems even in the presence of mismatched uncertainties and/or unknown gains. The effectiveness of our proposed controllers are illustrated with simulation examples.     

Robust near-optimal output feedback control of non-linear systems

This work proposes a robust near-optimal non-linear output feedback controller design for a broad class of non-linear systems with time-varying bounded uncertain variables. Both vanishing and non-vanishing uncertainties are considered. Under the assumptions of input-to-state stable (ISS) inverse dynamics and vanishing uncertainty, a robust dynamic output feedback controller is constructed through combination of a high-gain observer with a robust optimal state feedback controller synthesized via Lyapunov's direct method and the inverse optimal approach. The controller enforces exponential stability and robust asymptotic output tracking with arbitrary degree of attenuation of the effect of the uncertain variables on the output of the closed-loop system, for initial conditions and uncertainty in arbitrarily large compact sets, provided that the observer gain is sufficiently large. Utilizing the inverse optimal control approach and singular perturbation techniques, the controller is shown to be near-optimal in the sense that its performance can be made arbitrarily close to the optimal performance of the robust optimal state feedback controller on the infinite time-interval by selecting the observer gain to be sufficiently large. For systems with non-vanishing uncertainties, the same controller is shown to ensure boundedness of the states, uncertainty attenuation and near-optimality on a finite time-interval. The developed controller is successfully applied to a chemical reactor example.     

Dynamic output feedback of linear networked control systems

A new packet type of control is proposed; it consists in that measurements of the sensor made with a certain frequency are stored in the digital encoder and transmitted in one packet in the network that closes the control system. A controller is proposed for linear networked control systems with one constant time delay that completely uses the output packet at constant control signal on the whole control interval. Its algorithm is based on linear matrix inequalities. The efficiency of this approach is demonstrated by a model example.     

Receding horizon output feedback control for constrained uncertain systems using periodic invariance

In this article, we consider a receding horizon output feedback control (RHOC) method for linear discrete-time systems with polytopic model uncertainties and input constraints. First, we derive a set of estimator gains and then we obtain, on the basis of the periodic invariance, a series of state feedback gains stabilising the augmented output feedback system with these estimator gains. These procedures are formulated as linear matrix inequalities. An RHOC strategy is proposed based on these state feedback and state estimator gains in conjunction with their corresponding periodically invariant sets. The proposed RHOC strategy enhances the performance in comparison with the case in which static periodic gains are used, and increases the size of the stabilisable region by introducing a degree of freedom to steer the augmented state into periodically invariant sets.     

具有未建模动态和输出约束系统的自适应输出反馈控制

针对一类具有未建模动态和输出约束的输出反馈非线性系统, 提出一种自适应输出反馈动态面控制方案. 利用神经网络逼近未知连续函数, 分别设计K滤波器和动态信号估计不可测量的状态, 并处理动态不确定性. 引入障碍李雅普诺夫函数并设计自适应控制器以保证BLF有界, 从而实现输出约束. 理论分析表明, 闭环控制系统是半全局一致终结有界的, 且满足输出约束, 仿真结果验证了所提出方案的有效性.