This paper deals with output regulation of a class of large-scale nonlinear systems with delays. Each of the subsystems is in the output feedback form, with nonlinear functions of the subsystem output and the outputs of other subsystems. The system outputs are subject to unknown constant delays. Both the system dynamics and the measurements are subject to unknown disturbances generated from unknown linear exosystems. Decentralized control design approach is adopted to design local controllers using measurements or regulated errors in each subsystems. It is shown in this paper that delays in the outputs of subsystems do not affect the existence of desired feedforward control input, and the invariant manifolds and the desired feedforward inputs always exist if the nonlinear functions are polynomials. Through a special parameterization of an augmented exosystem, an internal model can be designed for each subsystem, without the involvements of the uncertain parameters. The uncertain parameters affected by the uncertainty of the exosystem are estimated using adaptive control laws, and adaptive coefficients in the control inputs are used to suppress other uncertainties. The proposed decentralized adaptive control strategy ensures the global stability of the entire system, and the convergence to zero of the regulated errors. An example is included to demonstrate the proposed control strategy.
The problem of the decentralized robust tracking and model following is considered for a class of uncertain large scale systems including time-varying delays in the interconnections. On the basis of the Razumikhin-type theorem and the Lyapunov stability theory, a class of decentralized memoryless local state feedback controllers is proposed for robust tracking of dynamical signals. It is shown that by employing the proposed decentralized robust tracking controllers, one can guarantee that the tracking error between each time-delay subsystem and the corresponding local reference model without time-delay decreases uniformly asymptotically to zero. In this paper, it is assumed that the time-varying delays are any continuous and bounded nonnegative functions, and the proposed decentralized robust tracking controllers are independent of the delays. Therefore, the results obtained in the paper are applicable to large scale systems without exact knowledge of the delays, i. e. large systems with perturbed delays.
The primary objective of the present paper is to develop an approach for analyzing pinning synchronization stability in a complex delayed dynamical network with directed coupling. Some simple yet generic criteria for pinning such coupled network are derived analytically. Compared with some existing works, the primary contribution is that the synchronization manifold could be chosen as a weighted average of all the nodes states in the network for the sake of practical control tactics, which displays the different influences and contributions of the various nodes in synchronization seeking processes of the dynamical network. Furthermore, it is shown that in order to drive a complex network to a desired synchronization state, the coupling strength should vary according to the controller. In addition, the theoretical results about the time-invariant network is extended to the time-varying network, and the result on synchronization problem can also be extended to the consensus problem of networked multi-agent systems. Subsequently, the theoretic results are illustrated by a typical scale-free (SF) neuronal network. Numerical simulations with three kinds of the homogenous solutions, including an equilibrium point, a periodic orbit, and a chaotic attractor, are finally given to demonstrate the effectiveness of the proposed control methodology.
Time delay in the mediation of ventilation (VE) by arterial CO2 pressure (PaCO2) was studied during recovery from short impulse-like exercises with different work loads of recovery. Subjects performed two tests including 10-s impulse like exercise with work load of 200 watts and 15-min recovery with 25 watts in test one and 50 watts in test two. V . E, end tidal CO2 pressure (PETCO2) and heart rate (HR) were measured continuously during rest, warming up, exercise and recovery. PaCO2 was estimated from PETCO2 and tidal volume (VT). Results showed that predicted arterial CO2 pressure (PaCO2 pre) increased during recovery in both tests. In both tests, VE increased and peaked at the end of exercise. VE decreased in the first few seconds of recovery but started to increase again. The highest correlation coefficient between PaCO2 pre and V . E was obtained in the time delay of 7 s (r=0.854) in test one and in time delays of 6 s (r=0.451) and 31 s (r=0.567) in test two. HR was significantly higher in test two than in test one. These results indicate that PaCO2 pre drives VE with a time delay and that higher work intensity induces a shorter time delay., R. Afroundeh, T. Arimitsu, R. Yamanaka, C. S. Lian, K. Shirakawa, T. Yunoki, T. Yano., and Obsahuje bibliografii
The topology identification issue of complex stochastic network with delay and stochastic disturbance is mainly introduced in this paper. It is known the time delay and stochastic disturbance are ubiquitous in real network, and they will impair the identification of network topology, and the topology capable of identifying the network within specific time is desired on the other hand. Based on these discussions, the finite-time identification method is proposed to solve similar issues problems. The validity of theoretical results is proved with the stochastic dynamical system stability theory and finite-time stability theory. Finally, a simple numerical simulation is proposed to verify the feasibility of the method.
In this paper, we address the strong practical stabilization problem for a class of uncertain time delay systems with a nominal part written in triangular form. We propose, firstly, a strong practical observer. Then, we show that strong practical stability of the closed loop system with a linear, parameter dependent, state feedback is achieved. Finally, a separation principle is established, that is, we implement the control law with estimate states given by the strong practical observer and we prove that the closed loop system is strong practical stable. With the help of a numerical example, effectiveness of the proposed approach is demonstrated.