Decentralized adaptive neural control for interconnected stochastic nonlinear delay-time systems with asymmetric saturation actuators and output constraints     

Wenjie Si  Xunde Dong  Feifei Yang 《Journal of The Franklin Institute》2018,355(1):54-80

This paper investigates the problem of decentralized adaptive backstepping control for a class of large-scale stochastic nonlinear time-delay systems with asymmetric saturation actuators and output constraints. Firstly, the Gaussian error function is employed to represent a continuous differentiable asymmetric saturation nonlinearity, and barrier Lyapunov functions are designed to ensure that the output parameters are restricted. Secondly, the appropriate Lyapunov–Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. At last, based on Lyapunov stability theory, a decentralized adaptive neural control method is proposed, and the designed controller decreases the number of learning parameters. It is shown that the designed controller can ensure that all the closed-loop signals are 4-Moment (or 2 Moment) semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of the origin. Two examples are provided to show the effectiveness of the proposed method.  相似文献   

State estimation for networked systems with Markovian communication constraints and multiple packet dropouts     

Wei Liu  Kaijiang Yu  Xingguo Tan  Xuhui Bu 《Journal of The Franklin Institute》2018,355(2):878-901

In this paper, the state estimation problem for discrete-time networked systems with communication constraints and random packet dropouts is considered. The communication constraint is that, at each sampling instant, there is at most one of the various transmission nodes in the networked systems is allowed to access a shared communication channel, and then the received data are transmitted to a remote estimator to perform the estimation task. The channel accessing process of those transmission nodes is determined by a finite-state discrete-time Markov chain, and random packet dropouts in remote data transmission are modeled by a Bernoulli distributed white sequence. Using Bayes’ rule and some results developed in this study, two state estimation algorithms are proposed in the sense of minimum mean-square error. The first algorithm is optimal, which can exactly compute the minimum mean-square error estimate of system state. The second algorithm is a suboptimal algorithm obtained under a lot of Gaussian hypotheses. The proposed suboptimal algorithm is recursive and has time-independent complexity. Computer simulations are carried out to illustrate the performance of the proposed algorithms.  相似文献   

Enhanced Finite Spectrum Assignment with disturbance compensation for LTI systems with input delay     

Tito L.M. Santos  Taniel S. Franklin 《Journal of The Franklin Institute》2018,355(8):3541-3566

This paper presents a Finite Spectrum Assignment (FSA) with a generalized feedforward control for Linear Time-Invariant (LTI) systems with input delay and bounded unmeasured disturbances. A novel two-layer feedforward strategy is proposed in order to deal with matched and unmatched disturbances. The proposed control law is based on a filtered disturbance estimator and a generalized feedforward compensation which can be applied to any Artstein based predictor. An optimization design procedure is presented to improve disturbance attenuation properties in the presence of band-limited disturbances. The conditions to achieve disturbance rejection are also shown to deal with deterministic disturbance models. Furthermore, the proposed solution can be used to define either continuous-time or discrete-time control algorithms. Two case studies are presented to illustrate the benefits of the new approach.  相似文献   

Robust event-driven tracking control with preassigned performance for uncertain input-quantized nonlinear pure-feedback systems     

Yun Ho Choi  Sung Jin Yoo 《Journal of The Franklin Institute》2018,355(8):3567-3582

This paper presents a simplified design methodology for robust event-driven tracking control of uncertain nonlinear pure-feedback systems with input quantization. All nonlinearities and quantization parameters are assumed to be completely unknown. Different from the existing event-driven control approaches for systems with completely unknown nonlinearities, the main contribution of this paper is to design a simple event-based tracking scheme with preassigned performance, without the use of adaptive function approximators and adaptive mirror models. It is shown in the Lyapunov sense that the proposed event-driven low-complexity tracker consisting of nonlinearly transformed error surfaces and a triggering condition can achieve the preselected transient and steady-state performance of control errors in the presence of the input quantization.  相似文献   

Reliable H_∞ control on saturated linear Markov jump system with uncertain transition rates and asynchronous jumped actuator failure     

Stephen L. Campbell 《Journal of The Franklin Institute》2018,355(9):3853-3872

This paper is concerned with reliable H_∞?control for saturated linear Markov jump systems with uncertain transition rates and asynchronous jumped actuator failure. The actuator failures are assumed to occur randomly under the Markov process with a different jumping mode from the system jumping mode. In considering the mixed-mode-dependent state feedback controller, both H_∞ stochastic stability analysis for closed-loop system with completely accessible transition rates and uncertain transition rates are investigated. Moreover, based on the obtained stability conditions, the H_∞?control problems are investigated, and the controller gains can be obtained by solving a convex optimization problem with minimizing H_∞ performance as objective and linear matrix inequalities (LMIs) as constraints. The problem of designing state feedback controllers such that the estimate of the domain of attraction is enlarged is also formulated and solved as an optimization problem with LMI constraints. Simulation results are presented to illustrate the effectiveness of the proposed results.  相似文献   

Approximate decoupling and output tracking for MIMO nonlinear systems with mismatched uncertainties via ADRC approach     

Ze-Hao Wu  Bao-Zhu Guo 《Journal of The Franklin Institute》2018,355(9):3873-3894

In this paper, we consider output tracking for a class of MIMO nonlinear systems which are composed of coupled subsystems with vast mismatched uncertainties. First, all uncertainties influencing the performance of controlled outputs, which include internal unmodelled dynamics, external disturbances, and uncertain nonlinear interactions between subsystems, are refined into the total disturbance in the control channels of subsystems. The total disturbance is shown to be sufficiently reflected in the measured output of each subsystem so that it can be estimated in real time by an extended state observer (ESO) in terms of the measured outputs. Second, we decouple approximately the MIMO systems by cancelling the total disturbance based on ESO estimation so that each subsystem becomes approximately independent linear time invariant one without uncertainty and interaction with other subsystems. Finally, we design an ESO based output feedback for each subsystem separately to ensure that the closed-loop state is bounded, and the closed-loop output of each subsystem tracks practically a given reference signal. This is completely in comply with the spirit of active disturbance rejection control (ADRC). Some numerical simulations are presented to demonstrate the effectiveness of the proposed output feedback control scheme.  相似文献   

Global asymptotic stabilization for input-delay chained nonholonomic systems via the static gain approach     

Xiandong Chen  Xianfu Zhang  Chenghui Zhang  Le Chang 《Journal of The Franklin Institute》2018,355(9):3895-3910

In this paper, a novel control strategy is proposed for asymptotically stabilizing chained nonholonomic systems with input delay. Firstly, by using the input-state-scaling technique and the static gain control method, the stabilization control problem of such systems is transformed into designing two gain parameters to stabilize a class of generalized feedback systems with state delay. Then, based on the Lyapunov–Krasovskii theorem, the stability analysis of the closed-loop systems is achieved by the appropriate selection of the gain parameters, and the state and output feedback controllers are constructed simultaneously. An illustrative example is also provided to demonstrate the effectiveness of the proposed strategy.  相似文献   

Time-varying formation tracking for high-order multi-agent systems with switching topologies and a leader of bounded unknown input     

Jianglong Yu  Xiwang Dong  Qingdong Li  Zhang Ren 《Journal of The Franklin Institute》2018,355(5):2808-2825

Time-varying formation tracking problems for high-order multi-agent systems with switching topologies are investigated. Different from the previous work, the states of the followers form a predefined time-varying formation while tracking the state of the leader with bounded unknown control input. Besides, the communication topology can be switching, and the dynamics of each agent can have nonlinearities. Firstly, a nonlinear time-varying formation tracking control protocol is presented which is constructed using only local neighboring information. Secondly, an algorithm with four steps is proposed to design the time-varying formation tracking protocol, where the time-varying formation tracking feasibility condition is introduced. Thirdly, by using the Lyapunov theory, the stability of the proposed algorithm is proven. It is proved that the high-order multi-agent system with switching topologies achieves the time-varying formation tracking if the feasibility condition holds and the dwell time is larger than a positive constant. Finally, a numerical example with six followers and one leader is given to demonstrate the effectiveness of the obtained results.  相似文献   

Maximum likelihood carrier frequency offset estimation algorithm with adjustable frequency acquisition region     

Yung-Yi Wang  Chun-Wei Huang  Wei-Wei Chen 《Journal of The Franklin Institute》2018,355(5):2978-2985

This study presents a simple yet effective carrier frequency offset (CFO) estimation algorithm for orthogonal frequency division multiplexing (OFDM) systems. At the transmitter, the proposed algorithm uses null subcarriers to render the OFDM signal periodic in the time domain. At the receiver, these periodic time samples become CFO-bearing signals, which can be adopted to develop the maximum likelihood (ML) CFO estimation algorithm accordingly. In addition to providing reliable and efficient CFO estimation, the proposed algorithm has an adjustable acquisition region linearly proportional to the order of the null subcarrier insertion scheme.  相似文献   

Distributed cooperative learning for a group of uncertain systems via output feedback and neural networks     

Wu Ai  Weisheng Chen  Shaoyong Hua 《Journal of The Franklin Institute》2018,355(5):2536-2561

This paper studies the problem of adaptive neural network (NN) output-feedback control for a group of uncertain nonlinear multi-agent systems (MASs) from the viewpoint of cooperative learning. It is assumed that all MASs have identical unknown nonlinear dynamic models but carry out different periodic control tasks, i.e., each agent system has its own periodic reference trajectory. By establishing a network topology among systems, we propose a new consensus-based distributed cooperative learning (DCL) law for the unknown weights of radial basis function (RBF) neural networks appearing in output-feedback control laws. The main advantage of such a learning scheme is that all estimated weights converge to a small neighborhood of the optimal value over the union of all system estimated state orbits. Thus, the learned NN weights have better generalization ability than those obtained by traditional NN learning laws. Our control approach also guarantees the convergence of tracking errors and the stability of closed-loop system. Under the assumption that the network topology is undirected and connected, we give a strict proof by verifying the cooperative persisting excitation condition of RBF regression vectors. This condition is defined in our recent work and plays a key role in analyzing the convergence of adaptive parameters. Finally, two simulation examples are provided to verify the effectiveness and advantages of the control scheme proposed in this paper.  相似文献