Uncertain Networked Systems Research Articles

Distributed Consensus Formation Control with Collision and Obstacle Avoidance for Uncertain Networked Omnidirectional Multi-robot Systems Using Fuzzy Wavelet Neural Networks

This paper presents a distributed consensus formation control with collision and obstacle avoidance using fuzzy wavelet neural networks (FWNNs) for a group of networked mobile Mecanum-wheeled omnidirectional robots (MWORs) with uncertainties. The dynamic behavior of each uncertain MWOR is modeled by a reduced three-input–three-output second-order state equation with uncertainties, and the multi-MWOR system is modeled by graph theory. Using the Lyapunov stability theory and online learning the system uncertainties via FWNNs, an adaptive and distributed consensus backstepping control approach is presented to carry out formation control in the presence of uncertainties. Collision and obstacle-avoidance methods are provided to avoid any collisions among MWORs and their working environments. Five simulations are conducted to show the effectiveness and merit of the proposed method .

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Asymmetric Actuator Backlash Compensation in Quantized Adaptive Control of Uncertain Networked Nonlinear Systems

This paper mainly aims at the problem of adaptive quantized control for a class of uncertain nonlinear systems preceded by asymmetric actuator backlash. One challenging problem that blocks the construction of our control scheme is that the real control signal is wrapped in the coupling of quantization effect and nonsmooth backlash nonlinearity. To resolve this challenge, this paper presents a two-stage separation approach established on two new technical components, which are the approximate asymmetric backlash model and the nonlinear decomposition of quantizer, respectively. Then the real control is successfully separated from the coupling dynamics. Furthermore, by employing the neural networks and adaptation method in control design, a quantized controller is developed to guarantee the asymptotic convergence of tracking error to an adjustable region of zero and uniform ultimate boundedness of all closed-loop signals. Eventually, simulations are conducted to support our theoretical results.

Robust filtering for uncertain networked systems with randomly delayed and lost measurements

This paper investigates the problem of robust filtering for networked linear time-varying systems with norm-bounded modelling uncertainties. Delay and dropout of measurement data in the transmission from sensor to filter are both modelled by a Bernoulli distributed random sequence. Finite-horizon two-stage Kalman filters are introduced whether or not the data packets in the network are time stamped. The parameters of robust Kalman filters are determined such that the covariances of the estimation errors are bounded and these upper bounds are guaranteed to be minimal. Novel augmented state vectors are used to extract procedures for computation of filters’ parameters. Lastly, simulation results are presented to demonstrate the superior performance of the proposed approach compared the existing methods in the literature.

Complex function projective synchronization of general networked chaotic systems by using complex adaptive fuzzy logic

This paper is concerned with the problem of complex function projective synchronization for uncertain networked chaotic complex systems. Based on Lyapunov stability, an adaptive control method is proposed for complex modified projective synchronization, which guarantees that the general drive-response networked chaotic complex systems are synchronized up to a complex scaling function matrix. Moreover, a complex fuzzy logic-based observer is designed to compensate for the model uncertainties and the external disturbances that exist in response networks, without prior information about uncertain factors. Numerical simulations are presented to demonstrate the effectiveness of the proposed method.

Discrete-Time Sliding Mode Control for Uncertain Networked System Subject to Time Delay

We deal with uncertain systems with networked sliding mode control, subject to time delay. To minimize the degenerative effects of the time delay, a simpler format of state predictor is proposed in the control law. Some ultimate bounded stability analyses and stabilization conditions are provided for the uncertain time delay system with proposed discrete-time sliding mode control strategy. A numerical example is presented to corroborate the analyses.

Improved robust finite-horizon Kalman filtering for uncertain networked time-varying systems

A novel robust finite-horizon Kalman filter is presented for networked linear time-varying systems with norm-bounded parameter uncertainty whether, or not, the data packets in the network are time-stamped. Measured data loss and latency in the communication link are both described by a Bernoulli distributed random sequence. Then, a two-stage recursive structure is employed for the robust Kalman filter. The filter parameters are determined such that the covariance of the estimation error does not exceed the prescribed upper bound. New augmented state-space model is employed to derive a procedure for computation of the filter parameters. The main novelty of the paper is to use the measurement reorganization technique for the robust Kalman filter design where the observation dropout and delay are both modeled by a stochastic process. Finally, the simulation results confirm the outperformance of the proposed robust Kalman filter compared to the rival methods in the literature.

Distributed Control of Uncertain Networked Systems: A Decoupled Design

This paper studies interconnected networked control systems in the presence of communication constraints and plant uncertainties. We propose a novel control architecture, where a reference model is introduced in each subsystem with the objective of generating the data for network broadcast as well as local feedback control. With this structure, the co-design of an output-feedback control strategy and the required communication protocol can be decoupled: the local controller only needs to address the uncertainty in the system dynamics, while the communication protocol purely focuses on the limitations due to communication channels. As a result, one can integrate the existing communication protocols and robust control techniques into this architecture without worrying about the coupling between the control and the communication. We provide stability conditions for the overall closed-loop system and derive uniform bounds on the error signals between the real system, the reference model, and an ideal model, which has perfect communication and no uncertainties. It is shown that these bounds can be arbitrarily improved, subject only to the hardware limitations.

Distributed Adaptive Tracking Control for Unknown Nonlinear Networked Systems

In this paper, we investigate the cooperative tracking problem for a class of nonlinear uncertain networked systems subject to an active leader, whose state can merely be partially measured and input channel is disturbed as well. By virtue of neural network (NN) technique, the dynamics of followers are properly modeled on certain basis functions and their input channels are assumed to be disturbed as well. In this work, an observer-based adaptive control is proposed for the nonlinear networked systems which may have non-identical dynamics. It is shown via Lyapunov theory that the overall system is cooperatively uniformly ultimately bounded (UUB) by appropriately choosing the parameters under some graph condition. In the end, several numerical simulations are elaborated for validation of the proposed adaptive controller.

Robust H∞ Control for Uncertain Discrete Networked Control Systems

This study is concerned with the robust H control for a class of uncertain discrete Networked Control Systems (NCSs). The NCSs with bounded network-induced delay and data packet dropout are modeled as closed-loop systems with time-varying input delay. By using new Lyapunov-Krasovskii function and combining Jessen inequality and reciprocal convex technique, a sufficient condition which asymptotically robust stabilizes closed-loop systems and satisfies H performance index is derived. This study needs fewer Linear Matrix Inequality (LMI), compared with the existing literature. Therefore, the result obtains lower conservativeness. Finally, the robust H controller is obtained with an improved cone complementarity linearization (ICCL).Simulation results show the effectiveness of the proposed method.

Robust [formula omitted] control for uncertain networked systems with communication constraints

This paper considers robust H∞ control for networked control systems (NCSs) with communication constraints, network-induced delay and uncertainties in both system dynamic and access rates. Medium access constraints of both sensor–controller and controller–actuator channels are considered, that is, not all the sensors and actuators are granted access to the network simultaneously to transfer measurements, the access status of sensors or actuators are governed by some stochastic variables. Then new NCSs model is proposed by using these stochastic variables. The purpose of this paper is to design the robust H∞ controller to stabilize the NCSs with communication constraints and random network-induced delay. By using the Lyapunov functional method and the linear matrix inequality technology, sufficient conditions for the robust mean square stable (RMSS) of the NCSs with an H∞ norm bound γ are obtained. A simulation example is given to demonstrate the effectiveness and application of the proposed method.

Intermittent Fault Detection for Uncertain Networked Systems

This paper investigates intermittent fault detection problem for a class of networked systems with multiple state delays and unknown input. Polytopic-type parameter uncertainty in the state-space model matrices is considered. A novel measurement model is employed to account for both the random measurement delays and the stochastic data missing (package dropout) phenomenon, which are typically resulted from the limited capacity of the communication networks. We aim to design an uncertainty-dependent fault detection filter such that, for all unknown input, all possible parameter uncertainties, and all incomplete measurements, the error between residual and weighted fault is made as small as possible. By converting the addressed robust fault detection problem into an alternative robustH∞filtering problem of a certain Markovian jumping system (MJS), a sufficient condition for the existence of the desired robust fault detection filter is derived. A residual evaluation within an incremental form is brought forward to make the whole method suitable for intermittent fault detection. A numerical example is utilized to demonstrate the effectiveness of the proposed approach.

Backstepping-based synchronisation of uncertain networked Lagrangian systems

In this article, we study the synchronisation problem of uncertain networked Lagrangian systems on directed communication topologies. For the nominal model without uncertainties, we propose a backstepping-based synchronisation design for heterogenous Lagrangian systems on directed graphs with a spanning tree. We relax earlier constraints on the feedback gain for the distributed synchronisation control law, which encompasses the existing double integrator consensus problem as a special case. We then extend the proposed design to the case without relative velocity measurement. For the uncertain Lagrangian model, we develop a distributed adaptive redesign so that asymptotic synchronisation convergence is achieved in the presence of linearly parameterised model uncertainties. Simulation results show the effectiveness of the proposed method.

An LMI Approach to Guaranteed Cost Control of Networked Control Systems with Nonlinear Perturbation

This paper is concerned with the problem of state-feedback guaranteed cost controller design for uncertain networked systems with both network-induces delay and data dropout taken into consideration. The sufficient condition for the existence of the networked guaranteed quadratic cost controller is obtained in terms of matrix inequalities, and the controller design method is deduced in terms of linear matrix inequalities. Furthermore, the suboptimal networked guaranteed cost controller design method is obtained with cone complementarity linearization algorithm. A numerical example is given to illustrate the proposed method.

Sliding mode control for a class of nonlinear discrete-time networked systems with multiple stochastic communication delays

In this article, a sliding mode control problem is studied for a class of uncertain nonlinear networked systems with multiple communication delays. A sequence of stochastic variables obeying Bernoulli distribution is applied in the system model to describe the randomly occurring communication delays. The discrete-time system considered is also subject to parameter uncertainties and state-dependent stochastic disturbances. A novel discrete switching function is proposed to facilitate the sliding mode controller design. The sufficient conditions are derived by means of the linear matrix inequality (LMI) approach. It is shown that the system dynamics in the specified sliding surface is robustly exponentially stable in the mean square if two LMIs with an equality constraint are feasible. A discrete-time SMC controller is designed that is capable of guaranteeing the discrete-time sliding-mode reaching condition of the specified sliding surface. Finally, a simulation example is given to show the effectiveness of the proposed method.

The Stripping Principle to the System Synthesis for a Kind of Complex Networked Systems

In this paper, based on the philosophical thinking of `On Contradiction', we propose a method to the system synthesis for a kind of uncertain networked systems which are composed of some heteromorphic subsystems. We call it the stripping principle. Based on the principle, we design, for each node, the integral feedback with variable gain so that it can remove or eliminate the interconnected parts, uncertainties and disturbances. Then we translate the problem of networked control into that of decentralized control. So we need only to consider the synthesis for each of the subsystems respectively without concerning the influence of the non-principal factors. Therefore, with little restrictions to the networked system and using simple control structure, we can get satisfactory control results even for systems which are with non-smooth components. The theoretical analysis and simulation results are shown to indicate the effectiveness of the proposed method.

The Improvement of Fastness for a Kind of Uncertain Networked Systems Based on the Stripping Principle and Optimal Control

Abstract In this paper, based on using the stripping principle and optimal control, we consider the improvement of fastness for a kind of uncertain networked systems which are composed of some heteromorphic subsystems. The method can be summarized as follows. Facing the complex networked structure and the unavoidable uncertainties or disturbances, we use the integral feedback with a variable gain for each of the subsystems to remove or eliminate the interconnected parts, uncertainties and disturbances. So we turn the control problem of networked systems into that of decentralized control. And then we use optimal control for the subsystems respectively. Then the fastness of the networked systems can be improved. The theoretical analysis and simulation result are given to indicate the effectiveness of the proposed approach.

Robust control for a class of nonlinear networked systems with stochastic communication delays via sliding mode conception

This paper deals with the robust control problem for a class of uncertain nonlinear networked systems with stochastic communication delays via sliding mode conception (SMC). A sequence of variables obeying Bernoulli distribution are employed to model the randomly occurring communication delays which could be different for different state variables. A discrete switching function that is different from those in the existing literature is first proposed. Then, expressed as the feasibility of a linear matrix inequality (LMI) with an equality constraint, sufficient conditions are derived in order to ensure the globally mean-square asymptotic stability of the system dynamics on the sliding surface. A discretetime SMC controller is then synthesized to guarantee the discrete-time sliding mode reaching condition with the specified sliding surface. Finally, a simulation example is given to show the effectiveness of the proposed method.