Random Network Delay Research Articles

An Active Front Steering System Design Considering the CAN Network Delay

The x-by-wire technology promotes the rapid development of intelligent vehicles, but it comes with the network delays, which would deteriorate the control performance. Therefore, this paper proposes an active front steering (AFS) design scheme considering the network delays to ensure the vehicle path-tracking accuracy and stability performance. First, the vehicle system with delays induced by the Controller Area Network (CAN) is analyzed, based on which an augmented model is built to describe the vehicle motion combined with the random network delays. Considering the uncertainty of the delay, the model is reconstructed by the polytope method. Then, a robust H∞ state feedback controller is developed to ensure the system performance when handling the parametric uncertainties. Furthermore, the robust invariant set is introduced to depict the system constraints, which can guarantee the vehicle stability. Through transforming into the linear matrix inequalities, a feasible solution is calculated. Finally, the rapid control prototype (RCP) based on the CarSim/Simulink test platform is used to validate the proposed controller. The results compared with the model predictive control show the effectiveness to ensure the prescribed performance.

Two networked predictive control methods for output tracking of networked systems with plant-model mismatch

This paper addresses the output tracking control problem for networked systems with plant-model mismatch, where two-channel random network delays are considered. According to the different ways of obtaining future control commands, two networked predictive control (NPC) methods are designed. One is the NPC method using one-way time delays, called ONPC, and the other is the NPC method using round-trip time delays, called RNPC. Furthermore, they are compared in terms of the way of compensation for two-channel delays, prediction process, and communication load, respectively. Then, the closed-loop stability conditions of the RNPC system and the ONPC system for the plant-model mismatch and match cases are derived, and their output tracking performance is also theoretically analysed. Finally, the results of the theoretical analysis are verified through numerical simulation that illustrates the effectiveness of the proposed two NPC methods as well as their separate advantages.

An Event-Triggered Networked Predictive Control Method Using an Allowable Time Delay

An event-triggered network predictive control method, which uses allowable time delays, was developed for networked control systems with random network delays, packet disorders, and packet dropouts in the feedback and forward channels. In this method, random communication constraints are uniformly treated as a time delay at each time instant. Subsequently, based on a time-delay state feedback control law, the proposed method is used to actively compensate for the time delay that exceeds the allowable. In addition, the introduction of an event-triggered mechanism reduces communication loads and saves network resources. A necessary and sufficient stability condition for the closed-loop system is provided, which is independent of random time delays and is related to the allowable delay. Finally, the simulation results of the two systems verified the effectiveness of the proposed method.

Comparison of Three Data-Driven Networked Predictive Control Methods for a Class of Nonlinear Systems

Dear Editor, In this letter, in order to deal with random network delays and packet losses in a class of networked nonlinear systems, three data-driven networked predictive control methods are designed. Their closed-loop systems and control increments are derived, respectively. Although the expressions of their control increments are obviously different, they are similar in form and composition, which are helpful to evaluate the effects of control actions. A comparison of the control performance of the three methods is carried out by a simulation example so as to show their advantages and disadvantages.

Event-Triggered Cooperative Predictive Control for Networked Multi-Agent Systems with Random Delays and Packet Dropouts

This paper addresses the cooperative output tracking control problem for a class of leader-following linear heterogeneous networked multi-agent systems subject to random network delays and packet dropouts in the feedback and forward channels of each agent. A state observer is established at the plant side of each agent, and an event-triggering transmission mechanism is introduced to decide which state estimate is transmitted to the corresponding controller so as to save the network resources of the feedback channel. To further compensate for the negative effects of those random communication constraints and the event trigger, a cooperative predictive control scheme with proportional and integral actions is proposed. Then, a necessary and sufficient condition is derived for the stability of the resulting closed-loop system. Finally, simulation results are given to show the effectiveness of the proposed scheme.

Robust stabilization control for multi-station motion system with network communication constraints

In this article, the robust stabilization control techniques and the time delays compensation method are proposed in a networked multi-station cooperative motion system (MSCMS), where random network-induced communication constraints are presented. First, an uncertain multi-nodes model of MSCMS is established. Moreover, the random network communication delays, station nodes position compensation, two types of topologies of the station nodes, and the mutual position disturbance among the multi-station nodes are considered simultaneously. Second, a discrete-time Markov chain is used to model the random network delays for the MSCMS. A time delay compensation method is applied to compensate the tracking errors among the multi-motor nodes. Moreover, the stability conditions and the robust controller design method for MSCMS are presented by constructing a new Lyapunov functional and combining stability theory and inequality techniques. Finally, the effectiveness of the proposed method for the MSCMS is verified by several comparative experimental results.

Asynchronous Deterministic Network Based on the DiffServ Architecture

In this study, we propose a scalable framework that guarantees both latency and jitter bounds in large networks, including the Internet. The framework is composed of two parts: a latency-guaranteeing network and a jitter-guaranteeing end system. For latency bounds, we suggest regulators per class per input–output port pair of the DiffServ-type relay nodes. For jitter bounds, based on the guaranteed latency bounds, we suggest time-stamping and buffers at the network egress edge. The framework does not require network-wide time synchronization, frequency synchronization, flow state maintenance, or flow-level queuing/scheduling. Therefore, the complexity does not increase as the number of flows or network size increases. Moreover, the framework is based on the DiffServ architecture; therefore, it requires minimal modification to the current Internet. We demonstrate that the proposed regulators can achieve latency bounds comparable to the IEEE asynchronous traffic shaping technique. We prove that the jitter is bounded even with realistic limitations such as buffers without cut-through capability. We also prove that in the presence of clock drift, the jitter can still be upper bounded with a suggested compensation algorithm. We demonstrate through experiments on simple programmable microcontrollers that the jitter upper bound can be within a few tens of microseconds, even in a realistic situation with store-and-forward buffers, clock drift, and random network delays.

Active fault-tolerant predictive control of networked systems subject to actuator faults and random communication constraints

ABSTRACT The fault-tolerant control problem is investigated for a linear networked system subject to an additive actuator fault as well as random network delays and packet dropouts in the backward and forward channels. To deal with the adverse effects of the actuator fault as well as those communication constraints, an active compensation scheme combining active fault-tolerant control and predictive control is proposed based on the simultaneous estimation of the system state and actuator fault. The obtained closed-loop system is a randomly switched system with bounded round-trip time delays, and the corresponding closed-loop stability condition is derived by using a switched Lyapunov approach. Simulation results for a networked DC motor system are provided to verify the proposed method.

Event-Triggered Non-Switching Networked Sliding Mode Control for Active Suspension System With Random Actuation Network Delay

An active suspension system enables a road vehicle to run with increased stability, providing better safety and comfort, by maintaining the wheels in contact with the road surface. Therefore, there is currently demand for designing a robust controller that gives a satisfactory performance in the presence of the different road profiles. This investigation focuses on the design of a discrete-time non-switching networked sliding mode control for the active suspension system, using an event-triggered approach and actuation network delay compensation scheme. A novel event-triggered proportional-integral (PI) sliding variable is built with actuation network delay compensation in the presence of system uncertainties. The discrete-time non-switching networked sliding mode control law is designed using a novel sliding variable, and the control actions at the controller side are updated based on the event generation. The event generator block in the feedback channel increases the communication rate and reduces network congestion by restricting the transmission of unnecessary data packets. The random actuation network delay in the forward and feedback channel is modeled using the Poisson distribution and compensated using the Thiran’s approximation technique. The stability of the closed-loop system is derived using the proposed control law that ensures the finite-time convergence of the system state variables within the specified sliding band. Furthermore, the proposed controller is validated on an active suspension system in the presence of network abnormalities and system uncertainties. Numerical results inferred that the proposed control strategy with event-triggered approach and actuation network delay compensation scheme outperforms as considered the Gao’s reaching law, conventional non-switching reaching law, or the control strategy without actuation network delay compensation.

Networked model predictive control using a wavelet neural network

This study proposes using a wavelet neural network (WNN) with a feedforward component and a model predictive controller (MPC) for online nonlinear system identification and control over a communication network. The WNN performs the online identification of the nonlinear system. The MPC uses the model to predict the future outputs of the system over an extended prediction horizon and calculates the optimal future inputs by minimizing a controller cost function. A computationally efficient formulation for the controller is presented to reduce the computational complexity of the MPC for online implementation and Lyapunov theory is used to prove the stability of the MPC. The methodology is applied to the online identification and control of an unmanned autonomous vehicle. Simulation results show that the MPC with an extended prediction horizon can effectively control the system in the presence of fixed or random network delay.

Robust Reset Speed Synchronization Control for an Integrated Motor-Transmission Powertrain System of a Connected Vehicle Under a Replay Attack

This paper deals with the speed synchronization control of a connected vehicle subject to a replay attack. A large number of replay attack signals are injected into controller area network (CAN) through external network, which greatly reduces the real-time control performance of a connected integrated motor-transmission (IMT) system. In order to ensure the performance of an IMT speed tracking system under large random message delays, a robust reset controller combined with a delay-robust speed synchronization controller satisfying energy-to-peak performance is designed in this paper. The uncertain impact caused by a replay attack is described by large random network delays which are modeled by polytopic inclusion. Then, a dynamic output-feedback controller considering the uncertainty caused by attack-delays is proposed for online speed tracking. Moreover, a robust reset controller is designed to obtain comparatively better transient response in the case of large attack-delays. In this control strategy, once the reset condition is triggered, the after-reset value calculated by linear matrix inequalities (LMIs) would replace the dynamic state vector. Finally, the effectiveness of the proposed controller is verified by comparing it with model predictive control (MPC), existing PD control considering delays and energy-to-peak robust control in terms of performance.

Higher order networked sliding mode controller for heat exchanger connected via data communication network

Heat Exchanger (HE) is a widely used device in industrial applications for both cooling and heating processes because it can sustain a wide range of temperature and pressure parameters without affecting the output performance of the system. In this paper, we propose a Higher-Order Sliding Mode (HOSM) controller for HE connected via a data communication network. The higher-order sliding mode controller is well known for chattering attenuation which occurs due to switching control action in a sliding mode control technique. The HOSM controller based on super-twisting algorithm is proposed to compensate for the random communication network delay and process delay in the presence of model uncertainties of HE. The sufficient condition for stability is ensured by the trivial Lyapunov function. The simulation results demonstrate the efficacy of the designed controller for the HE in terms of chattering, delay compensation, and faster convergence. Further, the performance of HE is compared in two ways. In first case, the proposed controller performance is compared for a HE system with network delay and without network delay. In the second case, the performance of the proposed controller is compared with the conventional constant plus proportional rate reaching law based controller.

Trajectory Tracking Control of Autonomous Vehicle With Random Network Delay

Random network delay will introduce uncertainty into trajectory tracking model of the autonomous vehicle, which seriously deteriorates the vehicle's control system stability and trajectory tracking accuracy. In this paper, considering steering angle oscillation caused by random network delay, trajectory tracking system robustness and stability is analyzed and a linear uncertain time-delay system is established. Comprehensively considering control system accuracy, robustness, and computational efficiency in the rolling optimization of Model Predictive Control (MPC), Adaptive Model Predictive Control for Uncertain model (UM-AMPC) algorithm is proposed to predict control variables for the next sampling time and alleviate the target angle discontinuity. This is achieved by operating target angle signal and augmented state variables, which are received by the lower nodes during the period from the current sampling time to network delay upper bound. The hardware-in-the-loop simulation results show that the proposed algorithm can effectively guarantee system stability and tracking accuracy of the autonomous vehicle under random network delay.

Tracking Synchronization Improvement of Networked Manipulators Using Novel Adaptive Nonsingular Terminal Sliding Mode Control

In this article, we focus on the experimental validation of the developed adaptive nonsingular terminal sliding mode (ANTSM) controller for a networked manipulator system. The proposed control approach is designed to deal with a combination of adverse and inexactly known conditions in practice, including parametric uncertainties, frictions, exogenous disturbances, and random time-varying network delays. Another issue addressed in this article is the tradeoff between achieving a smooth convergence and a high tracking accuracy in the physical implementation of the ANTSM controller. Hence, a novel time-varying gain in a form of logistic function is introduced to provide converging smoothness and meanwhile improve the tracking accuracy. Experimental results and empirical analysis are provided to demonstrate the effectiveness and performance improvement of the proposed controller with a time-varying gain.

Predictive cloud control for multiagent systems with stochastic event-triggered schedule

This paper addresses a predictive cloud control problem for a linear multiagent system with random network delays and noises. To reduce communication cost, a stochastic event-triggered schedule is introduced to decide whether current measurements need to be transmitted. An optimal state estimation algorithm is designed to compensate random network delays in the feedback channel. Subsequently, a predictive cloud control scheme is proposed for the multiagent system to achieve both stability and consensus. Simultaneously, random network delays in the forward channel is compensated actively. Sufficient and necessary conditions of stability and consensus for the closed-loop multiagent system are derived. Finally, a numerical example is provided to verify correctness and effectiveness of the proposed methods.

Research of Network Closed-loop Control System Based on the Model Predictive Control

Abstract Uncertainty latency of the remote closed-loop control system in information transmission through Internet, Analysis delays how to influence closed-loop control system. Based on predictive control method of neural network, research the application of closed-loop control system control methods under a random network delay. Simulation results show that: This method is able to reflect and predict the delay characteristics of between network path represented by the measured data, and can be replace actual network to research in application based on Internet closed-loop control system; the methods used is fast and accurate, it can be used for online learning network model and predict the network delay value, provides a new way of remote closed-loop control based on Internet.

H∞Control for LPV Discrete Systems with Random Time-Varying Network Delay

In this paper, we study theH∞control problem for Linear Parameter Varying (LPV) discrete systems with random time-varying network delay. The state matrices of LPV discrete systems are deterministic functions and changed with parameters; the range of parameters is measurable. Considering the characteristics of networks with random time-varying delay, we proposed a new parameter-dependentH∞performance criterion based on the Lyapunov stability theory. The coupling between Lyapunov functions and system matrices could be eliminated by introducing an additional matrix in this criterion, which made it easier for numerical implementation. On this basis, we designed a state feedback controller by virtue of linear matrix inequalities, which transformed the sufficient conditions into existence condition of solution of parametric linear matrix inequalities. The designed controller could keep the closed-loop system asymptotically stable under given time delay and probability and meet predefined performance metric. The validity of the proposed method is verified by numerical simulation.

Power Peak Shaving With Data Transmission Delays for Thermal Management in Smart Buildings

This paper presents a scheme aimed at mitigating the influence of random data transmission delays in networked thermal appliance control systems in smart buildings. The impact of this type of delays is first analyzed, and it is proposed to utilize loose timing synchronization and add blank gaps between the consecutive appliance operations to avoid the possible violation of the given power budget. A cooperative control of thermal appliance operation is developed using a networked model predictive control-based controller to deal with delays. It is also shown that the schedulability of such a control scheme can be assessed online. The performance of the proposed control scheme is assessed by a simulation study based on the thermal dynamics of an eight-room office building. The obtained results show that the proposed solution can achieve an efficient power peaks shaving in the presence of random network delays.

Formal analysis of control and termination of distributed computation in weaker spaces

The control and termination detection of a distributed computation involving large-scale distributed database is difficult in the presence of concurrency, random network delays, and varying reliabi...

Improved bilateral teleoperation with proactive haptic sensing and transmission

This article presents a novel master-slave control configuration that is experimentally demonstrated to improve teleoperation performance under random network delay. This is achieved via the design of a proactive haptic sensing system based on a laser range sensor on the slave side, which in turn allows for the proactive transmission of force control from the master to the slave, thus compensating for Internet-based network delays. The proposed configuration introduces three main contributions to the literature of bilateral control systems: (1) fully decoupled position and force control systems, which allow for the controller gains of each loop to be tuned independently, eliminating the trade-off common to most previous literature; (2) a novel approach that exploits the slow variation nature of the environment parameters, resulting in a lower bandwidth requirement in comparison to previous force control methods; (3) capability to measure the slave environment location and the prediction of the contact force as a result, which provides the human operator with the capability to generate the reaction force proactively on the master side. The conducted experiments demonstrated a significantly improved performance in terms of synchronized forces and positions despite the random network delay between the master and slave systems.