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Networked predictive control of systems with random communication delay

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Abstract

This paper proposes a novel networked predictive control strategy and analyses the stability of closed-loop networked predictive control systems with random communication delay. The proposed networked predictive controller consists of a networked control predictor and a conventional predictive controller. The networked control predictor compensates the network communication delay. The conventional predictive controller achieves the required control performance. The stability criteria of a closed-loop networked predictive control system are analytically derived for both the fixed communication delay and random communication delay. The simulated results confirm the analytical results given in the paper.

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... τ f = τ b = 5, exist in the forward and feedback communication channels. The simulation and experimental results are shown in Fig. 4, where simulation 1 and experiment 1 are the cases where there is no time delay in the communication channels, and simulation 2/3 and experiment 2/3 are the results that τ f and τ b exist in the communication channels while using tracking controller (4) and (8), respectively. It can be seen that, when time-delays exist in the control loop, the control performance of controller (8) is better than that of (4), and the results are consistent with that of simulation 1/experiment 1. ...
... The simulation and experimental results are shown in Fig. 4, where simulation 1 and experiment 1 are the cases where there is no time delay in the communication channels, and simulation 2/3 and experiment 2/3 are the results that τ f and τ b exist in the communication channels while using tracking controller (4) and (8), respectively. It can be seen that, when time-delays exist in the control loop, the control performance of controller (8) is better than that of (4), and the results are consistent with that of simulation 1/experiment 1. The tracking errors are bounded within ±4 cm finally. ...
... Based on above results, it can be concluded that the networked predictive tracking controller (8) is capable of compensating consecutive data losses in the feedback channel. Whereas, if a perturbation occurs when the data packets are lost, controller (8) could not eliminate the perturbation immediately until networked controller received the positional information of mobile robot. ...
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This paper investigates remote tracking control problem of a network-based agent with communication delays existing in both forward and feedback communication channels. A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced. Simulations and experiments are provided for several cases, which verify the realizability and effectiveness of the proposed controller.
... Gecikme hakkında birön bilgi oldugu varsayılmaktadır. Benzer durumlarda modelöngörülü kontrol (model predictive control, MPC) da kullanılabilir [8,9] ama bunlar kontrolör ve eyleyici arasında dogrudan baglantı oldugunu varsaydıklarından tam anlamıyla ABKS oldukları söylenemez. Bunun nedeni algılayıcıdan kontrolöre olan baglantıda bir aksaklık olursa,öngörülere temel olacak bilginin ortadan kalkmasıdır. ...
... Eyleyici senkronize moda tekrar girdiginde sistemin referansı yakaladıgı ve eyleyici dügümünün referansa gitmek için senkronize modda kalmasına gerek olmadıgı görülebilir. Sistemimizin benzer araştırmalarda oldugu gibi [9] onceden bilinen bir referans sinyaline sahip olmadıgına dikkat edilmelidir. Basit AKOSun performansı MODOAKOStan daha hızlı bir şekilde bozulur. ...
... It should be noted that many existing works attempted to design a controller that is sufficiently robust to handle network constraints such as network-induced delay and data dropout rather than actively compensate for them. Recently, a new model-based method called networked predictive control has been proposed to actively compensate for network-induced delay and data dropout [20][21][22][23][24][25][26][27][28]. This method has been demonstrated to be very effective by substantial simulations and experiments. ...
... However, how to analyze stability of a networked predictive control system is a challenging topic which has not been completely solved. In existing results, the common Lyapunov function approach [20][21][22][23][24][25][26][27]. or the switched Lyapunov function approach [28] are usually applied to obtain a stability condition for the closed-loop system and these methods can only yield some sufficient stability conditions. ...
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Stability of a networked predictive control system subject to network-induced delay and data dropout is investigated in this study. By modeling the closed-loop system as a switched system with an upper-triangular structure, a necessary and sufficient stability criterion is developed. From the criterion, it also can be seen that separation principle holds for networked predictive control systems. A numerical example is provided to confirm the validity and effectiveness of the obtained results. © 2015 Science China Press and Springer-Verlag Berlin Heidelberg
... To further improve tracking performance, it is possible to apply a predictive control strategy called sequencebased control (among others also known as packet-based control) (Bemporad (1998); Liu et al. (2004); Tang and de Silva (2006); Polushin et al. (2008); Findeisen and Varutti (2009); Liu (2010); Quevedo and Nešić (2011);Fischer et al. (2013b)). The idea of this method is that in addition to the current control input the controller also sends predicted control inputs applicable at future time steps. ...
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In networked control systems, sequence-based controllers are used to compensate for transmission delays and losses in unreliable data networks. For this purpose, the controller sends not only the current control input to the actuator but also a sequence of predicted control inputs. The additional inputs can be used when subsequent transmissions get delayed or lost. In this paper, the sequence-based method is applied to the problem of trajectory tracking over an unreliable network and an optimal sequenced-based tracking controller is derived. The main advantage of the presented approach is that future information on the reference trajectory can optimally be embedded in the predicted control sequences. Furthermore, the controller can be implemented offline. An interesting result is that the optimal controller can still be separated into a feedback part and a feedforward part (as in standard optimal tracking control) despite of both the unreliable network and the sequence-based method. The performance of the derived tracking controller is demonstrated by Monte Carlo simulations with an inverted pendulum.
... Despite the successes reported in these works, making the communication medium an integral part of the actual controller being designed may not be a good design practice since the underlying network and the control system operating on it are two distinct entities and the traffic load and the delay of the communication medium can change during operation of the NCS. On the other hand, model predictive controllers are used in similar scenarios as given by Liu et al. (2004) and Rawlings (2000) but they either do not take the synchronization between the nodes into account or are not set up to be networked control systems due to the fact that they rely on a direct-link between between the sensor and controller and a transmission failure would inhibit future predictions. ...
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... To reduce the network traffic load, a sampled-data NCS scheme has been presented and some necessary and sufficient conditions for global exponential stability of the closed-loop systems via state/output feedback , without/with network delays have been established in [12] . The random network delays in the controller to actuator channel in NCSs have been studied in [13] and the fixed network delay and the random network delays in both forward and feedback channels have been considered in pa- per [14], but the random network delays are not in the form of a Markov process. In [15] and [16], the problems of stochastic stability of networked control systems with random time-delays have been discussed, in which the random ...
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... Srinivasaguta et al [22] proposed a time-stamped model predictive control algorithm for NCS when random delay is less than one sample time. Liu et al [10] proposed using a networked control predictor to take the latest control value from the predictive control sequence available to deal with random communication time delay problem, and then Mu et al [12] presented using a low pass filter to filter the error produced between the delayed plant output measurement and its delayed openloop model output to improve system robustness. Tang and de Silva [23] proposed a NCS control strategy based on generalized predictive control with the buffering of future control sequence to overcome the transmission delay problems at the controller-to-actuator lines and Tang and de Silva [23] presented the conditions under which the stability of the constrained model predictive control for NCS with random delay can be guaranteed. ...
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... To reduce the network traffic load, a sampled-data NCS scheme has been presented and some necessary and sufficient conditions for global exponential stability of the closedloop systems via state/output feedback, without/with network delays have been established in [7]. The random network delays in the controller to actuator channel in NCSs have been studied in [5] and the fixed network delay and the random network delays in both forward and feedback channels have been considered in paper [6], but the random network delays are not in the form of a Markov process. In [8,17], the problems of stochastic stability of networked control systems with random time-delays have been discussed, in which the random time-delays are modeled as a Markov process. ...
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... The Smith predictor method (Smith 1959) is still considered an effective method to deal with delays, which utilized a mathematical model of the plant in the minor feedback loop to compensate for the network delay. But the stability of this method is still very difficult to be analysed The networked predictive control method (NPC) proposed in this paper is based on the idea proposed by Liu et al. (2004). When the digital network channels are employed in a control system, it is possible that the information exchanged between the controller and actuator or between the sensors and controller can be a package of data rather than a single value in each transmission (Liu et al 2006 ...
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A novel networked predictive control methodology is proposed to actively compensate for the network delay and data drop-out, which seriously degrades the performance of the control system, particularly in the case of controlling open-loop unstable systems. The basic idea of this proposed method is that a control prediction generator will be designed to generate future control sequences which are sent to the actuator side. The network delay compensator on the actuator side will choose the appropriate control data from the transmitted prediction sequences according to the network delay. The stability of this proposed method is also discussed. To demonstrate effectiveness of this method, the simulation and practical experiments are carried out .
... Despite the successes reported in these works, making the communication medium an integral part of the actual controller being designed may not be a good design practice since the underlying network and the control system operating on it are two distinct entities and the traffic load and the delay of the communication medium can change during operation of the NCS. On the other hand, model predictive controllers are used in similar scenarios as given by Liu et al. (2004) and Rawlings (2000) but they either do not take the synchronization between the nodes into account or are not set up to be networked control systems due to the fact that they rely on a direct-link between between the sensor and controller and a transmission failure would inhibit future predictions. ...
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... Thus, to overcome the bad network environments, numerous control schemes have been proposed (e.g. see [6][7][8][9]) where networked predictive control (NPC) technique is an important tool [10,11], since it often effectively compensates the network-induced delays and consecutive packet dropouts and therefore has attracted much attentions [12][13][14][15][16]. Liu et al. [17] presented the sufficient conditions for the stability of the closed-loop system with only bounded time-varying delay in feedback channels, then in [18], the sufficient conditions are given to ensure the stability of the closed-loop system with timevarying delays in both feedback and forward channels. The key idea of NPC is as follows: based on received data, the observer and the network delay compensator calculate a series of predicted states and the predicted control signals, and then this series of control signals are packed and transmitted through a communication network to the plant side. ...
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... To reduce the network traffic load, a sampled-data NCS scheme has been presented and some necessary and sufficient conditions for global exponential stability of the closed-loop systems via state/output feedback, without/with network delays have been established in Montestruque & Antsaklis (2003). The random network delays in the controller to actuator channel in NCS have been studied in Liu et al. (2004) and the fixed network delay and the random network delays in both forward and feedback channels have been considered in the paper Liu et al. (2007), but the random network delays are not in the form of a Markov process. Due to the limited transmission capacity of the network and some devices in closed-loop systems, data transmitted in practical NCS should be quantized before they are sent to the next network node. ...
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First, we review some previous work on networked control systems (NCSs) and offer some improvements. Then, we summarize the fundamental issues in NCSs and examine them with different underlying network-scheduling protocols. We present NCS models with network-induced delay and analyze their stability using stability regions and a hybrid systems technique. Following that, we discuss methods to compensate network-induced delay and present experimental results over a physical network. Then, we model NCSs with packet dropout and multiple-packet transmission as asynchronous dynamical systems and analyze their stability. Finally, we present our conclusions
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