Performance Of Networked Control Systems Research Articles

Optimal Tracking Performance of Networked Control Systems Under Communication Channel Noise

Optimal Tracking Performance of Networked Control Systems Under Communication Channel Noise

Optimal tracking performance of networked control systems under communication constraints

This paper investigates the optimal tracking performance (OTP) of multiple-input multiple-output discrete-time communication-constrained systems by thinking about Denial of Service (DoS) attacks, codecs and additive Gaussian white noise under energy constraints. The non-cooperative relationship between DoS attacks and intrusion detection systems (IDS) is analyzed using repeated game theory. A penalty mechanism is constructed to force the attackers to adopt a cooperative strategy, thus improving the system performance. Partial factorization and spectrum decomposition are used to provide the OTP for systems. The results demonstrate that the systems’ OTP are linked to intrinsic characteristics like non-minimum phase zeros and unstable poles. Finally, concrete examples are shown that the results are accurate.

Can Decentralized Control Outperform Centralized? The Role of Communication Latency

In this paper, we examine the influence of communication latency on performance of networked control systems. Even though distributed control architectures offer advantages in terms of communication, maintenance costs, and scalability, it is an open question how communication latency that varies with network topology influences closed-loop performance. For networks in which delays increase with the number of links, we establish the existence of a fundamental performance trade-off that arises from control architecture. In particular, we utilize consensus dynamics with single- and double-integrator agents to show that, if delays increase fast enough, a sparse controller with nearest neighbor interactions can outperform the centralized one with all-to-all communication topology.

Optimal switching control design for industrial networked control system with uncertain exogenous dynamics

Industrial networked control system performance can be compromised through introduction of intended attacks by intruders. Several ways have been reported in literature to introduce attacks like denial-of-service, packet dropout, and delays etc. in Industrial networked control system. Attacks may be designed based on the system knowledge gathered through eavesdropping process. This article deals with problem of constrained optimal switching control design with industrial networked control system (iNCS) through avoiding performance deteriorating uncertain exogenous dynamics. To characterize and detect the abnormal behaviour of iNCS a random distribution process is adopted which represent the attack sequence in the process on the plant side. The delays and packet loss are introduced through Bernoulii distribution process to express uncertainty of network and also attack introduced by intruders on either side of tightly coupled component. The iNCS performance is evaluated with uncertain exogenous dynamics i.e. packet loss 0%, 10%, 20%, 30%, delays, and malicious attack. The proposed design guarantees the transient and steady state performance of linear-time-invariant iNCS. The proposed design methodology evaluated under switching of optimal predictive control performance of networked system with simulation of numerical problem.

Tracking and Regulation Performance Limitations of Networked Control Systems Over Erasure Channel With Input Quantization

Limitations in communication networks, such as delays, packet dropouts, and insufficient bandwidth, create great challenges in the output tracking control and regulation performance of networked control systems. In this article, we propose some novel performance indexes for achieving the optimal tracking and regulation performance. By considering the influences of noise, packet dropouts, and logarithmic quantization on the channel input, the performance limitations of the networked systems are investigated by applying a two-degree-of-freedom (TDOF) control technique. The results obtained prove that the tracking and regulation performance is dependent not only on the position of the plant’s nonminimum phase zeros and unstable poles, but also on the directions. Furthermore, it is demonstrated that noise and quantization error have a negative influence on the control performance, and the design of the TDOF controller can eliminate the effect of packet dropouts on control performance. To validate the innovation results, several simulations are conducted.

A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks

This paper studies the stability problem and H∞ performance of networked control system (NCS) in the presence of mixed attacks by developing an improved event-triggered mechanism (ETM). Firstly, both aperiodic denial of service (DoS) attacks and random deception attacks are encountered for investigating system dynamic behavior. Then, a resilient optimized dynamic event-triggered mechanism (RODETM) is proposed for reducing the unnecessary costs of system operation and mitigating the impact caused by attacks. On this basis, the standard NCS is reformulated into a switched system under the mixed attacks. Further, using the piecewise Lyapunov-Krasovskii functional method, average dwell time scheme and the linear matrix inequality (LMI) method, some sufficient conditions with control design implementation are obtained, which can ensure the exponential stability with the expected prescribed H∞ performance index of the studied system. Finally, the effectiveness of the proposed approach is demonstrated by using a numerical simulation with comparative analysis.

The Effect of Time Delay on the Average Data Rate and Performance in Networked Control Systems

This paper studies the performance of a feedback control loop closed via an error-free digital communication channel with transmission delay. The system comprises a discrete-time noisy linear time-invariant (LTI) plant whose single measurement output is mapped into its single control input by a causal, but otherwise arbitrary, coding and control scheme. We consider a single-input multiple-output (SIMO) channel between the encoder-controller and the decoder-controller which is lossless and imposes random time delay. We derive a lower bound on the minimum average feedback data rate that guarantees achieving a certain level of average quadratic performance over all possible realizations of the random delay. For the special case of a constant channel delay, we obtain an upper bound by proposing linear source-coding schemes that attain desired performance levels with rates that are at most 1.254 bits per sample greater than the lower bound. We supplement our results with a numerical experiment demonstrating that the obtained bounds and operational rates are increasing functions of the constant delay.

Dynamic output feedback control for networked systems with limited communication based on deadband event-triggered mechanism

In this paper, a deadband event-triggered mechanism is used to reduce the transmission data of the network channel to improve the performance of networked control systems (NCSs) with limited communication. In view of the unmeasurable state signal in the actual network system, the dynamic output feedback control problem for the NCSs is studied. When network-induced delays, time-varying sampling intervals and signal transmission deadbands are considered simultaneously, the model of NCSs under the deadband event-triggered mechanism is constructed, and a sufficient condition for the stability of NCSs is given. Furthermore, the design method of the dynamic output feedback controller of NCSs under deadband event-triggered mechanism is proposed. Two simulation examples are used to show that the proposed approach can obtain the dynamic output feedback controller for NCSs with the deadband event-triggered mechanism, and also illustrate the deadband event-triggered mechanism can reduce the signal transmission in the network channel to obtain better system performance.

Co-Design of Quantization and Event-Driven Control for Networked Control Systems

This paper considers the co-design technique of quantization and event-driven control for reducing the negative influences of network on the system performance of networked control systems (NCSs). Event-driven strategy aims at reducing the frequency of transmission, while signal quantization reduces the amounts of data for each transmission. By combining these two techniques, this paper establishes the quantized event-driven control approaches for both the fixed and relative event threshold cases. The system stability and the existence of the minimum interevent interval (MIEI) are analyzed. Finally, the validity of the proposed approaches is illustrated by the numerical simulations.

Design of Networked Secure and Real-Time Control Based on Blockchain Techniques

The security of data propagation is a critical challengefor the widespread use of networked control systems (NCSs), while the conventional strategies based on estimation techniques cannot solve this issue well. Furthermore, the contradiction between the security and the real-time nature of the control method has not been settled yet. The aim of this article is to propose a novel real-time control method empowered by blockchain technologies to resolve the security problems of NCSs under potential cyberattacks. To facilitate the analysis of blockchain-assisted NCSs, a cyber-authentic-physical system (CAPS) framework is proposed. One of the significant features of the CAPS is that the defense of NCSs against attacks is built by introducing a blockchain protocol. Theoretical analysis reveals the relationship among the scale of the peer-to-peer network, the security of the CAPS, and the latency of NCSs, as well as clarifies the impact of the introduction of the blockchain mechanism on the performance of NCSs. With the networked secure control mechanism designed in this article, the security and stability of NCSs can be achieved simultaneously, and their sufficient conditions are also given. Finally, simulations and practical experiments are presented to show the efficacy of the suggested secure control strategy.

Performance analysis method for NCSs with coding and quantization constraints

This paper studied the performance of networked control systems (NCSs) with coding and quantization constraints. In the forward channel of NCSs, the effects of noise and coding–decoding under a two-degree of freedom controller (2DOF) are considered, while in the feedback channel, the effects of quantization and bandwidth are taken into account. The performance expression is achieved by the spectral factorization. From the results, it can be concluded that the performance is determined by the given plant construction (non minimum phase (NMP) zeros, unstable poles), characteristics of the channel parameters. At the same time, the additive white Gaussian noise (AWGN), coding–decoding, quantization, bandwidth and other factors in the communication path also affect the performance of the network communication path. Finally, the effectiveness and merits of the proposed control scheme are verified by simulations.

Optimal Tracking Performance of NCSs with Time-delay and Encoding-decoding Constraints

In this paper, the tracking performance of networked control systems (NCSs) under energy constraints with time-delay and encoding-decoding is studied. Through spectral factorization and partial decomposition techniques, we can obtain the explicit representation of the optimal performance. It is shown that the optimal performance is affected by non minimum phase (NMP) zeros, unstable poles and other multiple communication constraints such as time-delay, encoding-decoding and additive white Gaussian noise (AWGN). At the same time, the obtained result shows that a two-parameter compensator is superior to a one-parameter compensator. In addition, it is found that time-delay, encoding-decoding and AWGN affected the tracking capability of NCSs. Finally, an example is given for verifying the correctness of the conclusions.

A variable sampling period scheduling method for networked control system under resource constraints

ABSTRACTIn order to improve the performance of networked control system, a variable sampling period scheduling method for networked control system under resource constraints is presented based on network operation state. First, the scheduler obtains the current and past network utilisation, and packet transmission delay online. Based on the acquired network state, the improved particle swarm optimisation algorithm is used to optimise Gaussian process regression model to predict the network utilisation and packet transmission delay in the next sampling period. According to the error and error change rate of system control loop, the weight of the control loop is calculated based on fuzzy rules. Then, in accordance with the needs of network performance and control performance, the network bandwidth is allocated based on the predictive value of network utilisation and packet transmission delay. Finally, the new sampling period of each control loop is calculated. The simulation experiments are performed out based on True time toolbox. The simulation results show that the proposed variable sampling period scheduling methodcan improve output control performance of the system, reduce the packet transmission delay and integral absolute error value of the control loops, and improve network utilisation. The overall control performance of the system is improved. The variable sampling period scheduling method in this paper is effective.

Improving the performance of networked control systems with time delay and data dropouts based on fuzzy model predictive control

This paper proposes a fuzzy model predictive control (FMPC) combined with the modified Smith predictor for networked control systems (NCSs). The network delays and data dropouts are problems, which greatly reduce the controller performance. For the proposed controller, the model of the controlled system is identified on-line using the Takagi – Sugeno (T-S) fuzzy models based on the Lyapunov function. There are two internal loops in the proposed structure. The first is the loop around the FMPC, which predicts the future outputs. The other is the loop around the plant to give the error between the system model and the actual plant. The proposed controller is designed for controlling a DC servo system through a wireless network to improve the system response. The practical results based on MATLAB/SIMULINK are established. The practical results are indicated that the proposed controller is able to respond the networked time delay and data dropouts compared to other controllers.

TFS: Towards Fuzzy Rule-Based Feedback Scheduling in Networked Control Systems

With the pervasive applications of networked control systems (NCSs), it is increasingly important to design the network scheduling algorithm to ensure good overall system performance. Traditional static scheduling algorithms may work, but they require a-priori knowledge of the workload for processors and the network. As a result, using static scheduling may degrade the quality of control (QoC) of the control systems in the NCSs with limited bandwidth and dynamic workload. To achieve the desired overall performance of NCSs even when the available network resource for the control applications is scarce and unpredictable, we propose a dynamic time division multiple access (TDMA)-based fuzzy-controlled scheduling (TFS) scheme in this paper. Our approach uses the QoC of the control loops as continuous feedback for dynamic resource allocation. As a novel approach for network scheduling and control application co-design, the proposed scheme uses a condition-based cyclic state-switching framework to balance the network resource allocation among all the control loops. The scheme uses a fuzzy controller to provide the QoC guarantees by maintaining the overall system performance at a desired level. We investigate a simplified servo target tracking system as our case study to show the effectiveness of the proposed TFS scheme for achieving a desired level of the system performance. The simulation results confirm the advantages of TFS in comparison with the typical static and feedback scheduling algorithms.

Performance limitations of networked control systems with quantization and packet dropouts

This paper investigates the problem of optimal tracking performance of networked control systems (NCSs) with quantization and packet-dropouts. The system under consideration is linear time-invariant (LTI), multi-input multi-output (MIMO), where an H2 norm of error signal between the reference input and the system output is used as the tracking performance index. The impacts of packet-dropouts in the communication channel and the quantized input and output are studied. The goal is to obtain the minimal error in tracking a random signal, by searching through all possible stabilizing two-parameter controllers. It is shown that, the minimum value of tracking error is closely related to the reference input signal direction, the non-minimum phase zeros and unstable poles of the given plant, including the locations and directions. We also demonstrated the quantization error and the packet-dropouts may degrade the tracking performance. A typical example is given to evaluate the theoretical results.

Scheduling method for networked control system with resource constraints based on fuzzy feedback priority and variable sampling period

A scheduling method based on fuzzy feedback priority and variable sampling period for a networked control system with resource constraints is proposed in this paper. Firstly, each control loop weight is adjusted dynamically according to a control loop data transmission error through a quadratic square root mapping function. A different weight is given for each loop. A fuzzy feedback priority scheduling strategy is designed combined with dynamic weight, system output and system output error rate. The priority of each control loop is adjusted dynamically. Then, considering the current network status, the new network utilization is predicted through proportional control. A least-squares support vector machine (LSSVM) algorithm is used for controlled loop packet transmission time prediction. A variable sampling period for each control loop is determined by using a controlled loop dynamic weight, network utilization and data transmission time. Finally, a fuzzy feedback priority scheduler and variable sampling period scheduler are combined. The merits of the two schedulers are utilized to achieve the optimization goal. A simulation experiment is carried out using the True Time toolbox. Simulation results show that the scheduling method can make the network utilization rate converge to the desired value under resource constraints, improve the output response performance of the control loop, reduce the integral absolute error value of the control loop and decrease the data transmission time of the control loop. The networked control system performance is improved and the scheduling method of this paper is effective.

The minimal signal-to-noise ratio required for stability of control systems over a noisy channel in the presence of packet dropouts

The achievable performance of networked control systems (NCSs) are often constrained to the communication channel characteristics. This paper investigates the minimal signal-to-noise ratio (SNR) for stabilization of the single-input single-output (SISO), linear time-invariant systems whose output feedback is subjected to the additive white Gaussian noise (AWGN), and the effect of the packet dropouts which is modeled as a binary stochastic process. The authors considered both cases, with and without the input stochastic disturbance. With the parameterization of all stabilizing controllers, the results showed that signal-to-noise ratio performance is strongly dependent on the plant’s nonminimum phase zeros and unstable poles locations. It was also proven that the packet dropouts and the input stochastic disturbance might degenerate the signal-to-noise ratio performance. Lastly, simulations are provided in order to verify the obtained theoretical analysis results.

Optimal modified tracking performance for networked control systems with QoS constraint

This paper investigates the optimal modified tracking performance of networked control systems with a constraint on quality of service (QoS). The QoS is characterized by two parameters of the system, viz. data dropout and the additive white Gaussian noise. The proposed modified tracking performance index prevents the probability of invalid data arising from the variations in the tracking error in the absence of an integrator in the plant. The derived optimal filter eliminates the influence of channel noise in the feedback channel. The optimal modified tracking performance expression is obtained by using the co-prime factorization. Results indicate that the optimal modified tracking performance is influenced by the non-minimum phase zeros, modification factor, packet dropout probability, and the characteristics of the reference signals. The obtained results will give some guidance for the design of networked control systems. The efficiency of the model is verified using some typical examples.

Optimal tracking performance of networked control systems with communication delays under channel input power constraint

The optimal tracking performance of networked control systems with communication delay and white Gaussian noise under the consideration of the channel input power constraint is studied in this paper. The tracking performance is measured by the energy of the system’s error signal and channel input power. The tracking performance is minimized by considering the channel input power constraint searching through all stabilizing two-parameter controllers. The optimal tracking performance of networked control systems under the communication delays, packet dropout and white Gaussian noise of the communication channel has been studied. The explicit expressions of the optimal tracking performance are obtained by applying the spectral factorization and inner–outer factorization techniques. It is shown that the optimal tracking performance depends on the non-minimum phase zeros, unstable poles of the given plant, communication delay, packet dropouts probability and white Gaussian noise. It is also shown that if the constraint of the communication channel does not exist, the optimal tracking performance reduces to the existing tracking performance of the control system without communication. The result shows how the communication delay, packet dropout probability and white Gaussian noise may fundamentally constrain a networked system’s tracking capability. Finally, some typical examples are given to illustrate the theoretical results.