Network Delay Compensator Research Articles

Incremental networked predictive control of multi‐agent systems with plant‐model mismatch and random communication constraints

In this paper, we discuss the cooperative output tracking problem for networked multi-agent systems (NMASs) with plant-model mismatch as well as random communication constraints in the forward and feedback channels of each agent. In order to compensate actively for random communication constraints, that is, network-induced delays and packet dropouts, an incremental networked predictive control scheme based on a state observer is proposed, which consists of a data buffer, an incremental networked predictor, and a network delay compensator. For both the plant-model mismatch case and the plant-model match case, the stability conditions of resulting closed-loop NMASs are derived, respectively. Using the proposed method, the simulation results for three DC motor systems are presented to indicate that desired tracking performance can be achieved.

Resilient Wide-Area Damping Control for Inter-Area Oscillations to Tolerate Deception Attacks

Deception attacks that threaten communication networks will result in serious consequences ranging from the deterioration of damping performances to instability of power systems. To address this problem, this paper proposes a resilient wide-area damping control (RWADC) for inter-area oscillation based on a secure networked predictive control (SNPC), which is combined with information technology security system (ITSS) and the resilient control scheme based on networked predictive control (NPC). The ITSS including data encryption, data decryption and deception attack detection, is designed to guarantee data confidentiality, integrity, and authenticity. This security system is based on Data Encryption Standard (DES) and Message Digest Algorithm (MD5). The NPC part is used to provide optimal control sequences and compensate the impact of communication constraints and deception attacks, which includes modified generalized predictive control (MGPC), network delay compensator (NDC), and model identifier. Case studies are undertaken on the 16-machine 68-bus AC/DC hybrid power system. Simulation results show that the proposed RWADC can suppress inter-area oscillations, provide better damping performances than those of the conventional and robust WADC over different operating conditions and compensate adverse effects caused by deception attacks actively.

Fuzzy-Observer-Based Predictive Stabilization of DC Microgrids With Power Buffers Through an Imperfect 5G Network

This article investigates the fuzzy model predictive control synthesis of a power buffer for dynamic stabilization of a dc microgrid (MG), which is controlled through a low-latency communication network, such as the one envisioned in fifth-generation (5G). The proposed approach employs a Takagi–Sugeno fuzzy model, a fuzzy observer, and a model predictive scheme to alleviate the effects of the 5G-network-induced delays and data loss of the sensor-to-controller and controller-to-actuator links on the dc MG plant response. By employing the so-called time-stamp technique and network delay compensator (NDC), the delays are computed, and the data loss effects are compensated, thus improving the effectiveness and robustness of the proposed controller. In addition, a time-delay-independent observer is proposed to estimate the states of the constant power loads (CPLs) and the power buffer, based on the measured information. Due to the usage of two NDCs, the presented approach is robust against the network delays and results in a small computational burden. To show the merits of the proposed approach, it is applied to a dc MG that feeds two CPLs. Results show the simplicity of designing the observer-based controller and better robustness against the network delays, compared with the state-of-the-art methods. Additionally, software-in-the-loop simulations are presented to prove the practical applicability of the proposed controller.

Networked Fuzzy Predictive Control of Power Buffers for Dynamic Stabilization of DC Microgrids

This letter investigates the fuzzy model predictive control synthesis of networked controlled power buffer for dynamic stabilization of a dc microgrid (MG). The proposed is based on Takagi–Sugeno fuzzy model and model predictive scheme to mitigate the network-induced delays from the sensor-to-controller and controller-to-actuator links. By employing the so-called time-stamp technique and network delay compensator (NDC), the delays are computed and compensated, which improves the effectiveness and robustness of the proposed controller. Due to the usage of two NDCs, the presented approach is robust against the network delays and results in small computational burden. Therefore, it can widely be employed on large distributed power systems. To show the merits of the proposed approach, it is applied to a dc MG that feeds one constant power load. Results show the simplicity of designing the controller and better robustness against the network's delays compared to the state-of-the-art methods. Additionally, hardware-in-the-loop simulations are presented to prove the practical applicability of the proposed controller.

Wide-Area Damping Controller for Power System Interarea Oscillations: A Networked Predictive Control Approach

Wide-area damping controller (WADC) requires communication networks to transmit remote signals. The usage of communication networks will introduce time delays into the control loop of the WADC. Ignoring this time delay would deteriorate the damping performance provided by the WADC or even cause the whole system instability. This paper employs networked predictive control (NPC) to design a WADC for the generator exciter to enhance the damping of interarea oscillations in a large-scale power system. The NPC incorporates with a generalized predictive control (GPC) to generate optimal control predictions, and a network delay compensator to detect and compensate both constant and random delays. Moreover, model identification is used to obtain an equivalent reduced-order model of the large-scale power system and deal with the model uncertainties and variation of operating conditions. Case studies are based on the New England 10-machine 39-bus system. Effectiveness of the proposed WADC is verified by simulation studies and compared with a conventional WADC and a GPC-based WADC without delay compensation.

Data-driven predictive control for networked control systems

This paper is concerned with the problem of data-driven predictive control for networked control systems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.

H ∞ predictive control of networked control systems

This article is concerned with the problem of H ∞ predictive control of networked control system with random network delay. A new control scheme termed networked predictive control is proposed. This scheme mainly consists of the control prediction generator and network delay compensator. While designing the predictor, the control input to the actuator may be different due to networked induced time-delay and data dropout, and two cases are considered depending on the way that the observer obtains the plant control input u t . The necessary and sufficient conditions are given for the closed-loop networked predictive control system to be stochastically stable for different u t and random network delays in controller to actuator channel (CAC) and sensor to controller channel (SCC). A simulation study shows the effectiveness of the proposed scheme.

Predictive control of networked systems with random delay and data dropout

This study is concerned with the stochastic stability analysis of networked control systems with random network delay. A new control scheme termed networked predictive control is proposed. This scheme mainly consists of the control prediction generator and network-delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network-delay compensator removes the effects of the network transmission delay and data dropout. The stochastic stability criteria of the closed-loop networked predictive control systems are derived. A numerical example and a practical experiment are given to show the potential of the proposed techniques.

Networked predictive control of systems with random delay in signal transmission channels

This article considers the design and stability of networked control systems with random delay in signal transmission channels. To deal with the random delay, a networked predictive control strategy is proposed for discrete networked systems. The key parts of the control strategy are the control prediction generator that provides a set of future control predictions and the network delay compensator that compensates for the network transmission delay. The analytical stability criteria of the closed-loop networked predictive control systems are derived for both fixed and random network delays. The proposed networked predictive control method is illustrated using simulations and practical Intranet-/Internet-based control experiments.

NETWORKED PREDICTIVE CONTROL OF SYSTEMS WITH RANDOM NETWORK TRANSMISSION DELAY – A POLYNOMIAL APPROACH

The paper considers the design of networked control systems with random network transmission delay and addresses their closed-loop stability. A novel control strategy is proposed to deal with the random network delay, which is termed as networked predictive control. The key parts of the networked predictive control are the control prediction generator that provides a set of future control predictions and the network delay compensator that removes the network transmission delay. The analytical stability criteria of the closed-loop networked predictive control systems are derived for both fixed and random networked transmission delays.