Decentralized dynamic event‐triggered control for networked control systems under unreliable communication network and actuator saturation

To tackle the trajectory tracking problem and achieve high control accuracy in many actual nonlinear systems with unknown dynamics and input saturation, a novel discrete‐time extended state observer‐based model‐free adaptive constrained sliding mode control with modified prescribed performance is investigated via compact‐form dynamic linearization (CFDL) and partial‐form dynamic linearization (PFDL). Firstly, the original non‐affine system is turned into an affine one comprising an unknown nonlinear term and a linearly parametric term affine to the input via both PFDL and CFDL. Then, a discrete‐time extended state observer (DESO) is used to estimate the lumped disturbance containing the unknown nonlinear time‐varying term and the term relevant to the estimation error of pseudo partial derivative (PPD) parameter. Furthermore, a modified prescribed performance function is introduced in the model‐free adaptive sliding mode control scheme to keep the output tracking error in the prescribed bound without causing any asymmetric offset error in the steady‐state. Meanwhile, to suppress the influence of input saturation on the control system, an anti‐windup compensator is used. Finally, rigorous theoretical analyses show the robust convergence of the tracking error via the proposed CFDL and PFDL‐based methods under external disturbances. Simulations verify the superiority of the modified prescribed performance function, DESO, and anti‐windup compensator in the proposed method. Also, the effects of the PFDL‐based method and the CFDL‐based one are compared during the simulation.

“…Then, a DESO is used to estimate 𝜁 t . Define the state vector (33) is rewritten as the following state-space equation:…”

Section: Deso In Cfdl Modelmentioning

confidence: 99%

“…If the input constraint problem is not considered during the siding mode controller design process, the closed-loop system might be unstable for the integral saturation of SMC. For now, input constraint has been contained in many real scenarios [30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Discrete‐time extended state observer‐based model‐free adaptive constrained sliding mode control with modified prescribed performance via CFDL and PFDL

Huang,

Dong,

Zhang

et al. 2023

“…There was research focusing on the application of decentralized controller into the large-scale web-winding system [10]. On the other hand, the decentralized controller is an effective tool in dealing with the system with random disturbances, such as in the network area [11,12]. In decentralized control, the mean field game (MFG) is an alternative route when encountering large-scale agents, which was introduced by Lasry and Lions and Huang et al in 2007 to manage a large number of agents in a non-cooperative game problem [20,21].…”

Section: Literature Reviewmentioning

confidence: 99%

Mobility‐aware optimal trade planning and mean field game‐based decentralized charging control for large‐scale electric vehicles

Zhao

2023

The uncertainty mobility characteristics of electric vehicles (EVs) are a key factor that influence the charging station trade income with the power grid. In this paper, a hierarchical energy management strategy is proposed for charging stations when large‐scale EVs are considered. The traveling and parking mobility characteristics of EVs are first extracted by analyzing historical real‐world traveling data. Then, a day‐ahead power trade planning strategy between the grid and charging station to maximize incomes is developed by solving a mixed‐integer linear programming problem. Furthermore, based on EV mobility characteristics, clusters are generated to classify different parking behaviors, where a mean field game‐based decentralized charging control scheme for individual EVs in each cluster is employed. The target of the proposed optimal charging controller is to guarantee the charging power tracking performance and the power demand of individual EV at the terminal time for subsequent travel. Finally, simulations on MATLAB/Simulink platform are conducted to show the effectiveness of the proposed hierarchical energy management strategy.

“…As a result of this separation, both the slow and fast dynamics can be updated independently when their corresponding triggering conditions are satisfied. Therefore, both the slow and fast dynamics can be updated at different rates, potentially preventing many redundant communications and network bandwidth. Further, event‐triggered control designed for many network‐resource‐constrained systems [31–33] may not be suitable for singularly perturbed systems. The major problem is designing a proper triggering mechanism that can ensure the stability of the SPS because it is influenced by the small perturbed parameter (SPP) and the separation between the two clusters of eigenvalues.…”

Section: Introductionmentioning

confidence: 99%

“…2. Further, event-triggered control designed for many network-resource-constrained systems [31][32][33] may not be suitable for singularly perturbed systems. The major problem is designing a proper triggering mechanism that can ensure the stability of the SPS because it is influenced by the small perturbed parameter (SPP) and the separation between the two clusters of eigenvalues.…”

Section: Introductionmentioning

confidence: 99%

Input‐based event‐triggered control of a discrete‐time singularly perturbed system under a resource constrained environment

Sahu

Bhandari

Fulwani

2023

This paper proposes an input‐based event‐triggered mechanism for a network‐controlled discrete‐time singularly perturbed system, where the latest measurements are transmitted when a predefined condition is satisfied on the input. The significant contribution of the proposed work is the separation of control updates for slow and fast dynamics such that the proposed event‐triggered mechanism updates and broadcasts the current measurements of slow and fast dynamics in their respective time scales and reduces the usage of network resources. Further, the proposed input‐based event‐triggered mechanism avoids redundant updates of the control input and reduces actuation and resource utilization in some instances. Furthermore, the ultimate boundedness of the system states is established. The simulation uses a quarter‐car suspension system to demonstrate the proposed theory.