On the modeling of networked controlled systems (original) (raw)
Related papers
Modelling and optimal controller design of networked control systems with multiple delays
International Journal of Control, 2003
In this paper we discuss the modelling and control of networked control systems (NCS) where sensors, actuators and controllers are distributed and interconnected by a common communication network. Multiple distributed communication delays as well as multiple inputs and multiple outputs (MIMO) are considered in the modelling algorithm. In addition, the asynchronous sampling mechanisms of distributed sensors are characterized to obtain the actual time delays between sensors and the controller. Due to the characteristics of a network architecture, piecewise constant plant inputs are assumed and discrete-time models of plant and controller dynamics are adopted to analyse the stability and performance of a closed-loop NCS. The analysis result is used to verify the stability and performance of an NCS without considering the impact of multiple time delays in the controller design. In addition, the proposed NCS model is used as a foundation for optimal controller design. The proposed control algorithm utilizes the information of delayed signals and improves the control performance of a control system encountering distributed communication delays. Several simulation studies are provided to verify the control performance of the proposed controller design.
Delay-Dependent Stability Improvement for Networked Control Systems: a Sampled Data Approach
Algerian Journal of Signals and Systems
This paper concerns the stability conditions and controller design for sampled-data networked control systems (NCSs) model subject to network communication delays, the main objective is to guarantee the maximum allowable upper bounds of network-induced time-varying delays that keep the NCSs stable. First, Lyapunov-Krasovskii functional with simple and double-integral terms is constructed considering both upper and lower bounds of network delay. Then, less conservative Linear Matrix Inequalities (LMIs) stability conditions are established using null terms to introduce free weighting matrices based on the Leibniz-Newton formula. Furthermore, Finsler's lemma is used for the relaxation of the obtained LMI's stability conditions using slack decision variables. It is also used to decouple Lyapunov-Krasovskii matrices from the system ones. The application of the proposed approach for different NCSs gives higher upper delay bounds compared with other methods.
Robust stability bounds for networked controlled systems with unknown, bounded and varying delays
IET Control Theory & Applications, 2009
A robust control-oriented modelling approach for networked controlled systems (NCS) with uncertain, varying, bounded transmission delays and asynchronous discrete-time control laws is presented. The resulting model is then used for the derivation of sufficient conditions for the robust stability of NCSs and the computation of the maximum allowable delay (constrained within one sampling period) that the closed-loop system can tolerate given a pre-selected set of stabilising gains for the nominally delayed system. The derived stability conditions can be used for both open-loop stable and unstable systems and are numerically simple to use because they rely on singular-value calculations and the solution of a standard discrete Lyapunov equation. The impact of certain designer choices (such as sampling period, nominal delay and tuning parameters appearing in the stability conditions) on the delay range is also investigated. Simulation studies are used to investigate the efficiency of the derived robust stability bound.
Delays and packet losses are undesirable from a control system perspective as they tend to adversely affect performance. Networked Control Systems (NCSs) are a class of control systems wherein control components exchange information using a shared communication channel. Delays and packet losses in the communication channels are usually random, thereby making the analysis and design of control loops more complex. The usual assumptions in classical control theory, such as delay free sensing and synchronous actuation, assume lesser significance when it comes to NCSs. Hence, this necessitates a reformulation / relook into the existing models used for NCS control loop analysis and design. In this paper, we study and present the reformulations required for NCSs to include random delays and packet losses in the channel. This paper therefore, provides a unified baseline and framework for analyzing a host of problems that can be captured as NCSs subjected to random delays and packet losses.
Analysis and modeling of networked control systems: MIMO case with multiple time delays
Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
This paper discusses the modeling and analysis of Networked Control Systems (NCSs) where sensors, actuators, and controllers are distributed and interconnected by a common communication medium. Therefore, multiple distributed communication delays as well as multiple inputs and multiple outputs are considered in the modeling algorithm. In addition, the asynchronous sampling mechanisms of distributed sensors are characterized to obtain the actual time delays between sensors and the controller. Due to the characteristics of a network architecture, piecewise constant plant i n p u t s a r e assumed and discrete-time models of plant and controller dynamics are adopted to analyze the stability and performance of a closed-loop NCS. The analysis result is used to verify the stability and performance of an NCS if the controller is designed without considering the impact of multiple time delays. Also, the NCS model provided can be used as a foundation for further controller design to compensate for the distributed communication delays.
Improved Stability Analysis of Networked Control Systems under Asynchronous Sampling and Input Delay
2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2010
This article presents a novel approach to assess the stability of linear systems with delayed and sampled-data inputs. It proposes an extension of existing results on the stability of sampled-data systems to the case where a delay is introduced in the control loop. The method is based on a continuoustime modelling of the systems together with the discrete-time Lyapunov theorem, which provides easy tractable sufficient conditions for asymptotic stability. Those conditions cope the problem of stability under asynchronous samplings and time-varying delays. The period and delay-dependent conditions are expressed using computable linear matrix inequalities. Several examples show the efficiency of the stability criteria.
Modeling approaches and robust stability conditions for networked controlled systems with uncertain
IFAC Proceedings Volumes (IFAC-PapersOnline), 2008
In this article two modeling approaches for Networked Controlled Systems (NCS) with different types of uncertainly varying bounded transmission delays and static discretetime control laws are presented. Different models are offered for each case, all linked to the objective of designing robust discrete-time controllers. It is analytically shown how the careful mixing of asynchronous (event-driven) and synchronized (clocked) signals can lead to discrete time uncertain (possibly switched) systems, where results form robust control analysis and synthesis can be applied. After showing the implications of these modelling results for control synthesis purposes, sufficient conditions for the robust stability are given for each approach and a comparison of the conservatism of results is discussed.
Event-based Controller Design for Networked Control Systems with Time-varying Random Delays
Majlesi Journal of Electrical Engineering, 2020
This paper is concerned with a controller design method for Networked Control Systems (NCSs) with time-varying random delays. The proposed controller is an event-based controller and is able to effectively save the network bandwidth and energy resources of the system in comparison with common control schemes while guaranteeing the stability of the system. The proposed controller switches between two main triggering schemes: event-triggered control scheme and self-triggered control scheme. The stability issue in this combinatorial method is also considered. The validity of the proposed algorithm is confirmed via simulation results and the results are well compared with results from exerting event-triggered and self-triggered control individually.
2006
This paper proposes a method for robust state feedback controller design of networked control systems with interval time-varying delay and nonlinearity. The key steps in the method are to construct an improved interval-delay-dependent Lyapunov functional and to introduce an extended Jessen's inequality. Neither free weighting nor model transformation are employed in the derivation of the system stability criteria. It is shown that the maximum allowable bound on the nonlinearity could be computed through solving a constrained convex optimization problem; and the maximum allowable delay bound and the feedback gain of a memoryless controller could be derived by solving a set of linear matrix inequalities (LMIs). Numerical examples are given to demonstrate the effectiveness of the proposed method.
Stabilization of Networked Control Systems With a New Delay Characterization
IEEE Transactions on Automatic Control, 2008
The problem of data packet dropout and transmission delays induced by communication channel in networked control systems (NCSs) is studied in this paper. We model the continuous-time NCSs with data packet dropout and transmission delays as ordinary linear systems with time-varying input delays. By using the Lyapunov-Razumikhin function techniques, delaydependent condition on the stabilization of NCSs is obtained in terms of linear matrix inequalities (LMIs). Stabilizing state feedback controllers can then be constructed by using the feasible solutions of some LMIs. The admissible upper bounds of data packet loss and delays can be computed by using the quasi-convex optimization algorithm. Numerical examples illustrate the effectiveness of the proposed approach.