Networked control system – an overview

Networked Control System (NCS) is fetching researchers’ interest from many decades. It’s been used in industry which range from manufacturing, automobile, aviation, aerospace to military. This paper gives the general architecture of NCS and its fundamental routes. It also touches to its advantages and disadvantages and some of the popular controller which include PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control)

Stochastic model predictive control for constrained networked control systems with random time delay

In this paper the continuous time stochastic constrained optimal control problem is formulated for the class of networked control systems assuming that time delays follow a discrete-time, finite Markov chain . Polytopic overapproximations of the system's trajectories are employed to produce a polyhedral inner approximation of the non-convex constraint set resulting from imposing the constraints in continuous time. The problem is cast in a Markov jump linear systems (MJLS) framework and a stochastic MPC controller is calculated explicitly, oine, coupling dynamic programming with parametric piecewise quadratic (PWQ) optimization. The calculated control law leads to stochastic stability of the closed loop system, in the mean square sense and respects the state and input constraints in continuous time

Finite-Time Boundedness and Stabilization of Networked Control Systems with Time Delay

The finite-time control problem of a class of networked control systems (NCSs) with time delay is investigated. The main results provided in the paper are sufficient conditions for finite-time stability via state feedback. An augmentation approach is proposed to model NCSs with time delay as linear systems. Based on finite time stability theory, the sufficient conditions for finite-time boundedness and stabilization of the underlying systems are derived via linear matrix inequalities (LMIs) formulation. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed results

New results on stabilization of networked control systems with packet disordering

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Fuzzy PD Control of Networked Control Systems Based on CMAC Neural Network

The network and plant can be regarded as a controlled time-varying system because of the random induced delay in the networked control systems. The cerebellar model articulation controller (CMAC) neural network and a PD controller are combined to achieve the forward feedback control. The PD controller parameters are adjusted adaptively by fuzzy reasoning mechanism, which can optimize the control effect by reducing the uncertainty caused by the network-induced delay. Finally, the simulations show that the control method proposed can improve the performance effectively

Networked control system for electrohydraulic flow control positioner using Neural Controller and Collaborative Network

Electrohydraulic flow control valve is an essential element of an automated process industry where fluid control is applicable. The use of conventional controllers overan IP-communication network for controlling electrohydraulic flow control positioner to regulate mainline pressure and flow rate in pipeline transportation of petroleum products between two stations where downstream pressure of the pumping station fluctuates significantlyposes a problem of instability on the flowrate and the mainline pressure of the pipeline. Additionally, the effect of network induced, time-varying delay between the controller and the electrohydraulic flow control valves induces a problem of poor quality of control and inefficient system performance of the control loop. In this paper, we presented an application of neural network in processflow control using an electrohydraulic valve positionerand proposed a concept of collaborative network for networked control systems over IP-based networks.peer-reviewe