Abstract
The concept of remotely controlling a system through communication network gave birth to Networked Control Systems (NCSs). The NCSs are traditional feedback control loops closed through a real-time communication network. It is evident that the performance of closed-loop system deteriorates due to network delay and information loss in communication channel due to bandwidth limitation or congestion. Hence, it is mandatory to improvise the existing control strategies for NCS. In this chapter, we propose an approach for designing discrete-time sliding mode controller for NCS having random fractional delay and multiple packet loss simultaneously. The fractional delay that occurs within sampling period is modelled using Poisson’s distribution function and is approximated using Thiran’s delay approximation technique. The multiple packet loss that occurs in communication channel between sensor and controller is treated with uniform probability distribution function and compensated at controller end. Based on the proposed approach, a sliding surface is designed and is used to derive discrete-time sliding mode control law that computes the control actions in the presence of random network delay and multiple packet loss. Further, a second-order disturbance estimator is incorporated at the plant side to estimate the disturbance that occurs in the plant. The disturbance estimator guarantees the width of quasi-sliding mode band (QSMB) of order \(O(h^{3})\) with decreasing reaching steps. Hence, the robustness properties of closed-loop NCS are improved. The stability of the closed-loop NCS is also derived using Lyapunov approach that assures the finite-time state convergence in the presence of network non-idealities. The efficacy of the proposed algorithm is examined through simulation results.
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Shah, D.H., Mehta, A. (2018). Discrete-Time Sliding Mode Control with Disturbance Estimator for NCS Having Random Fractional Delay and Multiple Packet Loss. In: Discrete-Time Sliding Mode Control for Networked Control System. Studies in Systems, Decision and Control, vol 132. Springer, Singapore. https://doi.org/10.1007/978-981-10-7536-0_7
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DOI: https://doi.org/10.1007/978-981-10-7536-0_7
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