Performance Accretion in Delay Compensation of Networked Control System Using Markov Approach-Based Randomness Estimation in Smith Predictor

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Introduction

In today’s perspective the development of science and technology has fetched a wide change in the field of control system. Now-a-days, the control system is not only confined within the structure of the institutional framework, but is performing tasks globally and the network is rooted to do so. This mutual form of control system with network is called networked control system (NCS), elucidated by Yang, (2006), Liu & Wang (2008), and Chow & Gupta, (2009). Wherein, Antsaklis & Baillieul, (2007), and Bemporad et., al., (2010) described that Control is established through the network on the control system components such as reference input, control signals and the output-feedback of the plant is shared through sensors over the network (Kizito et. al., 2020 and Guo et. al., 2010). Networked control systems have been emerged as a major technique for regulating, directing, and commanding modern scientific and industrial systems in a broader form relatively than a conventional control system. Networked control systems have provided a wide variety of effective amenities at the ground level such as working up the complexity of wiring, extending work efficiency, ease of system operation, upgradation and maintenance, low cost and reduced space and improves efficiency and accessibility with reduced power requirements (Zelinka & Amadei, 2019; Antsaklis, 2005, and Gao et. al., 2008). Adapted challenges in designing networked control systems encourage all researchers to work in this area such as delay in receiving control signals and output signals, packet dropout, and inappropriate use of channel bandwidth (Yu & Zhang, 2008). Apart from the encouraging approaches of NCS there are certain limitations which constantly gain the attention of the researchers across the globe, like network-induced delay, signal quantization, narrowing bandwidth, packet dropout, communication security are few issues of prime concern (Ghabi et. al., 2018 and Zhang et. al., 2015).

In the past few years, the researchers are constantly trying to improve the NCS sector through various approaches and algorithms. Network-induced time delays performs a significant role for the deprived performance of networked control systems, one of the main reasons differentiating system instability (Wang et. al., 2007, and Zhang et. al., 2016). The various kinds of delay in a networked control system can be illustrated through Fig. 1, representing state dynamics of control system can be defined by state equation of the system as:

(1) where the state vector , is , input vector, is , square matrix A & B have dimensions as & respectively. is the total delay in the system that can be limited as such that . Similarly, system output can be expressed as integration of state variables and inputs as:(2) where, output vector y is , output matrix C is and D is transmission matrix having dimensions .