Smith Predictor for Control of the Temperature Process with Long Dead Time

Bogdanovs, Nikolajs; Beļinskis, Romualds; Krumins, A.; Pētersons, Ernests; Ipatovs, Aleksandrs

doi:10.5220/0007808501730179

Cited by 3 publications

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“…As the plant model Gn(s) is the fast model actuated by control signal C(s) produces a predicted output or the open-loop prediction of the actual plant gets added to the estimated disturbance as a feedback signal to the controller. This feedback signal is termed as a predicted process variable with disturbances (y p (t))(Bogdanovs et al, 2019). The resultant transfer function of the model can be written as eq.…”

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confidence: 99%

Alleviation of Delay in Tele-Surgical Operations Using Markov Approach-Based Smith Predictor

Kumar

Nigam

2022

International Journal of Business Analytics

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The acceptance of tele-robotics and teleoperations through networked control system (NCS) is increasing day-by-day. NCS involves the feedback control loop system wherein the control components such as actuators and sensors are controlled and allowed to share their feedback over real time network with distributed users spread geographically. The performance and surgical complications majorly depend upon time delay, packet dropout and jitter induced in the system. The delay of data packet to the receiving side not only causes instability but also affect the performance of the system. In this article, author designed and simulate the functionality of a model-based Smith predictive controller. The model and randomized error estimations are employed through Markov approach and Kalman techniques. The simulation results show a delay of 49.926ms from master controller to slave controller and 79.497ms of delay from sensor to controller results to a total delay of 129.423ms. This reduced delay improve the surgical accuracy and eliminate the risk factors to criticality of patients’ health.

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confidence: 99%