Abstract
This paper proposes a sliding mode predictive controller with a new robust global sliding surface for a certain networked control system with random time delay, mismatched parametric uncertainty, and external disturbances. First, the model of the networked control system is established, based on which linear transformation is made to get a new form of the system which does not have time delay term in expression. Then a global sliding surface is proposed followed by the sufficient condition given in the form of linear matrix inequality (LMI) to guarantee system stability and robustness. Subsequently, a sliding mode predictive controller is proposed with modified reaching law as its reference trajectory and the rolling optimization method is combined to provide optimal control input for each step so that chattering can be minimized. Finally, simulations have been made and the results indicate the advantages of the proposed controller in the aspect of convergence speed, chattering suppression, and robustness to uncertainties.
Highlights
Because smart sensors and actuators with individual communication modules and processing units are adopted which allow for local control actions and communication is realized through a digital communication network with a more robust network such as a mesh, ring, or bus topology, networked control systems can overcome many disadvantages of the traditional control systems
[4] presents a novel fuzzy sliding mode controller and the networked-induced delay is handled by Pade approximation; [5] proposes a network time delay compensation method based on time delay prediction, where the predicted time delay is used instead of the actual time delay as the parameters of the network time delay compensation controller; and [6] designed an event-triggered predictor-based controller with sampled measurements where predictor models are chosen depending on the delay uncertainty
Model-based predictive control (MPC) is a popular control methodology that has been successfully implemented in many industrial applications, showing good performance [11,12,13], and it is found recently that the introduction of MPC in Sliding mode control (SMC) can effectively suppress chattering because the idea of multistep prediction and rolling optimization of MPC can optimize the reaching phase and obtain the optimal switching control signal of each step during the sliding phase [14,15,16,17,18]
Summary
Because smart sensors and actuators with individual communication modules and processing units are adopted which allow for local control actions and communication is realized through a digital communication network with a more robust network such as a mesh, ring, or bus topology, networked control systems can overcome many disadvantages of the traditional control systems. Model-based predictive control (MPC) is a popular control methodology that has been successfully implemented in many industrial applications, showing good performance [11,12,13], and it is found recently that the introduction of MPC in SMC can effectively suppress chattering because the idea of multistep prediction and rolling optimization of MPC can optimize the reaching phase and obtain the optimal switching control signal of each step during the sliding phase [14,15,16,17,18]. A sliding mode predictive controller has been proposed for a certain networked control system with random time delay, mismatched parametric uncertainty, and external disturbances. Simulations are made to test the effectiveness of the proposed controller and the results indicate that the proposed controller is advanced in the aspect of chattering suppression and robustness to uncertainties
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