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Abstract:   (959 Views)
In this paper, the event-triggered strategy in the case of finite-horizon model predictive control (MPC) is studied and its advantages over the input to state stability (ISS) Lyapunov based triggering rule is discussed. In the MPC triggering rule, all the state trajectories in the receding horizon are considered to obtain the triggering rule. Clearly, the finite horizon MPC is sub-optimal with respect to the infinite-horizon case. This sub-optimality is considered as a coefficient to implement the MPC triggering rule and to increase the inter-execution time. However, to design a proper processing board to control this coefficient suitably, it is necessary to specify lower and upper bounds for it. The contribution of this paper is to determine an effective upper bound for this coefficient. By incorporating the sub-optimal lower bound instead of being 1, the conservatism decreases. This coefficient can be used as a tunable parameter in integrated or network control systems to compromise between the performance and inter-execution time. Simulation results depict the applicability of the proposed method and validate the theoretical results.
Type of Article: Research paper | Subject: Special
Received: 2016/09/6 | Accepted: 2018/11/5

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