By Huiping Li, Yang Shi
This ebook deals a complete, easy-to-understand evaluate of receding-horizon keep watch over for nonlinear networks. It provides novel basic options that may at the same time deal with basic nonlinear dynamics, procedure constraints, and disturbances coming up in networked and large-scale platforms and that are extensively utilized. those receding-horizon-control-based techniques can in achieving sub-optimal regulate functionality whereas making sure closed-loop balance: a characteristic beautiful to engineers.
The authors handle the issues of networked and dispensed keep watch over step by step, steadily expanding the extent of problem offered. The ebook first introduces the state-feedback regulate difficulties of nonlinear networked structures after which experiences output suggestions regulate difficulties. For large-scale nonlinear platforms, disturbance is taken into account first, then verbal exchange hold up individually, and finally the simultaneous mixture of delays and disturbances. every one bankruptcy of this easy-to-follow ebook not just proposes and analyzes novel regulate algorithms and/or ideas, but in addition conscientiously develops provably right layout stipulations. It additionally offers concise, illustrative examples to illustrate the implementation approach, making it important either for educational researchers and engineering practitioners.
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Extra resources for Robust Receding Horizon Control for Networked and Distributed Nonlinear Systems
Example text
For the constrained nonlinear systems with two-channel packet dropouts, we recall the following regional ISpS-type Lyapunov function (a type of comparison function) [17, 22]. 3) with ωk ∈ Υ . 3) is needed for establishing the regional ISpS. 3), the trajectory x(k, x, ¯ ω0,k−1 ) is continuous at x¯ = 0 and ω0,k−1 = 0 with respect to the initial state and the disturbances for all k ∈ Z 0. 1 Assumption 1 is a prerequisite for analyzing the solution to the nonlinear system under investigation [7]. 5 in [7].
4), the definition of ISpS is stated as follows. 4) is said to be ISpS in Ω. 4 is a modification from that in [22] originally proposed for time-invariant nonlinear systems. The notation of ISpS is a generalization of the well-known ISS [8, 22]. In fact, ISpS will be reduced to ISS when the constant c = 0. Recently, ISS has been employed to study the stability of constrained nonlinear systems with network-induced delays in [17] and with packet dropouts in [19]. The ISpS property will be exploited for this study.
Unlike the conventional RHC-based on control strategy that requires solving optimization problem at each time instant, the optimization problem is required to be solved only when new information is available. ) Therefore, the optimization problem does not need to be solved for all the time instants, reducing computational load significantly. In addition, a new transmission mechanism over the C-A channel is elegantly designed such that only necessary control packets are transmitted from the controller node to the actuator node (and the control packet is not needed to be transmitted for all the time instants).