H∞ Estimation for Stochastic Time Delays in Networked Control Systems by Partly Unknown Transition Probabilities of Markovian Chains

Abstract

This paper is concerned with the problem of H 1 estimation for networked control systems. Time delays and packet dropouts are considered simultaneously. The occurrence probability of each time delay is considered. The packet dropouts have the Bernoulli distributions. The system is modeled as Markovian jump linear systems with partly unknown transition probability. State observer is designed to estimate the practical state with H 1 feature. The estimation problem is cast into a set of linear matrix inequalities. An example is provided to illustrate the effectiveness and applicability of the proposed method.

Model predictive control based on time-varying efficiency for hydraulic hub-motor driving vehicle

“…In accordance with equations ( 6) and ( 7), on the basis of the principle of flow continuity, and in consideration of the efficiency of HVP and HHM, the input and output of the hydraulic system are connected after ignoring the flow loss in the pipeline, as shown in equation (16).…”

“…15 The problem of robust stabilization by H N control is theoretically and practically important because H N performance mainly deals with disturbance rejection in dynamic systems. [16][17][18] The m synthesis approach, which is based on structured singular value m, can provide the control system robust stability and performance with regard to structured perturbations. 19 Compared with other methods, MPC is more effective in handling nonlinear dynamic characteristics and avoiding saturation bounds.…”