A non-uniform multi-rate control strategy for a Markov chain-driven Networked Control System

Abstract

ElsevierCuenca Lacruz, ÁM.; Ojha, U.; Salt Llobregat, JJ.; Chow, M. (2015). AbstractIn this work, a non-uniform multi-rate control strategy is applied to a kind of Networked Control System (NCS) where a wireless path tracking control for an Unmanned Ground Vehicle (UGV) is carried out. The main aims of the proposed strategy are to face time-varying network-induced delays and to avoid packet disorder. A Markov chain-driven NCS scenario will be considered, where different network load situations, and consequently, different probability density functions for the network delay are assumed. In order to assure mean-square stability for the considered NCS, a decay-rate based sufficient condition is enunciated in terms of probabilistic Linear Matrix Inequalities (LMIs). Simulation results show better control performance, and more accurate path tracking, for the scheduled (delay-dependent) controller than for the non-scheduled one (i.e. the nominal controller when delays appear). Finally, the control strategy is validated on an experimental test-bed.

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

“…Stochastic Finite-Time ∞ Output Feedback Control. In this subsection, we will deal with the problem of the design of output-feedback controller for system (1). Theorem 10.…”

“…Networked control system (NCS) is a new research field originated from control engineering practice, which is composed of controller, actuator, and sensor. Due to low cost, low power consumption, and practical resource sharing, the dynamic behavior of NCSs has been widely concerned in recent years [1][2][3][4][5]. However, network is not a reliable communication medium.…”

“…The trajectory of state ( ) when E{ ( )} = 0.8, E{ ( )} = 0.8, E{ 1 ( )} = 0.6, E{ 2 ( )} = 0.8.Moreover, the time-varying delays satisfy 1 ≤ ( ) ≤ 4( = 1, 2), the exogenous disturbance ( ) is chosen as ( ) = 1/(0.1 + 2 ), and the nonlinear function ( ( )) is selected as( ( )) = [ tanh(−0.3 1 ( )) tanh(0.5 2 ( ))] . For given = 40, = 1, 1 = 1, and = 1.002, it can be easily checked that E{ ( )1 ( )} ≤ 1 is satisfied under the initial condition (0) = [0.5 −0.2] and̂(0) = [0 0] .By solving the minimization problem involving LMIs conditions (53) and (54) and using LMI toolbox in Matlab, we can obtain the optimal value 2min = 39.5855 and the optimal ∞ performance min = 0.0779. By Theorem 10, the resulting controller gain matrices are expressed as…”

Energy-Efficient Control for an Unmanned Ground Vehicle in a Wireless Sensor Network

“…By means of these indexes, the energy-efficient control proposal may be compared with the conventional time-triggered control strategy. Regarding control performance, similar to [49], these three cost indexes will be used:…”

Optimal tracking performance of control systems with two-channel constraints

“…Owning to the advantages of the NCSs over the traditional real-time control systems in information processing and decision-making, control and optimization of NCSs are rapidly developed and broadly applied [7,9,17,18,19,34]. However, system performance could be deteriorated, even leading to instability of the control plants, due to the limitations of the channel bandwidth [13,30], channel capacity [4,12,30], delays [37,28], quantization [1,28], congestions [11] and packet loss [5,23,27] and fault [36] in the communication channels of NCSs.…”