Linear optimal filter for system subject to random delay and packet dropout

2016 ◽  
Vol 38 (5) ◽  
pp. 880-892 ◽  
Author(s):  
Xiao Liang ◽  
Huanshui Zhang
Keyword(s):  
Optimal Filter ◽  
Packet Dropout ◽  
Random Delay

State Estimation for Kinematic Model Over Lossy Network

2010 ◽  
Author(s):  
Soo Jeon
Keyword(s):  
State Estimation ◽  
Kinematic Model ◽  
Optimal Filter ◽  
Operating Conditions ◽  
Packet Dropout ◽  
Sensory Data ◽  
Mean Error ◽  
Error Covariance ◽  
Packet Arrival ◽  
The Mean

The major benefit of the kinematic Kalman filter (KKF), i.e., the state estimation based on kinematic model is that it is immune to parameter variations and unknown disturbances regardless of the operating conditions. In carrying out complex motion tasks such as the coordinated manipulation among multiple machines, some of the motion variables measured by sensors may only be available through the communication layer, which requires to formulate the optimal state estimator subject to lossy network. In contrast to standard dynamic systems, the kinematic model used in the KKF relies on sensory data not only for the output but also for the process input. This paper studies how the packet dropout occurring from the input sensor as well as the output sensor affects the performance of the KKF. When the output sensory data are delivered through the lossy network, it has been shown that the mean error covariance of the KKF is bounded for any non-zero packet arrival rate. On the other hand, if the input sensory data are subject to lossy network, the Bernoulli dropout model results in an unbounded mean error covariance. More practical strategy is to adopt the previous input estimate in case the current packet is dropped. For each case of packet dropout models, the stochastic characteristics of the mean error covariance are analyzed and compared. Simulation results are presented to illustrate the analytical results and to compare the performance of the time varying (optimal) filter gain with that of the static (sub-optimal) filter gain.

Gain and Order Scheduling of Optimal Fractional Order PID Controllers for Random Delay and Packet Dropout in Networked Control Systems

2011 ◽  
Vol 403-408 ◽  
pp. 4814-4820 ◽  
Author(s):  
Indranil Pan ◽  
Saptarshi Das ◽  
Ayan Mukherjee ◽  
Amitava Gupta
Keyword(s):  
Control Systems ◽  
Fractional Order ◽  
Networked Control Systems ◽  
Pid Controllers ◽  
Optimal Time ◽  
Packet Dropout ◽  
Random Delay ◽  
Order Scheduling ◽  
Domain Performance ◽  
Fractional Order Pid

Application of fractional order (FO) PID controllers has been proposed over an unreliable network with random delays and packet dropouts. The gain and order of the controllers have been tuned offline to obtain optimal time domain performance for different network conditions with the help of Genetic Algorithm (GA). The FO controller parameters are then scheduled for time varying network conditions and the performance is compared with their integer order counterparts.

scholarly journals Dynamic Output Feedback Control for Nonlinear Networked Control Systems with Random Packet Dropout and Random Delay

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Shuiqing Yu ◽  
Junmin Li ◽  
Yingde Tang
Keyword(s):  
Control Systems ◽  
Output Feedback ◽  
Networked Control Systems ◽  
Output Feedback Control ◽  
Packet Dropout ◽  
Dynamic Output Feedback ◽  
Random Delay ◽  
Dynamic Output ◽  
Nonlinear Networked Control Systems ◽  
Random Packet Dropout

This paper investigates the dynamic output feedback control for nonlinear networked control systems with both random packet dropout and random delay. Random packet dropout and random delay are modeled as two independent random variables. An observer-based dynamic output feedback controller is designed based upon the Lyapunov theory. The quantitative relationship of the dropout rate, transition probability matrix, and nonlinear level is derived by solving a set of linear matrix inequalities. Finally, an example is presented to illustrate the effectiveness of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document