Decentralized social‐optimal solution of finite number of average field linear quadratic control

2021 ◽  
Author(s):  
Zhipeng Li ◽  
Damián Marelli ◽  
Minyue Fu ◽  
Zhigang Ren
Keyword(s):  
Finite Number ◽  
Optimal Solution ◽  
Average Field ◽  
Linear Quadratic Control ◽  
Linear Quadratic

scholarly journals Optimal linear quadratic control for wireless sensor and actuator networks with random delays and packet dropouts

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771877956
Author(s):  
Zhuwei Wang ◽  
Lihan Liu ◽  
Chao Fang ◽  
Xiaodong Wang ◽  
Pengbo Si ◽  
...  
Keyword(s):  
Frequency Control ◽  
Optimal Solution ◽  
Load Frequency Control ◽  
Wireless Sensor ◽  
Linear Quadratic Control ◽  
Linear Quadratic ◽  
Relay Nodes ◽  
Packet Dropouts ◽  
Frequency Control System ◽  
Optimal Linear

In this article, the optimal linear quadratic control problem is considered for the wireless sensor and actuator network with stochastic network-induced delays and packet dropouts. Considering the event-driven relay nodes, the optimal solution is obtained, which is a function of the current plant state and all past control signals. It is shown that the optimal control law is the same for all locations of the controller placement. Since the perfect plant state information is available at the sensor, the optimal controller should be collocated with the sensor. In addition, some issues such as the plant state noise and suboptimal solution are also discussed. The performance of the proposed scheme is investigated by an application of the load frequency control system in power grid.

scholarly journals Suboptimality in linear control systems with time delay

1982 ◽  
Vol 23 (4) ◽  
pp. 428-437
Author(s):  
W. L. Chan
Keyword(s):  
Control Systems ◽  
Performance Index ◽  
Optimal Solution ◽  
Linear Control ◽  
Linear Control Systems ◽  
Linear Quadratic Control ◽  
A Posteriori ◽  
Linear Quadratic ◽  
Elementary Methods ◽  
And Control

AbstractFor the linear quadratic control problem with delay, a lower bound for the performance index is obtained by elementary methods. Using this bound, two important a posteriori error estimates are derived. The first one measures the deviation of the performance index while the second is for the deviation of the state and control variables from the optimal solution.

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