Output controllability and optimal output control of state-dependent switched Boolean control networks

Automatica ◽  
2014 ◽  
Vol 50 (7) ◽  
pp. 1929-1934 ◽  
Author(s):  
Hao Chen ◽  
Jitao Sun
Keyword(s):  
Output Control ◽  
Control Networks ◽  
Optimal Output ◽  
State Dependent ◽  
Output Controllability

scholarly journals Robust Output Controllability Analysis and Control Design for Incomplete Boolean Networks with Disturbance Inputs

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Lei Deng ◽  
Shihua Fu ◽  
Ying Li ◽  
Peiyong Zhu
Keyword(s):  
Sufficient Conditions ◽  
Boolean Networks ◽  
Algebraic Form ◽  
Output Control ◽  
Optimal Output ◽  
Product Technique ◽  
Output Controllability ◽  
The Cost ◽  
Necessary And Sufficient ◽  
And Control

This paper addresses the problems of robust-output-controllability and robust optimal output control for incomplete Boolean control networks with disturbance inputs. First, by resorting to the semi-tensor product technique, the system is expressed as an algebraic form, based on which several necessary and sufficient conditions for the robust output controllability are presented. Second, the Mayer-type robust optimal output control issue is studied and an algorithm is established to find a control scheme which can minimize the cost functional regardless of the effect of disturbance inputs. Finally, a numerical example is given to demonstrate the effectiveness of the obtained new results.

scholarly journals Output controllability and observability of mix-valued logic control networks

2021 ◽  
Vol 1 (3) ◽  
pp. 145-156
Author(s):  
Yuyang Zhao ◽  
◽  
Yang Liu
Keyword(s):  
Tensor Product ◽  
Transition Matrix ◽  
Initial State ◽  
Control Networks ◽  
Controllability Matrix ◽  
Logic Control ◽  
Product Method ◽  
Output Controllability ◽  
Controllability And Observability ◽  
Logical Rules

<abstract><p>This paper focuses on output controllability and observability of mix-valued logic control networks (MLCNs), of which the updating of outputs is determined by both inputs and states via logical rules. First, as for output controllability, the number of different control sequences are derived to steer a MLCN from a given initial state to a destination output in a given number of time steps via semi-tensor product method. By construsting the output controllability matrix, criteria for the output controllability are obtained. Second, to solve the problem of observability, we construct an augmented MLCN with the same transition matrix, and use the set controllability approach to determine the observability of MLCNs. Finally, a hydrogeological example is presented to verify the obtained results.</p></abstract>

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