Discrete-time linear-quadratic (LQ) optimal and nonlinear flow control in multi-source connection-oriented communication networks

2009 ◽  
Vol 20 (7) ◽  
pp. 679-688 ◽  
Author(s):  
Przemysław Ignaciuk ◽  
Andrzej Bartoszewicz
Keyword(s):  
Flow Control ◽  
Communication Networks ◽  
Discrete Time ◽  
Nonlinear Flow ◽  
Linear Quadratic ◽  
Time Linear

Discrete Linear Time Invariant Analysis of Digital Fluid Power Pump Flow Control

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Per Johansen ◽  
Daniel B. Roemer ◽  
Torben O. Andersen ◽  
Henrik C. Pedersen
Keyword(s):  
Flow Control ◽  
Discrete Time ◽  
Control Method ◽  
Linear Time ◽  
Linearization Method ◽  
Fluid Power ◽  
Linear Time Invariant ◽  
Pump Flow ◽  
Linear Control Theory ◽  
Time Linear

A fundamental part of a digital fluid power (DFP) pump is the actively controlled valves, whereby successful application of these pumps entails a need for control methods. The focus of the current paper is on a flow control method for a DFP pump. The method separates the control task concerning timing of the valve activation and the task concerning the overall flow output control. This enables application of linear control theory in the design process of the DFP pump flow controller. The linearization method is presented in a general framework and an application with a DFP pump model exemplifies the use of the method. The implementation of a discrete time linear controller and comparisons between the nonlinear model and the discrete time linear approximation shows the applicability of the control method.

Calculation of Optimized Movement Trajectories for the Human Forearm

2013 ◽  
Vol 401-403 ◽  
pp. 1347-1352
Author(s):  
Li Li Yang
Keyword(s):  
Discrete Time ◽  
Linear Quadratic Regulator ◽  
Minimum Variance ◽  
Movement Trajectory ◽  
Linear Quadratic ◽  
Variance Model ◽  
Movement Trajectories ◽  
Human Forearm ◽  
Optimal Movement ◽  
Time Linear

Using the minimum variance model, optimal human forearm trajectories formation was investigated using a discrete time linear quadratic regulator. First, the continuous dynamics of the human forearm were established on the basis of the relation between muscle torque and neural control signal, and then we transferred the continuous system dynamics to discrete time notation. Finally we expressed the objective function of minimum variance model using a discrete time linear quadratic regulator and employed Riccati recursion to obtain the optimal movement trajectories of the human forearm. The results of example simulation show that the optimal movement trajectory of the forearm follows a smooth curve, and the speed curve of the hand is single peaked and bell shaped. These are in good agreement with the inherent kinematic properties of optimal movement, and therefore the method is effective for calculating the optimal movement trajectory of the human forearm.

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