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Longke Wang

Researcher at Georgia Institute of Technology

Publications -  7
Citations -  146

Longke Wang is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Actuator & Hydraulic circuit. The author has an hindex of 4, co-authored 5 publications receiving 133 citations.

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Journal ArticleDOI

Application of Singular Perturbation Theory to Hydraulic Pump Controlled Systems

TL;DR: In this article, the authors use singular perturbation theory to simplify control designs for hydraulic systems and to make designs more feasible for engineering practice, and present the derivations, simulations and experimental tests of control laws for a hydraulic displacement-controlled actuator.
Journal ArticleDOI

A Hydraulic Circuit for Single Rod Cylinders

TL;DR: In this paper, the Flow Control Circuit with Dynamical Compensations with Stationary Stability Analysis and Dynamic Stability Analysis (SSA) is described. And the authors propose a compensation algorithm for the flow control Valves.
Journal ArticleDOI

Using Leakage to Stabilize a Hydraulic Circuit for Pump Controlled Actuators

TL;DR: In this paper, the authors examined the problem of system stability in a pump controlled system with single rod cylinders and showed that the system dynamics have a stable tendency or an instable tendency corresponding to different cylinder movements.
Proceedings ArticleDOI

A control approach with application to variable displacement pumps

TL;DR: In this paper, the authors present the derivations and simulations of a control law for a hydraulic displacement controlled actuator, which is robust to variations in the bulk modulus and position tracking error exponentially decays and control efforts are dominated by low frequency signals.
Proceedings ArticleDOI

Adaptive Robust Control of Hydraulic Robots With Recursive Least Squares

TL;DR: In this article, a robot control approach using a discrete recursive least square algorithm is proposed, which shows robustness when the system suffers from measurement noise and has a fast parameter convergence rate.