Dynamic Feedback Linearization for Electrohydraulically Actuated Control Systems

1995 ◽  
Vol 117 (4) ◽  
pp. 468-477 ◽  
Author(s):  
Gholamreza Vossoughi ◽  
Max Donath
Keyword(s):  
Control Systems ◽  
Feedback Linearization ◽  
Operating Conditions ◽  
Control Law ◽  
Dynamic Feedback ◽  
Uncertainty Model ◽  
Rotational Joint ◽  
Linearized System ◽  
Linear Controllers ◽  
Robust Control Systems

Using the dynamic inversion principal, a globally linearizing feedback control law is developed for an electrohydraulic servo system. The proposed control law is implemented on a rotational joint driven by a linear actuator. The results from experiments indicate that better uniformity of response is achieved across a wider range of operating conditions than would otherwise be possible. Improved symmetry is obtained for the extension and retraction phases of motion for an asymmetric actuator under various loading conditions and actuator positions. As a result of the improvements in linearity, significantly better performance is achieved when using linear controllers. To incorporate the effects of parametric uncertainties on the feedback linearization, a state space linear fractional representation of the parametrically uncertain linearized system is also developed. This uncertainty model is specifically suited for the design of robust control systems using the μ-synthesis and H∞ based approach.

scholarly journals The Effects of Weighting Functions on the Performances of Robust Control Systems

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 46
Author(s):  
Mircea Dulau ◽  
Stelian-Emilian Oltean
Keyword(s):  
Robust Control ◽  
Control Systems ◽  
Tracking Error ◽  
Weighting Functions ◽  
Loop Control ◽  
Frequency Sensitivity ◽  
Sensitivity Functions ◽  
Loop Control System ◽  
Robust Control Design ◽  
Robust Control Systems

An important stage in robust control design is to define the desired performances of the closed loop control system using the models of the frequency sensitivity functions S. If the frequency sensitivity functions remain within the limits imposed by these models, the control performances are met. In terms of the sensitivity functions, the specifications include: shape of S over selected frequency ranges, peak magnitude of S, bandwidth frequency, and tracking error at selected frequencies. In this context, this paper presents a study of the effects of the specifications of the weighting functions on the performances of robust control systems.

Integration of Multibody System Dynamics With Sliding Mode Control Using FPGA Technique for Trajectory Tracking Problems

2018 ◽  
Author(s):  
Ayman A. Nada ◽  
Abdullateef H. Bashiri
Keyword(s):  
Sliding Mode Control ◽  
Mobile Robot ◽  
Control Systems ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Integrated Control ◽  
Equations Of Motion ◽  
Multiple Input Multiple Output ◽  
Control Law ◽  
Mode Control

Trajectory tracking robotic systems require complex control procedures that occupy less space and need less energy. For these reasons, the development of computerized and integrated control systems is crucial. Recently, developing reconfigurable Field Programmable Gate Arrays (FPGAs) give a prominence of the complete robotic control systems. Furthermore, it has been found in the literature that the model-based control methods are most efficient and cost-effective. This model must interpret how multiple moving parts interact with each other and with their environment. On the other hand, MultiBody Dynamic (MBD) approach is considered to solve these difficulties to attain the models accurately. However, the obtained equations of motion do not match the well-developed forms of control theory. In this paper, the MBD model of a mobile robot is established; and the equations of motion are reshaped into their control canonical form. Additionally, the Sliding Mode Control (SMC) theory is used to design the control law. The constraints’ manifold, which is available in the equations of the MBD system, are imposed systematically as the switching surface. SMC is applied because of its ability to address multiple-input/multiple-output nonlinear systems without resorting any approximations. Eventually, the experimental verification of the proposed algorithm is carried out using DaNI mobile robot in which, a Reconfigurable Input/Output (RIO) board is used to reorient the control design, so that can fit the required trajectory. The control law is implemented using LabVIEW software and NI-sbRIO-9631 with acceptable performance. It is obvious that the integration of MBD/SMC/FPGA can be used successfully to develop embedded systems for the applications of trajectory tracking robotics.

A Dynamic Simulation Model of Industrial Robots for Energy Examination Purpose

2015 ◽  
Vol 805 ◽  
pp. 223-230 ◽  
Author(s):  
Paryanto ◽  
Alexander Hetzner ◽  
Matthias Brossog ◽  
Jörg Franke
Keyword(s):  
Energy Consumption ◽  
Control Systems ◽  
Feedback Linearization ◽  
Coulomb Friction ◽  
State Of The Art ◽  
Industrial Robot ◽  
Motor Drives ◽  
Industrial Robots ◽  
Dynamic Simulation Model ◽  
Linear Damping

In this paper, a modular dynamic model of an industrial robot (IR) for predicting and analyzing its energy consumption is developed. The model consists of control systems, which include a state-of-the-art feedback linearization controller, permanent magnet synchronous drives and the mechanical structure with Coulomb friction and linear damping. By using the developed model, a detailed analysis of the influence of different parameter sets on the energy consumption and loss energy of IRs is investigated. The investigation results show that the operating parameters, robot motor drives, and mechanical damping and elasticity of robot transmissions have a significant effect on the energy consumption and accuracy of IRs. However, these parameters are not independent, but rather interrelated. For example, a higher acceleration and velocity shortens IRs’ operating periods, but needs a greater motor current, tends to excite vibrations to a greater extent, and thus produces a higher amount of loss energy.

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