On the Dynamic Response of Actuation Devices in Open and Closed-Loop Mechanisms With Nonlinear Dynamics

2014 ◽  
Author(s):  
Jahangir Rastegar ◽  
Dake Feng
Keyword(s):  
Nonlinear Dynamics ◽  
Dynamic Response ◽  
Closed Loop ◽  
Mechanical Systems ◽  
Open Loop ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Actuation System ◽  
Highly Nonlinear ◽  
Actuation Devices

This paper presents a study of the dynamic response of actuation devices used in mechanical systems with open and closed-loop linkage mechanisms and highly nonlinear dynamics such as robot manipulators. The study shows that the actuation forces/torques provided by actuation devices can be divided into two basic groups. The first group corresponds to the components of each actuator force/torque that is “actuator motion independent”. The dynamic response of this group is relatively high and limited only by the dynamic response limitations — for the case of electrically driven actuation systems — of the driving power amplifiers, electronics, computational and signal processing devices and components. The second group corresponds to those components of the actuator forces/torques that is “actuator motion dependent”. The dynamic response of this group is relatively low and dependent on the actuator effective inertial load and actuation speed. In all mechanical systems that are properly designed, the dynamic response of the first group is significantly higher than those of the second group. By separating the required actuating forces/torques into the above two groups, the dynamic response of such nonlinear dynamics systems may be determined for a given synthesized trajectory. The information can also be used to significantly increase the performance of mechanical systems. When a feed-forward control signal is used, the performance of the system is shown to be significantly improved by generating each one of the group of actuation components separately considering the dynamic response of the actuation system to each group of components. A method for separating the actuation forces/torques into the said “actuator motion independent” and “actuator motion dependent” groups for mechanical systems with open-loop and closed-loop linkage mechanisms is provided. Provided examples include an open-loop manipulators with feed-forward trajectory control and a closed-loop mechanism, both with highly nonlinear dynamics. Practical methods for implementing the proposed feed-forward control for nonlinear dynamics systems are discussed.

On the Dynamic Response of Actuation Devices in Nonlinear Dynamics Systems

2013 ◽  
Author(s):  
Jahangir Rastegar ◽  
Dake Feng
Keyword(s):  
Nonlinear Dynamics ◽  
Dynamic Response ◽  
Control Systems ◽  
Mechanical Systems ◽  
Inertial Load ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Actuation System ◽  
Actuation Devices ◽  
Actuation Systems

This paper presents a study of the dynamic response of actuation devices used in mechanical systems with nonlinear dynamics such as robot manipulators. The study shows that the actuation forces/torques provided by actuation devices can be divided into two basic groups. The first group corresponds to the components of each actuator force/torque that is “actuator motion independent”. The dynamic response of this group is relatively high and limited only by the dynamic response limitations — for the case of electrically driven actuation systems — of the driving power amplifiers, electronics, computational and signal processing devices and components. The second group corresponds to those components of the actuator forces/torques that is “actuator motion dependent”. The dynamic response of this group is relatively low and dependent on the actuator effective inertial load and actuation speed. In all mechanical systems that are properly designed, the dynamic response of the first group is significantly higher than those of the second group. By separating the required actuating forces/torques into the above two groups, the dynamic response of such nonlinear dynamics systems may be determined for a given synthesized trajectory. The information can also be used to significantly increase the performance of control systems of such mechanical systems. When a feed-forward control signal is used, the performance of the system is shown to be significantly improved by generating each one of the group of components separately considering the dynamic response of the actuation system to each one of the groups of components. An example and practical methods of implementing the proposed feed-forward control for nonlinear dynamics systems are provided.

On the Comparison of the Dynamic Performance of Open-Loop and Closed-Loop Mechanisms

2014 ◽  
Author(s):  
Jahangir Rastegar ◽  
Dake Feng
Keyword(s):  
Dynamic Response ◽  
Dynamic Systems ◽  
Closed Loop ◽  
Dynamic Performance ◽  
Mechanical Systems ◽  
Open Loop ◽  
Actuation Devices

In general, mechanical systems with closed-loop mechanisms can achieve significantly higher operating speeds as compared to open-loop mechanisms such as robots performing identical tasks. In this brief paper, the reason for the superior dynamic performance of closed-loop mechanisms as compared to open-loop mechanisms performing identical tasks is shown to be the inherent dynamic response limitations of the actuation devices in open-loop dynamic systems. Several examples are provided.

The application of compound proportional resonant control strategy in multiple PV inverters system

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840098
Author(s):  
Yuan Li ◽  
Huifang Shen ◽  
Chao Xiong ◽  
Yaofei Han ◽  
Guofeng He
Keyword(s):  
Control Strategy ◽  
Closed Loop ◽  
Control Strategies ◽  
Integrated Control ◽  
Reference Signal ◽  
Loop Model ◽  
Harmonic Compensation ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Set Up

In order to eliminate the effect on the grid current caused by the background harmonic voltage and the reference signal on the grid connected multi-inverter, this paper adopts the double closed-loop feed-forward control strategy. This strategy is based on the inductor voltage and the grid-connected current, and the integrated control strategy of quasi-proportional resonance loop parallel to a specific harmonic compensation loop. Based on the closed-loop model of multiple inverters, the change curves of the transfer function of the two control strategies are compared with the feed-forward control and the composite proportional resonance. The two corresponding control methods are used to analyze the current quality of the multi-inverter impact. Finally, the MATLAB/Simulink simulation model is set up to verify the proposed control strategies. The simulation results show that the proposed method can achieve better tracking of the sinusoidal command signal at the fundamental frequency, and enhance the anti-interference ability of the system at the 3rd, 5th, and 7th harmonic frequency.

scholarly journals PI- Controlled PV Fed Fly Back Converter with Enhanced Dynamic Response

2019 ◽  
Vol 8 (2S11) ◽  
pp. 4031-4034
Keyword(s):  
Steady State ◽  
Dynamic Response ◽  
Rise Time ◽  
Closed Loop ◽  
Input Voltage ◽  
Pi Controller ◽  
Open Loop ◽  
Load Variations ◽  
Simulink Model ◽  
Step Down

Fly back converter is the most popular converter because of its simplicity, low part counts and isolation. It occupies less volume and it saves cost. Fly back converter steps up and step down the voltage with the same polarity. Open loop operation remains insensitive to the input voltage and load variations. Matlab Simulink model for Fly back converter is established using PI controller. Open loop Fly back converter system and closed loop fly back converter systems are simulated and their outcomes are compared. Comparison is done in terms of Rise time ,Settling time and steady state error

scholarly journals Positioning system for assembly and manufacturing tasks

2019 ◽  
Vol 299 ◽  
pp. 02002
Author(s):  
Radu-Eugen Breaz ◽  
Sever-Gabriel Racz
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Closed Loop Control ◽  
Positioning System ◽  
Programmable Logic ◽  
Loop Control ◽  
Asynchronous Motors ◽  
Voltage Frequency ◽  
Incremental Encoder ◽  
Actuation Devices

The paper presents a two-axis positioning system using asynchronous motors as actuation devices. Theuse of asynchronous motors reduces the overall cost of the system, while providing actuating torques superior to the ones provided by stepping motors. The system is controlled by mean of a programmable logic controller (PLC) and two voltage-frequency inverters fitted with motion control cards. In contrasts to a stepping motor system, which works in open loop mode, the proposed system uses closed loop control on each axis. The motion loop is closed by means of an incremental encoder.

Experiments on Point-to-Point Control of a Flexible Beam Using Laplace Transform Technique: Part II—Closed-Loop

1991 ◽  
Vol 113 (3) ◽  
pp. 438-443 ◽  
Author(s):  
S. P. Bhat ◽  
D. K. Miu
Keyword(s):  
Closed Loop ◽  
Position Control ◽  
Open Loop ◽  
Flexible Beam ◽  
Laplace Domain ◽  
Loop Control ◽  
Feed Forward Control ◽  
Laplace Transform Technique ◽  
Point Control ◽  
Point To Point

Using the Laplace domain synthesis technique documented in earlier publications, experiments on the closed-loop point-to-point position control of a flexible beam are presented. Two different approaches are described, a feed-forward control and an iterative open-loop control. Solution to the robustness problems encountered during actual implementation is also demonstrated.

A Neural Network Strategy for Learning of Nonlinearities Toward Feed-Forward Control of Pressure-Compensated Hydraulic Valves With a Significant Dead Zone

2018 ◽  
Author(s):  
Jarmo Nurmi ◽  
Mohammad M. Aref ◽  
Jouni Mattila
Keyword(s):  
Adaptive Learning ◽  
Dead Zone ◽  
Effective Means ◽  
Previous Method ◽  
Deep Convolutional Neural Networks ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Highly Nonlinear ◽  
Hydraulic Manipulator ◽  
Hydraulic Valves

A velocity feed-forward-based strategy is an effective means for controlling a heavy-duty hydraulic manipulator; in particular, a typical valve-controlled hydraulic manipulator, to compensate for valve dead-zone and other hydraulic valve nonlinearities. Based on our previous work on the adaptive learning of valve velocity feed-forwards, manually labelling and identifying the dead-zones and the other nonlinearities in the velocity feed-forward curves of pressure-compensated hydraulic valves can be avoided. Nevertheless, it may take two to three minutes or more per actuator to identify a pressure-compensated valve’s highly nonlinear velocity feed-forward in real-time with an adaptive approach, which should be reduced for realistic applications. In this paper, inspired by brain signal analysis technologies, we propose a new method based on deep convolutional neural networks comparing with the previous method to significantly reduce this online learning process with the strong nonlinearities of pressure-compensated hydraulic valves. We present simulation results to demonstrate the effectiveness of the deep learning-based learning method compared to the previous results with an adaptive control-based learning.

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