Modeling of an Inertially Stabilized Camera System Using Gimbal Platform

2016 ◽  
Author(s):  
Gary Haggart ◽  
Vidya K. Nandikolla ◽  
Ruting Jia
Keyword(s):  
Low Cost ◽  
System Stability ◽  
Motor Drive ◽  
Performance Limits ◽  
Camera System ◽  
Control Scheme ◽  
Selection For ◽  
And Performance ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

This paper develops a camera gimbal platform for stabilization and tracking purposes. The main focus of this research is analytical modeling of an inertially stabilized platform with the prediction of the angular stability. The mechanical model of the platform includes, moment of inertia, motor drive, and performance of the gyro to measure the disturbances of the platform. The gimbal/motor system is developed and simulated and feedback control scheme is designed to stabilize and maintain the line of sight (LOS) for tracking purposes. The model integrates a PI2 controller using a PID-I approach for the system stability. The effect of vibration induced disturbance in the system is investigated to simulate the realistic behavior of an inertially stabilized platform. The simulation results of the four types of commercial gyros are presented to calculate the required values for stability purposes. The results from the simulation generated the performance limits chart describing the working condition of the low cost sensors vs the high cost sensors. As the vibration level increased, the performance of the highest quality sensor greatly decreased. This verifies the value and necessity of modeling and simulating to understand the component trade studies to ensure correct sensor selection for the desired application.

scholarly journals A High-Precision Control Scheme Based on Active Disturbance Rejection Control for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiangyang Zhou ◽  
Chao Yang ◽  
Beilei Zhao ◽  
Libo Zhao ◽  
Zhuangsheng Zhu
Keyword(s):  
Disturbance Rejection ◽  
Precision Control ◽  
Sensing Applications ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Control Scheme ◽  
Remote Sensing Applications ◽  
Aerial Remote Sensing ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

This paper presents a high-precision control scheme based on active disturbance rejection control (ADRC) to improve the stabilization accuracy of an inertially stabilized platform (ISP) for aerial remote sensing applications. The ADRC controller is designed to suppress the effects of the disturbance on the stabilization accuracy that consists of a tracking differentiator, a nonlinear state error feedback, and an extended state observer. By the ADRC controller, the effects of both the internal uncertain dynamics and the external multisource disturbances on the system output are compensated as a total disturbance in real time. The disturbance rejection ability of the ADRC is analyzed by simulations. To verify the method, the experiments are conducted. The results show that compared with the conventional PID controller, the ADRC has excellent capability in disturbance rejection, by which the effect of main friction disturbance on the control system can be weakened seriously and the stabilization accuracy of the ISP is improved significantly.

scholarly journals Coupling Analysis and Cross-Feedback Control of Three-Axis Inertially Stabilized Platform with an Active Magnetic Bearing System

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Tong Wen ◽  
Biao Xiang ◽  
Waion Wong
Keyword(s):  
Feedback Control ◽  
Vibration Isolation ◽  
Base Plate ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Single Input Single Output ◽  
Control Scheme ◽  
Amb System ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

An active magnetic bearing (AMB) system is used to suspend the yaw gimbal of three-axis inertially stabilized platform (ISP) to minimize the friction. The dynamic functions of three gimbals in ISP are developed. The base coupling at dynamic base plate is stronger than that at static base plate, and the gimbal coupling among three gimbals increases with the number of unlocked gimbals. Therefore, a cross-feedback control scheme is designed to minimize the base coupling and the gimbal coupling, and then the multi-input multioutput system of three-axis ISP with coupling terms is simplified into three decoupled single-input single-output systems. Experimental results verify that the yaw gimbal suspended by AMB system has better vibration isolation ability than the roll gimbal supported by mechanical bearing, and the gimbal coupling and the base coupling are effectively suppressed by the cross-feedback control scheme.

Stability analysis of a time-optimally controlled electrostatic suspension system and suspension experiments in a vacuum

2010 ◽  
Vol 225 (1) ◽  
pp. 88-100 ◽  
Author(s):  
T T Le ◽  
J U Jeon
Keyword(s):  
Low Cost ◽  
Electromagnetic Levitation ◽  
Dielectric Materials ◽  
Suspension System ◽  
System Stability ◽  
Suspension Systems ◽  
Control Scheme ◽  
Time Optimal ◽  
Bang Bang Control ◽  
Work First

Electrostatic suspension permits conductive, semiconductive, and dielectric materials to be supported without mechanical contact, in contrast to electromagnetic levitation by which only ferromagnetic materials can be levitated. To expand applications of electrostatic suspension systems, a low-cost electrostatic suspension system using a time optimal bang—bang control scheme where linear analogue high-voltage amplifiers that are costly and bulky are not employed has already been implemented. In this article, a time optimal bang—bang control scheme is used to stabilize the system like the previous work. First, the process to find the recoverable set for all the states in which a time optimal bang—bang control exists is described in detail. Then, the switching criterion for the suspension system is derived by using a backward integration technique and the system stability is theoretically investigated using Lyapunov's function as well. To experimentally verify the system stability in vacuum, suspension experiments are carried out with 3.5 in aluminium discs in a vacuum environment. Experiments in the atmosphere are also conducted for comparison with the results in the vacuum. The experimental results show that an aluminium disc has been stably suspended at a reference gap length of 300 μm in a vacuum environment.

Iterative Learning Control With Optimal Feedback and Feedforward Control

2010 ◽  
Author(s):  
Shuwen Yu ◽  
Masayoshi Tomizuka
Keyword(s):  
Control Strategy ◽  
Iterative Learning Control ◽  
Feedforward Control ◽  
Learning Control ◽  
Iterative Learning ◽  
System Stability ◽  
Optimal Feedback ◽  
Control Scheme ◽  
Combined Control ◽  
And Performance

Iterative learning control (ILC) is a feedforward control strategy used to improve the performance of a system that executes the same task repeatedly, but is incapable of compensating for non-repetitive disturbances. Thus a well-designed feedback controller needs to be used in combination with ILC. A robustness filter called the Q-filter is essential for the ILC system stability. The price to pay, however, is that the Q-filter makes it impossible for ILC to achieve perfect tracking of the repetitive reference or perfect cancellation of repetitive disturbances. To reduce error, it is effective to apply a pre-design feedforward control input in addition to ILC. In this paper, a simple P-type ILC is combined with an optimal feedback-feedforward control inspired by classic predictive control, so as to take advantages of each control strategy. It will be shown that the choice of the injection point of the learned ILC effort is crucial for a tradeoff between stability and performance. Therefore, the stability and performance analysis based on different injection points is studied. A systematic approach to the combined control scheme is also proposed. The combined control scheme is attractive due to its simplicity and promising performance. The effectiveness of the combined control scheme is verified by simulation results with a wafer scanner system.

scholarly journals An Improved Fuzzy Neural Network Compound Control Scheme for Inertially Stabilized Platform for Aerial Remote Sensing Applications

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xiangyang Zhou ◽  
Yating Li ◽  
Yuan Jia ◽  
Libo Zhao
Keyword(s):  
Disturbance Rejection ◽  
Fuzzy Neural Network ◽  
Variable Universe ◽  
Compound Control ◽  
Sensing Applications ◽  
Control Scheme ◽  
Fuzzy Neural ◽  
Remote Sensing Applications ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

An improved fuzzy neural network (FNN)/proportion integration differentiation (PID) compound control scheme based on variable universe and back-propagation (BP) algorithms is proposed to improve the ability of disturbance rejection of a three-axis inertially stabilized platform (ISP) for aerial remote sensing applications. In the design of improved FNN/PID compound controller, the variable universe method is firstly used for the design of the fuzzy/PID compound controller; then, the BP algorithm is utilized to finely tune the controller parameters online. In this way, the desired performances with good ability of disturbance rejection and high stabilization accuracy are obtained for the aerial ISP. The simulations and experiments are, respectively, carried out to validate the improved FNN/PID compound control method. The results show that the improved FNN/PID compound control scheme has the excellent capability in disturbance rejection, by which the ISP’s stabilization accuracy under dynamic disturbance is improved significantly.

scholarly journals Robust H∞ Control for Path Tracking of Network-Based Autonomous Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Changfang Chen ◽  
Minglei Shu ◽  
Yinglong Wang ◽  
Ruixia Liu
Keyword(s):  
Autonomous Vehicles ◽  
Path Tracking ◽  
System Stability ◽  
Linear Matrix ◽  
Packet Dropout ◽  
Negative Effects ◽  
Parameter Uncertainties ◽  
Control Scheme ◽  
And Performance ◽  
Attention Level

This paper investigates the robust H∞ path-tracking control problem of network-based autonomous vehicles (AVs) with delay and packet dropout. Generally, both network-induced delay and packet dropout bring negative effects on the system stability and performance. A robust H∞ control scheme is proposed to realize the desired path tracking and lateral stability. The closed-loop system is asymptotically stable with the prescribed H∞ disturbance attention level if there exist some matrices satisfying certain linear matrix inequality (LMI) conditions. Furthermore, the proposed controller is robust to the parameter uncertainties and external disturbances. Simulation results are presented to verify the effectiveness of the proposed control scheme.

scholarly journals Calibration of multi-camera photogrammetric systems

2014 ◽  
Vol XL-1 ◽  
pp. 101-108 ◽  
Author(s):  
I. Detchev ◽  
M. Mazaheri ◽  
S. Rondeel ◽  
A. Habib
Keyword(s):  
Stability Analysis ◽  
Low Cost ◽  
A Priori ◽  
Relative Orientation ◽  
System Stability ◽  
Specific System ◽  
Camera System ◽  
System Calibration ◽  
System Stability Analysis ◽  
Orientation Parameters

Due to the low-cost and off-the-shelf availability of consumer grade cameras, multi-camera photogrammetric systems have become a popular means for 3D reconstruction. These systems can be used in a variety of applications such as infrastructure monitoring, cultural heritage documentation, biomedicine, mobile mapping, as-built architectural surveys, etc. In order to ensure that the required precision is met, a system calibration must be performed prior to the data collection campaign. This system calibration should be performed as efficiently as possible, because it may need to be completed many times. Multi-camera system calibration involves the estimation of the interior orientation parameters of each involved camera and the estimation of the relative orientation parameters among the cameras. This paper first reviews a method for multi-camera system calibration with built-in relative orientation constraints. A system stability analysis algorithm is then presented which can be used to assess different system calibration outcomes. The paper explores the required calibration configuration for a specific system in two situations: major calibration (when both the interior orientation parameters and relative orientation parameters are estimated), and minor calibration (when the interior orientation parameters are known a-priori and only the relative orientation parameters are estimated). In both situations, system calibration results are compared using the system stability analysis methodology.

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