Speed tracking control for the gimbal system with harmonic drive

Li, Haitao; Ning, Xin; Han, Bangcheng

doi:10.1016/j.conengprac.2016.11.001

Cited by 21 publications

(3 citation statements)

References 40 publications

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“…Simulation results are shown Figures 9,10,11,12,13,14,15,16,17,18,19,20,21. Step 1: The author has done a search for components on Simulink.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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LQG, PID controller, ANN for single axis gimbal actuator

Danh¹

2022

EAI Endorsed Trans AI Robotics

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Gimbal or other stable platforms have structures that move according to its functions. This is for the purpose of keeping track of the goals to the fullest. Tracking targets can become difficult as the subject moves further and further away and they are out of the gimbal’s allowable viewing range. Besides, under the influence of noise signals form outside space, it becomes even more difficult to observe the gimbal’s targets. To overcome above disadvantages, this paper is presented an adjustment method to limit above risks. Adjusting Linear Quadratic Gaussian (LQG) for expensive gimbal systems, noise signals are processed purely by Kalman filters to improve the function of observing targets. In addition, proportional- integral-derivative (PID) controller, artificial neural network in this case is also considered to verify the effectiveness of control methods listed below. In particular, ANN is the most effective control method today to deal with unwanted signals. These unwanted signals can cause worsening conditions during the operation of systems.Therefore, artificial network (ANN) is a solution to information and communication security problems. Simulation is done by Matlab. Novelty of the work: no previous research has been published for this genre. The study of this genre with the use of artificial intelligence is suggestive of the study of artificial intellligence technologies at a higher level. This category is also a suggestion for studying a smoother control method based on existing data.

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“…Simulation results are shown Figures 9,10,11,12,13,14,15,16,17,18,19,20,21. Step 1: The author has done a search for components on Simulink.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Precise control [16] for a two-axis gimbaled sensor system is a new research work that the author looks forward to doing it in the future. Speed tracking control [17] for ac-robots with harmonic drive is an endless source of inspiration. The techniques in [18,19,20,21] can be applied for ac-robots.…”

Section: Introductionmentioning

confidence: 99%

LQG, PID controller, ANN for single axis gimbal actuator

Danh¹

2022

EAI Endorsed Trans AI Robotics

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“…In Chen et al's work [ 23 ], they propose this model in the presence of a gyroscope and examine its performance. In the article by Li et al [ 24 ], another improvement to the model is the use of a PID controller for system. I can use a PI controller for the system to investigate the behavior of Abdo et al's model [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

The Stability of a Two-Axis Gimbal System for the Camera

Danh

2021

The Scientific World Journal

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Gimbal or an inertial stabilization platform (ISP) is used to stabilize the line of sight of an object or device that is tracking another object (LOS) with stationary or moving targets or targets moving forward. It can achieve precision when there is isolation between the tracker and the gimbal base. Studying the 2-axis tilt angle to create gimbal stability, especially in a camera, is a compelling subject for the automation field, as it is controlled by modern controllers. This paper presents a two-axis gimbal loop in which the LOS rate is stable, and I proceed to examine the stability of the system to get a better overview of the system properties. Through examining the stability of the system, I can choose from modern control methods to control them. The stability of the system used from the two analysis methods I present below gives me a visual view from the results achieved. The simulation is performed in MATLAB.

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Dual‐channel observer design for composite disturbances based on characteristic compensation

Wen,

Wang,

Dong

et al. 2024

Intl J Robust & Nonlinear

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This paper presents a non‐coupled structure of characteristic compensation dual‐channel observer (CCDCO) for handling systems subjected to composite disturbances. There exist an outer disturbance compensation channel (ODCC) and an inner disturbance compensation channel (IDCC) in the design strategy. Specifically, in the ODCC, the proposed frequency characteristic compensation observer (FCCO) extracts and removes the regular periodic components from the composite disturbances, where the estimation error preserves irregular characteristics. Thus, the estimation error of FCCO and irregular parts are treated as lumped terms estimated via compensation function observer (CFO) in the IDCC. As a solving skill for composite disturbances estimation, CCDCO has two important advantages over previous designs. First, the proposed non‐coupled structure explicitly distinguishes disturbance characteristics according to a priori information known or not. Second, by combining the benefits of the CFO and proposed FCCO, different types of disturbances can be estimated accordingly without coupling of each other. Simulation results on the robotic manipulator are provided to validate the effectiveness of the proposed method.

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Speed tracking control for the gimbal system with harmonic drive

Cited by 21 publications

References 40 publications

LQG, PID controller, ANN for single axis gimbal actuator

LQG, PID controller, ANN for single axis gimbal actuator

The Stability of a Two-Axis Gimbal System for the Camera

Dual‐channel observer design for composite disturbances based on characteristic compensation

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