Optimal design of SINS's Stewart platform bumper for restoration accuracy based on genetic algorithm

Tu, Yongqiang; Yang, Ge; Wang, Lifeng; Zhou, Xiaohua

doi:10.1016/j.mechmachtheory.2018.01.016

Cited by 15 publications

(9 citation statements)

References 26 publications

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“…Compared with the driving forces, the friction of spherical joints and actuators is negligible. Therefore, power of six actuators can be expressed as follows according to (13) and (17): The derivation of (52) is in the appendix. Power of six actuators can be described with a cyclic function of the time, as shown in Figure 12.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

Dynamic Modeling and Analysis of a Novel 6‐DOF Robotic Crusher Based on Movement Characteristics

Shi

Liu

2019

Mathematical Problems in Engineering

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This paper proposes a novel 6-DOF robotic crusher that combines the performance characteristics of the cone crusher and parallel robot, such as interparticle breakage and high flexibility. Kinematics and dynamics are derived from the no-load and crushing parts in order to clearly describe the whole crushing process. For the no-load case, the kinematic and dynamic equations are established by using analytical geometry and Lagrange equation. Analytical geometry is mainly used to solve the inverse kinematics and then establish the velocity relationship between generalized coordinates and actuators. Lagrange equation which takes into account the weight of the mantle and actuators is used to solve driving forces of actuators. For the crushing case, crushing pressure is related to the compression ratio and particle size distribution, but the selection and breakage functions should be established first. Because the trajectory model of the mantle is difficult to be established by using analytical method, it can be obtained by an eccentric simulation. The results of input velocities and driving forces of actuators are distinctive due to the eccentric angle and selection of the initial position. Finally, the proposed approach is verified by a numerical example and then the energy consumption is calculated.

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Section: Numerical Results and Discussionmentioning

confidence: 99%

Dynamic Modeling and Analysis of a Novel 6‐DOF Robotic Crusher Based on Movement Characteristics

Shi

Liu

2019

Mathematical Problems in Engineering

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“…Therefore, the movement of the SP needs to be modeled to predict the attitude and position of the load platform and to verify the expression of the platform for the tested motion. Figure 13 shows the geometry of SP, in which the base platform is fixed to the ground, and the load platform moves according to the length of the six hydraulic struts [28]. Here, we define {P} and {B} as the coordinate systems of the load and the base platform, and O p and O b as the origins of these two coordinate systems.…”

Section: Stewart Platform (Sp) Modelingmentioning

confidence: 99%

Automatic Control and Model Verification for a Small Aileron-Less Hand-Launched Solar-Powered Unmanned Aerial Vehicle

et al. 2020

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This paper describes a low-cost flight control system of a small aileron-less hand-launched solar-powered unmanned aerial vehicle (UAV). In order to improve the accuracy of the whole system model and quantify the influence of each subsystem, detailed modeling of UAV energy and a control system including a solar model, engine, energy storage, sensors, state estimation, control law, and actuator module are established in accordance with the experiment and component principles. A whole system numerical simulation combined with the 6 degree-of-freedom (DOF) simulation model is constructed based on the typical mission route, and the parameter precision sequence and energy balance are obtained. Then, a hardware-in-the-loop (HIL) experiment scheme based on the Stewart platform (SP) is proposed, and three modes of acceleration, angular velocity, and attitude are designed to verify the control system through the inner and boundary states of the flight envelope. The whole system scheme is verified by flight tests at different altitudes, and the aerodynamic force coefficient and sensor error are corrected by flight data. With the increase of altitude, the cruise power increases from 47 W to 78 W, the trajectory tracking precision increases from 23 m to 44 m, the sensor measurement noise increases, and the bias decreases.

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“…Accelerometers, which provide acceleration information known as the specific force of a vehicle [ 1 ], is one of the core components of an inertial navigation system (INS) [ 2 , 3 ]. As a dead-reckoning navigation method, the navigation accuracy of an INS is restricted to the measurement error of the accelerometer [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Suppression of Nonlinear Error of Pendulous Integrating Gyroscopic Accelerometer at Instrument Level

Zhou

Yang

Niu

et al. 2023

Sensors

Self Cite

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The error coefficients of the pendulous integrating gyroscopic accelerometer (PIGA) mainly include the bias, scale factor, and nonlinear error. Previous works have fully studied and suppressed the bias and scale factor of PIGAs. At present, the nonlinear error is the most critical factor restricting the measurement accuracy of PIGAs. To address this barrier, a study on the analysis and suppression of the nonlinear error of PIGAs at the instrument level was carried out. Firstly, the error model of a PIGA is established by kinematics and dynamics analyses. Then, nonlinear error is analyzed based on the established model. Finally, a suppression method for the nonlinear error is proposed based on the analysis results. The nonlinear error analysis found that (1) the nonlinear error includes a quadratic term error caused by unequal inertia and the inertia product, cross-coupling error is caused by lateral accelerations, and error is caused by unequal stiffness; (2) unequal inertia and the inertia product were the most critical factors resulting in nonlinear error. Based on the results in the nonlinear error analysis, the suppression method for error focuses on unequal inertia and the inertia product. The proposed method of analysis and suppression was validated experimentally as the quadratic term coefficient was reduced by an order of magnitude from 1.9 × 10−6/g0 to 1.91 × 10−7/g0.

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Optimal design of SINS's Stewart platform bumper for restoration accuracy based on genetic algorithm

Cited by 15 publications

References 26 publications

Dynamic Modeling and Analysis of a Novel 6‐DOF Robotic Crusher Based on Movement Characteristics

Dynamic Modeling and Analysis of a Novel 6‐DOF Robotic Crusher Based on Movement Characteristics

Automatic Control and Model Verification for a Small Aileron-Less Hand-Launched Solar-Powered Unmanned Aerial Vehicle

Analysis and Suppression of Nonlinear Error of Pendulous Integrating Gyroscopic Accelerometer at Instrument Level

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