Search Results for author: Zhe Shen

Found 7 papers, 0 papers with code

Stability Analysis of a Feedback-linearization-based Controller with Saturation: A Tilt Vehicle with the Penguin-inspired Gait Plan

no code implementations29 Nov 2021 Zhe Shen, Yudong Ma, Takeshi Tsuchiya

Saturations in control signal can challenge the stability proof of a feedback-linearization-based controller, even leading the system unstable [1].

Flight Control System Design for Autonomous Aerial Surveys of Volcanoes

no code implementations21 Nov 2021 Zhe Shen

The eigenvalue of the feedback controller is picked based on the method developed in Chapter Path Planning.

State Drift and Gait Plan in Feedback Linearization Control of A Tilt Vehicle

no code implementations8 Nov 2021 Zhe Shen, Takeshi Tsuchiya

In this research, we put forward a unique fictional vehicle with tilt structure, which is to help evaluate the property of the tilt-structure-aimed controllers.

Singular Zone in Quadrotor Yaw-Position Feedback Linearization

no code implementations14 Oct 2021 Zhe Shen, Takeshi Tsuchiya

It is well known that the conventional quadrotor is an under-actuated MIMO system.

Position

The Pareto-frontier-based Stiffness of A Controller: Trade-off between Trajectory Plan and Controller Design

no code implementations19 Aug 2021 Zhe Shen, Takeshi Tsuchiya

Specially, the unavoidable dynamic state error is considered in the trajectory plan process, assuming the LQR without the feed-forward is applied in the subsequent control after plan problems.

A Novel Formula Calculating the Dynamic State Error and Its Application in UAV Tracking Control Problem

no code implementations18 Aug 2021 Zhe Shen, Takeshi Tsuchiya

This paper gives a novel formula (Copenhagen Limit) to calculate/estimate the dynamic state error of a system without a feedforward signal.

Identification of splicing edges in tampered image based on Dichromatic Reflection Model

no code implementations9 Apr 2020 Zhe Shen, Peng Sun, Yubo Lang, Lei Liu, Silong Peng

Therefore we present a novel optic-physical method to discriminate splicing edges from natural edges in a tampered image.

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