Optimal Control of an Assisted Passive Snake-Like Robot Using Feedback Linearization

2007 ◽  
Author(s):  
Saman Mohammadi ◽  
Zoya Heidari ◽  
Hojjat Pendar ◽  
Aria Alasty ◽  
Gholamreza Vossoughi
Keyword(s):  
Optimal Control ◽  
Nonlinear System ◽  
Nonlinear Control ◽  
Feedback Linearization ◽  
Equations Of Motion ◽  
Dynamic Equations ◽  
Unmodeled Dynamics ◽  
Pd Controller ◽  
Simulation Results ◽  
Distinct Line

In this paper we follow two approaches in optimal nonlinear control of a snake-like robot. After deriving the dynamic equations of motion using Gibbs-Appell method, reducing these equations, and some assumptions, feedbacklinearization method was used to linearize the nonlinear system. The obtained controller is used in simulations to control robot to track a desired line, with minimum required torques. Two goals are desired. First the robot’s head is expected to track a distinct line with a given speed. And next, tracking the serpenoid curve is desired. The simulation results prove the controller efficiency. The robustness of the designed controller is shown by comparing the torques with the required torques using a PD controller. Additionally, although we had model mismatches and unmodeled dynamics in controller part, we achieved the desired goals.

scholarly journals Stability and Manoeuvrability Simulation of a Semi-Autonomous Submarine Free-Running Model SUBOFF with an Autopilot System

2021 ◽  
Vol 11 (1) ◽  
pp. 410
Author(s):  
Yu-Hsien Lin ◽  
Yu-Ting Lin ◽  
Yen-Jun Chiu
Keyword(s):  
Optimal Control ◽  
Experimental Tests ◽  
Degree Of Freedom ◽  
Line Of Sight ◽  
Pd Controller ◽  
Free Running ◽  
Simulation Results ◽  
Guidance Algorithm ◽  
Logic Operations ◽  
Six Degree Of Freedom

On the basis of a full-appendage DARPA SUBOFF model (DTRC model 5470), a scale (λ = 0.535) semi-autonomous submarine free-running model (SFRM) was designed for testing its manoeuvrability and stability in the constrained water. Prior to the experimental tests of the SFRM, a six-degree-of-freedom (6-DOF) manoeuvre model with an autopilot system was developed by using logic operations in MATLAB. The SFRM’s attitude and its trim polygon were presented by coping with the changes in mass and trimming moment. By adopting a series of manoeuvring tests in empty tanks, the performances of the SFRM were introduced in cases of three sailing speeds. In addition, the PD controller was established by considering the simulation results of these manoeuvring tests. The optimal control gains with respect to each manoeuvring test can be calculated by using the PID tuner in MATLAB. Two sets of control gains derived from the optimal characteristics parameters were compared in order to decide on the most appropriate PD controller with the line-of-sight (LOS) guidance algorithm for the SFRM in the autopilot simulation. Eventually, the simulated trajectories and course angles of the SFRM would be illustrated in the post-processor based on the Cinema 4D modelling.

General Equations of a Helical Spring With a Cup Damper and Static Verification

1997 ◽  
Vol 119 (2) ◽  
pp. 319-326 ◽  
Author(s):  
Ming Hsun Wu ◽  
Jing Yuan Ho ◽  
Wensyang Hsu
Keyword(s):  
Experimental Data ◽  
Pitch Angle ◽  
Equations Of Motion ◽  
Maximum Error ◽  
Dynamic Equations ◽  
Helical Spring ◽  
Static Force ◽  
Static Verification ◽  
Simulation Results ◽  
Force Displacement

In this study, we derive the general equations of motion for the helical spring with a cup damper by considering the damper’s dilation and varying pitch angle of the helical spring. These dynamic equations are simplified to correlate with previous models. The static force-displacement relation is also derived. The extra stiffness due to the damper’s dilation considered in the force-displacement relation is the first such modeling in this area. In addition, a method is presented to predict the compressing spring’s coil close length and is then verified by experimental data. Moreover, the simulation results of the static force-displacement relation are found to correspond to the experimental data. The maximum error is around 0.6 percent.

Optimal Stabling of Attitude Maneuver for a Special Satellite With Reaction Wheel Actuators

2010 ◽  
Author(s):  
Seyed Hasan Miri Roknabadi ◽  
Mohamad Fakhari Mehrjardi ◽  
Mehran Mirshams
Keyword(s):  
Attitude Control ◽  
Equations Of Motion ◽  
Low Energy ◽  
Dynamic Equations ◽  
Satellite Motion ◽  
Reaction Wheel ◽  
State Equations ◽  
Time Consumption ◽  
Attitude Maneuver ◽  
Simulation Results

This paper presents an optimal attitude maneuver by Reaction Wheels to achieve desired attitude for a Satellite. At first, Dynamic Equations of motion for a satellite with just three Reaction Wheels of its active actuators are educed, and then State Equations of this system are obtained. An optimal attitude control with the LQR method has exerted for a distinct satellite by its Reaction Wheels. As a result simulation has presented an optimal effort by calculated Gain matrix to achieve desired attitude for chosen Satellite. It shows that satellite becomes stable in desired attitude with a low energy and time consumption. Furthermore equations derivation, coupling of electrical Reaction Wheel equations with dynamic equations of satellite motion, linearizes them and Reaction wheel saturation avoidance approaches are innovative. Simulation results, accuracy of achieving desired attitude and satellite stability support this statement.

Multibody Dynamics and Nonlinear Control of Flexible Space Structures

2004 ◽  
Vol 10 (11) ◽  
pp. 1639-1661 ◽  
Author(s):  
A. Suleman
Keyword(s):  
Nonlinear Control ◽  
Multibody Dynamics ◽  
Feedback Linearization ◽  
Equations Of Motion ◽  
Space Structures ◽  
Attitude Motion ◽  
Structural Flexibility ◽  
Large Space ◽  
Flexible Space Structures ◽  
Nonlinear Equations Of Motion

A multibody dynamics formulation for studying the response of large space structures with interconnected flexible bodies is presented. The use of system modes to model the structural flexibility results in a compact form of the nonlinear equations of motion. Next, the nonlinear control based feedback linearization technique is applied to effectively control the attitude motion of a flexible space platform. Using the original nonlinear dynamics of the multibody system, the controller determines the effort to effectively linearize the system and introduces a linear compensator to achieve the desired output in the presence of structural flexibility of the spacecraft.

scholarly journals Optimal Control of Holding Motion by Nonprehensile Two-Cooperative-Arm Robot

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Changan Jiang ◽  
Yuta Nakatomi ◽  
Satoshi Ueno
Keyword(s):  
Optimal Control ◽  
Dynamic Model ◽  
Nursing Care ◽  
Equations Of Motion ◽  
Viscoelastic Model ◽  
Normal Direction ◽  
Normal Forces ◽  
Robot Arms ◽  
Simulation Results ◽  
Optimal Regulator

Recently, more researchers have focused on nursing-care assistant robot and placed their hope on it to solve the shortage problem of the caregivers in hospital or nursing home. In this paper, a nonprehensile two-cooperative-arm robot is considered to realize holding motion to keep a two-rigid-link object (regarded as a care-receiver) stable on the robot arms. By applying Newton-Euler equations of motion, dynamic model of the object is obtained. In this model, for describing interaction behavior between object and robot arms in the normal direction, a viscoelastic model is employed to represent the normal forces. Considering existence of friction between object and robot arms, LuGre dynamic model is applied to describe the friction. Based on the obtained model, an optimal regulator is designed to control the holding motion of two-cooperative-arm robot. In order to verify the effectiveness of the proposed method, simulation results are shown.

scholarly journals Nonlinear Control based on Feedback Linearization for Double- Electromagnet Suspension System

1970 ◽  
Vol 108 (2) ◽  
pp. 85-90
Author(s):  
A. Maghsoudlou ◽  
R. Barzamini ◽  
K. D. Farahani
Keyword(s):  
Nonlinear Control ◽  
Feedback Linearization ◽  
Suspension System ◽  
Coupling Effects ◽  
Input And Output ◽  
Feedback Linearization Control ◽  
Measurement Noises ◽  
Simulation Results

In this paper a feedback linearization control for double electromagnet suspension system is presented that addresses the coupling effects between two groups of electromagnetic trains. The controller has been developed based on feedback linearization and some reasonable assumptions of nonlinear mathematical rules. The proposed method in tracking has a satisfying performance in presence of unknown changes in the mass. It also shows robustness against the presence of measurement noises because sensors in plant collect noise from the environment. The simulation results show the capability of the proposed algorithm in the presence of input and output perturbation. Ill. 13, bibl. 7 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.108.2.151

Euler–Lagrange as Pseudo-metric of the RRT algorithm for optimal-time trajectory of flight simulation model in high-density obstacle environment

Robotica ◽  
2015 ◽  
Vol 35 (5) ◽  
pp. 1138-1156 ◽  
Author(s):  
Mohammad Altaher ◽  
Omaima Nomir
Keyword(s):  
Equations Of Motion ◽  
Flight Simulation ◽  
Dynamic Equations ◽  
Optimal Time ◽  
Holonomic Constraints ◽  
Lagrange Formula ◽  
Path Constraints ◽  
Optimized Model ◽  
Simulation Results ◽  
Path Constraint

SUMMARYThis paper introduces a solution to the problem of steering an aerodynamical system, with non-holonomic constraints superimposed on dynamic equations of motion. The proposed approach is a dimensionality reduction of the Optimal Control Problem (OCP) with heavy path constraints to be solved by Rapidly-Exploring Random Tree (RRT) algorithm. In this research, we formulated and solved the OCP with Euler–Lagrange formula in order to find the optimal-time trajectory. The RRT constructs a non-collision path in static, high-dense obstacle environment (i.e. heavy path constraint). Based on a real-world aircraft model, our simulation results found the collision-free path and gave improvements of time and fuel consumption of the optimized Hamiltonian-based model over the original non-optimized model.

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