A Heuristic Study of Relegation of Control in Constrained Robotic Systems

1987 ◽  
Vol 109 (3) ◽  
pp. 224-231 ◽  
Author(s):  
H. Hemami ◽  
C. Wongchaisuwat ◽  
J. L. Brinker
Keyword(s):  
Computer Simulation ◽  
Control Problem ◽  
Control Strategy ◽  
Digital Computer ◽  
Robotic Systems ◽  
Independent Control ◽  
Mechanical Coupling ◽  
Heuristic Study ◽  
Separate Control ◽  
Planar Robot

A major control problem in the robotic field is the simultaneous and independent control of constrained trajectories and forces of constraint. The trajectories and the forces are related through the mechanical structure of the system. The task of the controller is to influence the mechanical coupling and allow separate control of the trajectories and the forces. A feasible control strategy is by relegation of control to the state or to the input. Relegation by inputs implies assigning the control of trajectories and forces to independent groups of inputs. In this paper, exact and approximate input relegation strategies are investigated. The effectiveness of the input relegation strategy is tested by digital computer simulation of a three link planar robot in a periodic rubbing maneuver.

Adaptive sliding tracking control for nonlinear uncertain robotic systems with unknown actuator nonlinearities

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Shubo Liu ◽  
Guoquan Liu ◽  
Shengbiao Wu
Keyword(s):  
Control Problem ◽  
Prior Knowledge ◽  
Control Strategy ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Robotic Systems ◽  
Actuator Nonlinearities ◽  
Simulation Results

Abstract This study is concerned with the tracking control problem for nonlinear uncertain robotic systems in the presence of unknown actuator nonlinearities. A novel adaptive sliding controller is designed based on a robust disturbance observer without any prior knowledge of actuator nonlinearities and system dynamics. The proposed control strategy can guarantee that the tracking error eventually converges to an arbitrarily small neighborhood of zero. Simulation results are included to demonstrate the effectiveness and superiority of the proposed strategy.

Road Feel Design for Vehicle Steer-by-Wire System Based on Joystick

2013 ◽  
Vol 336-338 ◽  
pp. 734-737
Author(s):  
Hong Yu Zheng ◽  
Ya Ning Han ◽  
Chang Fu Zong
Keyword(s):  
Computer Simulation ◽  
Control Strategy ◽  
Vehicle Speed ◽  
Control Module ◽  
Matlab Simulink ◽  
The Road ◽  
Steering Feel ◽  
Steer By Wire ◽  
Simulation Results ◽  
Wire System

In order to solve the problem of road feel feedback of vehicle steer-by-wire (SBW) system based on joystick, a road feel control strategy was established to analyze the road feel theory of traditional steer system, which included return, assist and damp control module. By verifying the computer simulation results with the control strategy from software of CarSim and Matlab/Simulink, it shows that the proposed strategy can effective get road feel in different vehicle speed conditions and could improve the vehicle maneuverability to achieve desired steering feel by different drivers.

Nonlinear Stochastic Optimal Control of MDOF Partially Observable Linear Systems Excited by Combined Harmonic and Wide-Band Noises

2019 ◽  
Vol 19 (03) ◽  
pp. 1950019 ◽  
Author(s):  
R. C. Hu ◽  
X. F. Wang ◽  
X. D. Gu ◽  
R. H. Huan
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Control Problem ◽  
Linear Systems ◽  
Control Strategy ◽  
Stochastic Optimal Control ◽  
Wide Band ◽  
Dynamic Programming Principle ◽  
Stochastic Dynamic ◽  
Partially Observable

In this paper, nonlinear stochastic optimal control of multi-degree-of-freedom (MDOF) partially observable linear systems subjected to combined harmonic and wide-band random excitations is investigated. Based on the separation principle, the control problem of a partially observable system is converted into a completely observable one. The dynamic programming equation for the completely observable control problem is then set up based on the stochastic averaging method and stochastic dynamic programming principle, from which the nonlinear optimal control law is derived. To illustrate the feasibility and efficiency of the proposed control strategy, the responses of the uncontrolled and optimal controlled systems are respectively obtained by solving the associated Fokker–Planck–Kolmogorov (FPK) equation. Numerical results show the proposed control strategy can dramatically reduce the response of stochastic systems subjected to both harmonic and wide-band random excitations.

Separate Control Strategy for a Biomimetic Gliding Robotic Fish

2021 ◽  
pp. 1-10
Author(s):  
Huijie Dong ◽  
Zhengxing Wu ◽  
Pengfei Zhang ◽  
Jian Wang ◽  
Min Tan ◽  
...  
Keyword(s):  
Control Strategy ◽  
Robotic Fish ◽  
Separate Control

Observer-based robust control for flexible-joint robot manipulators: A state-dependent Riccati equation-based approach

2020 ◽  
Vol 42 (16) ◽  
pp. 3135-3155
Author(s):  
Neda Nasiri ◽  
Ahmad Fakharian ◽  
Mohammad Bagher Menhaj
Keyword(s):  
Robust Control ◽  
Control Problem ◽  
Riccati Equation ◽  
Power Transmission ◽  
Control Method ◽  
Main Idea ◽  
Robotic Systems ◽  
Flexible Joint ◽  
State Dependent ◽  
Highly Nonlinear

In this paper, the robust control problem is tackled by employing the state-dependent Riccati equation (SDRE) for uncertain systems with unmeasurable states subject to mismatched time-varying disturbances. The proposed observer-based robust (OBR) controller is applied to two highly nonlinear, coupled and large robotic systems: namely a manipulator presenting joint flexibility due to deformation of the power transmission elements between the actuator and the robot known as flexible-joint robot (FJR) and also an FJR incorporating geared permanent magnet DC motor dynamics in its dynamic model called electrical flexible-joint robot (EFJR). A novel state-dependent coefficient (SDC) form is introduced for uncertain EFJRs. Rather than coping with the OBR control problem for such complex uncertain robotic systems, the main idea is to solve an equivalent nonlinear optimal control problem where the uncertainty and disturbance bounds are incorporated in the performance index. The stability proof is presented. Solving the complicated robust control problem for FJRs and EFJRs subject to uncertainty and disturbances via a simple and flexible nonlinear optimal approach and no need of state measurement are the main advantages of the proposed control method. Finally, simulation results are included to verify the efficiency and superiority of the control scheme.

scholarly journals Fuzzy-Approximation-Based Novel Back-Stepping Control of Flexible Air-Breathing Hypersonic Vehicles with Nonaffine Models

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Xingge Li ◽  
Gang Li
Keyword(s):  
Control Problem ◽  
Control Strategy ◽  
Hypersonic Vehicle ◽  
Hypersonic Vehicles ◽  
Input Constraints ◽  
Air Breathing ◽  
Fuzzy Approximation ◽  
Low Pass ◽  
Back Stepping Control ◽  
Low Pass Filters

This article investigates a novel fuzzy-approximation-based nonaffine control strategy for a flexible air-breathing hypersonic vehicle (FHV). Firstly, the nonaffine models are decomposed into an altitude subsystem and a velocity subsystem, and the nonaffine dynamics of the subsystems are processed by using low-pass filters. For the unknown functions and uncertainties in each subsystem, fuzzy approximators are used to approximate the total uncertainties, and norm estimation approach is introduced to reduce the computational complexity of the algorithm. Aiming at the saturation problem of actuator, a saturation auxiliary system is designed to transform the original control problem with input constraints into a new control problem without input constraints. Finally, the superiority of the proposed method is verified by simulation.

Sign in / Sign up

Export Citation Format

Share Document