Synthesis Design and Analysis of a Hybrid Controller for Robotic Arms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Adaptive Controller ◽  
Convergence Speed ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

In this paper, a hybrid controller for robotic arms is proposed and designed by combining a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the model reference adaptive controller and the PID+MRAC hybrid controller for 1-DOF and 2-DOF manipulators are compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+MRAC controllers are better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

Design, analysis and modelling of a hybrid controller for serial robotic manipulators

Robotica ◽  
2016 ◽  
Vol 35 (9) ◽  
pp. 1888-1905 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Model Reference ◽  
Control Approach ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

SUMMARYWhen the end-effector of a robotic arm grasps different payload masses, the output of joint motion will vary. By using a model reference adaptive control approach, the payload variation effect can be solved. This paper describes the design for a hybrid controller for serial robotic manipulators by combining a PID controller and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators is compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+ MRAC controllers is better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

Analysis and a Case Study of Model Reference Adaptive Control for Robotic Mechanisms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Adaptive Control ◽  
Robotic Manipulators ◽  
Model Reference Adaptive Control ◽  
Future Research ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Effect Model ◽  
Model Reference Adaptive

Motion control accuracy of robotic manipulators affects the overall robotic system performance. When the end-effector grasps different payloads, the joint motion of robotic manipulators will vary depending on the different payload masses. Traditional controllers have the problem of not being able to compensate the payload variation effect. Model reference adaptive control has been proposed to address the above problem. This paper discusses the model reference adaptive control of robotic manipulators initially raised by Roberto Horowitz and its associated development by other authors. A case study for a hybrid controller, which is derived from the model reference adaptive control system, is presented. Very few recent papers can be found in the area of model reference adaptive control of robotic manipulators, and this study can provide a guideline for future research in the direction of model reference adaptive control for robotic arms.

Design of a Control System for Serial Mechanisms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Control System ◽  
Dynamic Equation ◽  
Degrees Of Freedom ◽  
Nonlinear Term ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Hybrid Controller ◽  
Speed Performance ◽  
Convergence Performance ◽  
Model Reference Adaptive

A hybrid control system for multi degrees of freedom robotic manipulator is designed by integrating a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. For the 1-DOF link, because the inertia matrices and nonlinear term of the dynamic equation are constant, we can directly combine the PID and MRAC controller to design the PID+MRAC controller. However, for the more than 1-DOF link case, it is no longer applicable because the inertia matrices and nonlinear term of the dynamic equation are not constant. By using an improved adaptive algorithm and structure, and by combining the PID and improved MRAC controllers, a controller is designed for the more than 1-DOF link case. The convergence performance of the PID controller, MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators are compared.

PSO Tuned PID-Based Model Reference Adaptive Controller for Coupled Tank System

2014 ◽  
Vol 626 ◽  
pp. 167-171 ◽  
Author(s):  
D. Jeraldin Auxillia ◽  
T. Anitta
Keyword(s):  
Pid Controller ◽  
Environmental Changes ◽  
Pso Algorithm ◽  
Adaptive Controller ◽  
Nonlinear Processes ◽  
Process Industries ◽  
Model Reference ◽  
Effective Performance ◽  
Tank System ◽  
Model Reference Adaptive

In process industries control of nonlinear processes like level process is a common problem. For these nonlinear processes, to have a good performance even in the presence of environmental changes, the controller must have the ability to adopt changes in plant dynamics. So a Model Reference Adaptive Control (MRAC) based on PID controller is designed. Main objective of this work is to design PID-MRAC to include adaptiveness and to give good steady-state and transient performance for coupled tank system both with interaction and without interaction. A Particle Swarm Optimization (PSO) algorithm is used to fine tune the PID controller parameters. Simulations are done to show the effective performance of PID-MRAC compared to simple MRAC applied to couple tank system.

The development of a model reference adaptive controller to control the knee joint of paraplegics

1991 ◽  
Vol 36 (6) ◽  
pp. 683-691 ◽  
Author(s):  
M.S. Hatwell ◽  
B.J. Oderkerk ◽  
C.A. Sacher ◽  
G.F. Inbar
Keyword(s):  
Knee Joint ◽  
Adaptive Controller ◽  
Model Reference ◽  
Model Reference Adaptive

Evaluation of P-Q Controllers for an Injection Moulding Machine

2000 ◽  
Author(s):  
Paul K. Guerrier ◽  
Kevin A. Edge
Keyword(s):  
Injection Moulding ◽  
Adaptive Controller ◽  
Pi Controller ◽  
Hardware In The Loop ◽  
Model Reference ◽  
Industry Standard ◽  
Moulding Machine ◽  
Single Controller ◽  
Pressure Controller ◽  
Model Reference Adaptive

Abstract There are a number of problems surrounding traditional velocity and pressure controllers used on injection moulding machines. Injection moulding machines are also very expensive and full scale testing is often not appropriate at the beginning of new controller evaluation. This paper presents results for a half scale ‘hardware-in-the-loop’ load emulation of the filling and packing phases of injection moulding, suitable for controller evaluation. The problems linked to the current industry standard velocity and pressure controller are discussed along with alternative strategies. Schemes including single controller fuzzy logic and neural network solutions are discussed and ruled out in favour of ones containing separate velocity and pressure controllers. Results for a model reference adaptive pressure controller are presented and compared with those obtained using a closed loop PI controller experimentally and in simulation. Experimentally the model reference adaptive controller outperforms the PI controller but does suffer from gain drift.

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