Implementation of Adaptive Techniques for Motion Control of Robotic Manipulators

1988 ◽  
Vol 110 (1) ◽  
pp. 62-69 ◽  
Author(s):  
M. Tomizuka ◽  
R. Horowitz ◽  
G. Anwar ◽  
Y. L. Jia
Keyword(s):  
Adaptive Control ◽  
Industrial Robot ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Test Stand ◽  
Experimental Results ◽  
Direct Drive ◽  
Adaptive Controllers ◽  
Friction Forces ◽  
Digital Implementation

This paper is concerned with the digital implementation and experimental evaluation of two adaptive controllers for robotic manipulators. The first is a continuous time model reference adaptive controller, and the second is a discrete time adaptive controller. The primary purpose of these adaptive controllers is to compensate for inertial variations due to changes in configuration and payload, as well as disturbances, such as Coulomb friction and/or gravitational forces. Experimental results are obtained from a laboratory test stand, which emulates an one-axis direct drive robot arm with variable inertia, as well as a Toshiba TSR-500V industrial robot. Experimental results from the test stand indicate that these adaptive control schemes are promising for the control of direct drive robot arms. Friction forces arising from the harmonic gear of the Toshiba robot were detrimental if not properly compensated. Because of a high gearing ratio, the advantage of adaptive control for the Toshiba arm could be shown only by detuning the controller.

scholarly journals A New No Equilibrium Fractional Order Chaotic System, Dynamical Investigation, Synchronization, and Its Digital Implementation

Inventions ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 49
Author(s):  
Zain-Aldeen S. A. Rahman ◽  
Basil H. Jasim ◽  
Yasir I. A. Al-Yasir ◽  
Raed A. Abd-Alhameed ◽  
Bilal Naji Alhasnawi
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Chaotic System ◽  
Real World ◽  
Experimental Results ◽  
Chaotic Attractors ◽  
State Variables ◽  
Digital Implementation ◽  
Dynamical Behaviors ◽  
Real World Applications

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.

Adaptive Control of a Sliding Seat Using Magnetorheological Energy Absorbers

2010 ◽  
Author(s):  
Min Mao ◽  
Norman M. Wereley ◽  
Alan L. Browne
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Adaptive Controller ◽  
Degree Of Freedom ◽  
Lumped Mass ◽  
Adaptive Controllers ◽  
Bingham Number ◽  
Control Objective ◽  
Payload Mass ◽  
Energy Absorbers

Feasibility of a sliding seat utilizing adaptive control of a magnetorheological (MR) energy absorber (MREA) to minimize loads imparted to a payload mass in a ground vehicle for frontal impact speeds as high as 7 m/s (15.7 mph) is investigated. The crash pulse for a given impact speed was assumed to be a rectangular deceleration pulse having a prescribed magnitude and duration. The adaptive control objective is to bring the payload (occupant plus seat) mass to a stop using the available stroke, while simultaneously accommodating changes in impact velocity and occupant mass ranging from a 5th percentile female to a 95th percentile male. The payload is first treated as a single-degree-of-freedom (SDOF) rigid lumped mass, and two adaptive control algorithms are developed: (1) constant Bingham number control, and (2) constant force control. To explore the effects of occupant compliance on adaptive controller performance, a multi-degree-of-freedom (MDOF) lumped mass biodynamic occupant model was integrated with the seat mass. The same controllers were used for both the SDOF and MDOF cases based on SDOF controller analysis because the biodynamic degrees of freedom are neither controllable nor observable. The designed adaptive controllers successfully controlled load-stroke profiles to bring payload mass to rest in the available stroke and reduced payload decelerations. Analysis showed extensive coupling between the seat structures and occupant biodynamic response, although minor adjustments to the control gains enabled full use of the available stroke.

Comparative experiments with a multiple model based adaptive controller for a SCARA type direct drive manipulator

Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 721-729 ◽  
Author(s):  
M. Kemal Ciliz ◽  
M. Ömer Tuncay
Keyword(s):  
Adaptive Control ◽  
Nonlinear Effects ◽  
Adaptive Controller ◽  
Control Algorithms ◽  
Robot Arm ◽  
Multiple Model ◽  
Direct Drive ◽  
Test Bed ◽  
Efficient Test ◽  
Control Scheme

In this paper, different adaptive control algorithms will be experimentally tested on a two axis SCARA type direct drive robot arm, and the performance of these algorithms will be compared. Being a direct drive system, the nonlinear effects, arising from the dynamics of the manipulator under high velocities, are directly reflected in the control of the manipulator. This makes the manipulator a more efficient test bed for testing the efficiency of the proposed adaptive schemes. In the experiments, we used fast trajectories rather than slow ones to observe how the proposed controllers compensate the dynamic nonlinear effects of manipulator dynamics. We will test some known adaptive control algorithms given in the literature along with our proposed adaptive control scheme which makes use of multiple models.

Adaptive Control of Nanowires Motion Using Electric Fields in Fluid Suspension

2019 ◽  
Author(s):  
Juan Wu ◽  
Kaiyan Yu
Keyword(s):  
Adaptive Control ◽  
Electric Fields ◽  
Adaptive Controller ◽  
Experimental Results ◽  
Parametric Uncertainties ◽  
Control Scheme ◽  
Complex Characterization ◽  
Adaptive Control Scheme

Abstract Automated, highly precise manipulation of nanowires and nanotubes is essential to achieve scalable nanomanufacturing. However, nanowires exhibit uncontrolled variations in their structures or compositions that can limit their functions and properties. In this paper, we present an adaptive controller for the simultaneous manipulation of multiple nanowires using electric fields. We then prove its stability in the presence of parametric uncertainties. Without complex characterization of each nanowire’s mobility, the nanowires can be steered to achieve precisely controlled positions. Simulation and experimental results confirm the proposed adaptive control scheme precisely, independently, and simultaneously manipulates the motion of multiple nanowires.

Hybrid fuzzy direct/indirect adaptive controller for uncertain nonlinear systems

2020 ◽  
Vol 42 (15) ◽  
pp. 3012-3023
Author(s):  
Youssouf Bibi ◽  
Omar Bouhali ◽  
Tarek Bouktir
Keyword(s):  
Fuzzy Logic ◽  
Adaptive Control ◽  
Nonlinear Systems ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Fuzzy Neural Networks ◽  
Uncertain Nonlinear Systems ◽  
Adaptive Controllers ◽  
Direct Adaptive Control ◽  
Fuzzy Neural

This paper describes a new approach to adaptive control of uncertain nonlinear systems. A fuzzy logic controller is used to combine both direct and indirect methods. Based on the fuzzy neural networks, the plant unknown nonlinear functions are estimated, and then combined to form the indirect control law. In parallel, another fuzzy neural network approximates the direct adaptive control. According to the modelling error and its derivatives, the fuzzy logic controller modulates between direct and indirect adaptive controllers. The global stability of the overall system is shown by constructing a Lyapunov function. The simulation results show that within this scheme, the control objectives can be achieved with a fast convergence and optimal control for different dynamic regimes.

Experimental results for output feedback adaptive robot control

Robotica ◽  
2006 ◽  
Vol 24 (6) ◽  
pp. 727-738 ◽  
Author(s):  
John M. Daly ◽  
Howard M. Schwartz
Keyword(s):  
Adaptive Control ◽  
Feedback Control ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Robotic Manipulators ◽  
High Gain ◽  
Experimental Results ◽  
Position Information ◽  
High Gain Observer ◽  
Adaptive Output Feedback Control

This paper examines three methods of adaptive output feedback control for robotic manipulators. Implementing output feedback control allows use of only the position information, which can be measured quite accurately. Velocity and acceleration measurements can get corrupted by noise. A method proposed by K. W. Lee and H. K. Khalil [Adaptive output feedback control of robot manipulators using high-gain observer, Int. J. Control, 6, 869–886 (1997)] using a high-gain observer, one proposed by J. J. Craig, P. Hsu and S. S. Sastry [Adaptive control of mechanical manipulators, Int. J. Robot. Res., 6(2), 16–27 (1987)] with the addition of a linear observer that we propose, and a method proposed by R. Gourdeau and H. M. Schwartz [Adaptive control of robotic manipulators: Experimental results, Proceedings of the 1991 IEEE International Conference on Robotics and Automation (Apr. 1991) pp. 8–15] using an Extended Kalman Filter are examined. The methods are implemented in simulation and experimentally on a direct-drive robot. The performance of each of the algorithms is compared.

Experimental Validation of an Adaptive Controller for Manipulators on a Dynamic Platform

Robotica ◽  
2020 ◽  
pp. 1-24
Author(s):  
Andres Rodriguez Reina ◽  
Kim-Doang Nguyen ◽  
Harry Dankowicz
Keyword(s):  
Hardware Implementation ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Experimental Results ◽  
Moving Platforms ◽  
Control Framework ◽  
Theoretical Predictions ◽  
Time Formulation ◽  
Adaptive Control Strategy ◽  
Insight Into

SUMMARY This paper reports on laboratory and field experimental results for controlled robotic manipulators operating on moving platforms with unmodeled dynamics. The aim is to validate theoretical predictions for the dependence on control parameters of an adaptive control strategy. In addition, the results provide insight into different discretizations of the continuous-time formulation, suggesting the most suitable discretization scheme for hardware implementation. The second set of experimental results, obtained from an implementation of the control framework for synchronization and consensus in networks of robotic manipulators, similarly validate theoretical predictions on the sensitivity to network communication delays.

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