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Reproducible, robust robot control is particularly challenging at the microscale, where lesser understood surface forces, such as friction, dominate volumetric forces, such as magnetic attraction. In such an environment, an adaptive (or “uncalibrated”) controller which can dynamically adjust to changes in the operation environment is essential. This paper describes an uncalibrated controller utilizing...
Reinforcement learning has become more and more popular in robotics for acquiring feedback controllers. Many approaches aim for learning a controller from scratch, i.e., data-driven without any modeling of the physical plant. However, stability properties of the closed loop are often not considered, or established only a-posteriori or ad hoc. We propose to employ reinforcement learning in the context...
Visual servoing is a useful approach for robot control. It is specially attractive when the control objective can be stated directly in image coordinates like in point-to-point regulation. The adaptive control is a technique very used in robot manipulators due to uncertainty in the dynamic model and when is combined with vision allows to handle uncertainty in the camera parameters. In this paper,...
A novel non-smooth adaptive robot control is proposed in light of general error decimal power law and RBF neural networks. The corresponding stability analysis is presented to lay a foundation to the safe operation in practice. An illustrative example is used to validate the effectiveness of the proposed approach.
The cable-driven mechanism is usually used in robotic systems for the efficient transmission of forces or torques from actuators to the end-effector. However, the control design is challenging for these systems due to the cable compliance and transmission elasticity. In this paper, adaptive control in a cascaded structure is designed for the trajectory tracking of a cable driven robot arm. The desired...
In this paper, we presents a new NPID-type iterative learning control law with two nonlinear integral action for a class of nonlinear systems, denoted NP-D-INPD, which is composed by the linear combination of the derivative control mode, nonlinear control mode shaped by a nonlinear function of error, and two nonlinear integral control modes driven by a nonlinear function of error and a nonlinear differential...
In this paper, an adaptive Jacobian tracking control of robot manipulators is presented. The proposed controller is based on the inverse robot manipulator dynamics and estimated uncertainty which can compensate for the uncertain parameters and external disturbances. Using the Lyapunov approach, the paper incorporates sliding mode control to enhance the asymptotic stability that shows the tracking...
In this paper, we presents a new nonlinear iterative learning control law for a class of nonlinear systems, denoted NP-D-INP-D, which is composed by limiting the action of error in PID learning law, that is, use a bounded nonlinear function of error instead of error, and adding a differential feedback in the integrator of PID learning law to inject the suited damping. By using Bellman-Gronwall lemma,...
Recently, biologically inspired approaches have received much attention for robot control. A typical example of them is control of rhythmic behaviors by Central Pattern Generator (CPG). However, this control has a problem that there are few theories to determine parameters of CPG. For this reason, they are determined experimentally. In this paper, we propose a combination method of Genetic Algorithm...
The following topics are dealt with: identification and estimation; manufacturing system; automation; mobile robot; mobile navigation; fire fighting robot; sensor; biorobotics; medical robot; artificial neural network; sensing application; model predictive control; steel-making industry; service robot; field robot; fuzzy system; process control; adaptive control; robust control; power system; assistive...
This paper deals with the problem of optimizing a fuzzy self-tuning PID controller for robot manipulators. Fuzzy PID controllers have been developed and applied in many fields in the last fifteen years. However, there is no systematic method to design Membership Functions (MFs) for these controllers. We propose a simple method based on Genetic Algorithms (GA) to find optimal input and output MFs of...
In this paper, we presents a new class of iterative learning control law for a class of nonlinear systems, denoted PD-IPD, which is composed by adding a derivative term in the integrator of PID learning control law. By using Bellman-Gronwall lemma, the simple explicit conditions on the learning gains to ensure convergence are provided in the sense of Lambda norm. An attractive feature of PD-IPD learning...
In this paper, a new iterative learning algorithm is proposed for repetitive nonlinear systems. The control system employs a combination of state feedback and iterative learning control (ILC) in which the coefficients of states are learned similar to ILC methods. The control system is in a closed loop format both in iteration domain (because of ILC) and in time domain (because of feedback control)...
In this paper, a robust-adaptive controller is developed for trajectory tracking of two rigid-link electrically-driven (RLED) robot manipulators carrying a rigid object. First, the dynamic model of the cooperative robots is derived. This model is written in a combined form such that the forces exerted by the object on the manipulators are not explicitly appeared in the dynamic model. A robust-adaptive...
Under the condition that the base of a robot manipulator has motion disturbance, the control of the end-effector target is difficult. In this paper, we show a method for robot control under base motion disturbance and load change with passivity-based adaptive control and to compensate viscous and coulomb friction. We insert target in cartesian space and calculate the inverse kinematics. Then the trajectory...
To resolve the problem of trajectory tracking of robot which have uncertain parameters and many uncertain ingredients. In high precise control, feedforward control can improve the tracking performance of system, this text present a kind of PD controller with feedforward based on adaptive theory. And by MATLAB simulation, this method is effective.
This paper presents the tuning and implementation of a computationally efficient adaptive predictive control algorithm for robotic utility. The controller addresses the need for practical, computationally efficient, robust real-time adaptive control for multivariable robotic systems. It exploits a special matrix representation to obtain substantial reductions in the computational expense relative...
The modified transpose Jacobian (MTJ) algorithm has been proposed, based on an approximated feedback linearization approach, in which there is no need to a priori knowledge of the plant dynamics. In this paper, a Learning-based modified transpose Jacobian (LMTJ) control algorithm is presented for trajectory tracking of robotic manipulators in an iterative operation mode. In this new control method,...
Position control of expedition robots are considered. The robots are controlled to follow pre-determined paths via fixed way-points. The speed and heading are controlled to follow reference values calculated from the next way point and current position. Hybrid control is used for speed loop and heading loop, respectively. Depending on the parameter change of speed and heading model due to unexpected...
Adaptive fuzzy controllers are potential candidates for controlling robot arms. However, traditional fuzzy controllers suffer from the rule explosion phenomenon. We propose here a hierarchical scheme to implement the fuzzy system and consequently relax the rule explosion problem. Furthermore, since payloads are normally varying, robotic models are uncertain. We propose a fuzzy-logic based dynamic...
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