This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

In this paper, adaptive impedance control is developed for an ${n}$ -link robotic manipulator with input saturation by employing neural networks. Both uncertainties and input saturation are considered in the tracking control design. In order to approximate the system uncertainties, we introduce a radial basis function neural network controller, and the input saturation is handled by designing an auxiliary system. By using Lyapunov’s method, we design adaptive neural impedance controllers. Both state and output feedbacks are constructed. To verify the proposed control, extensive simulations are conducted.

Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation

Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will concern you to try reading modelling and control of robot manipulators as one of the reading material to finish quickly.

Modelling and Control of Robot Manipulators

In order to analyze the dynamic characteristics and PID controller performance of a quadrotor, this paper firstly describes the architecture of the quadrotor and analyzes the dynamic model of it. Then, based on the classic scheme of PID control, this paper designs a controller, which aims to regulate the posture (position and orientation) of the 6 d.o.f. quadrotor. Thirdly, the dynamic model is implemented in Matlab/Simulink simulation, and the PID control parameters are obtained according to the simulation results. Finally, a quadrotor with PID controllers is designed and made. In order to do the experiment, a flying experiment for the quadrotor has been done. The results of flying experiment show that the PID controllers robustly stabilize the quadrotor.

Dynamic analysis and PID control for a quadrotor

For parameter identifications of robot systems, most existing works have focused on the estimation veracity, but few works of literature are concerned with the convergence speed. In this paper, we developed a robot control/identification scheme to identify the unknown robot kinematic and dynamic parameters with enhanced convergence rate. Superior to the traditional methods, the information of parameter estimation error was properly integrated into the proposed identification algorithm, such that enhanced estimation performance was achieved. Besides, the Newton–Euler (NE) method was used to build the robot dynamic model, where a singular value decomposition-based model reduction method was designed to remedy the potential singularity problems of the NE regressor. Moreover, an interval excitation condition was employed to relax the requirement of persistent excitation condition for the kinematic estimation. By using the Lyapunov synthesis, explicit analysis of the convergence rate of the tracking errors and the estimated parameters were performed. Simulation studies were conducted to show the accurate and fast convergence of the proposed finite-time (FT) identification algorithm based on a 7-DOF arm of Baxter robot.

Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence

In this paper, a new control algorithm for operational space trajectory tracking control of robot arms is introduced. The new algorithm does not require velocity measurement and is based on (1) a primary controller which incorporates an algorithm to obtain synthesized velocity from joint position measurements and (2) a secondary controller which computes the desired joint acceleration and velocity required to achieve operational space motion control. The theory of singularly perturbed systems is crucial for the analysis of the closed-loop system trajectories. In addition, the practical viability of the proposed algorithm is explored through real-time experiments in a two degrees-of-freedom horizontal planar direct-drive arm.

Operational space trajectory tracking control of robot manipulators endowed with a primary controller of synthetic joint velocity

This article addresses the joint position control of torque-driven robot manipulators under actuators subject to torque saturation. Robots having viscous friction, but without gravity vector, are c...

https://journals.sagepub.com/doi/pdf/10.1177/1687814016628492

A family of nonlinear PID-like regulators for a class of torque-driven robot manipulators equipped with torque-constrained actuators:

In this paper, a novel adaptive controller for quadrotor position and orientation trajectory tracking is introduced. By taking into account the coupling between the position and the orientation dynamics, an adaptive scheme based on an accurate parameterization of the model-based feedforward compensation is presented. The adaptation update laws for the adaptation parameters are designed on Lyapunov’s theory so that the stability of the state space origin of the error dynamics is guaranteed. Barbalat’s lemma ensures convergence of the tracking errors and bounding of the adaptation parameters. The extensive real-time experimental results show the practical viability of the proposed scheme. More specifically, the performance of the proposed controller is compared with an adaptive controller taken from the literature and the non-adaptive version of the proposed controller. Better results are obtained with the novel adaptive approach.

/pdf/adaptive-control-for-quadrotor-trajectory-tracking-with-5glt4ipzlx.pdf

Adaptive Control for Quadrotor Trajectory Tracking With Accurate Parametrization

A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller.

/pdf/adaptive-neural-network-motion-control-of-manipulators-with-1jgoel4vte.pdf

Javier Moreno-Valenzuela

Papers

Operational space trajectory tracking control of robot manipulators endowed with a primary controller of synthetic joint velocity

A family of nonlinear PID-like regulators for a class of torque-driven robot manipulators equipped with torque-constrained actuators:

Adaptive Control for Quadrotor Trajectory Tracking With Accurate Parametrization

Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations

On parameter identification of the Furuta pendulum