Javier Moreno-Valenzuela

Bio: Javier Moreno-Valenzuela is an academic researcher from Instituto Politécnico Nacional. The author has contributed to research in topics: Control theory & Trajectory. The author has an hindex of 19, co-authored 94 publications receiving 1055 citations. Previous affiliations of Javier Moreno-Valenzuela include University of Liège & CINVESTAV.

Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking

Abstract: A novel proportional-integral-derivative (PID)-type motion controller for a quadrotor is introduced in this paper A rigorous analysis of the closed-loop system trajectories is provided, and gain tuning guidelines are discussed Real-time experimental results consisting of the implementation of a PID-based scheme, a sliding-mode controller, and the new scheme are given Gains are selected so that the three tested controllers present the same energy consumption In order to assess the robustness of the controllers tested, experiments are carried out in the presence of disturbances in one of the actuators Specifically, the disturbance consists in attenuating the force delivered Better tracking accuracy is obtained with the introduced nonlinear PID-type algorithm

A practical PID regulator with bounded torques for robot manipulators

Abstract: This paper proposes a saturated nonlinear PID regulator for industrial robot manipulators. Our controller considers the natural saturation problem given by the output of the control computer, the saturation phenomena of the internal PI velocity controller in the servo driver, and the actuator torque constraints of the robot manipulator. An approach based on the singular perturbations method is used to analyze the exponential stability of the closed-loop system. Experimental essays show the feasibility of the proposed controller. Furthermore, the theoretical results justify why the classical PID used in industrial robots preserves its exponential stability despite the saturation effects of the electronic control devices and the actuator torque constraints.

A New Nonlinear PI/PID Controller for Quadrotor Posture Regulation

Abstract: Based on the classic scheme of proportional , integral and derivative (PID) control, we present the design of a nonlinear controller, which aims to regulate the posture (position and orientation) of a 6 d.o.f. (degrees of freedom) aerial vehicle called Quadrotor. In particular, the Quadrotor horizontal position is controlled by PI actions, while the Quadrotor orientation and vertical position are controlled by PID algorithms. The controller shows robustness to aircraft systems effects, such as Coriolis forces and aerodynamic drag, although only the effect of gravitational forces is compensated. The controller performance is verified by numerical tests.

Adaptive Regulation of Vector-Controlled Induction Motors

Abstract: This paper addresses the speed and flux regulation of induction motors under the assumption that the motor parameters are poorly known. An adaptive passivity-based control is proposed that guarantees robust regulation as well as accurate estimation of the electrical parameters that govern the motor performance. This paper provides a local stability analysis of the adaptive scheme, which is illustrated by simulations and supported by a successful experimental validation on an industrial product.

Adaptive Control

Abstract: 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 Neural Impedance Control of a Robotic Manipulator With Input Saturation

Abstract: 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.

Modelling and Control of Robot Manipulators

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Dynamic analysis and PID control for a quadrotor

Abstract: 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.

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

Abstract: 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.