Tarak Damak

On trajectory tracking control for nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances

This paper studies the trajectory tracking control problem of mobile manipulators subject to nonholonomic constraints, operating in task space, with the presence of external torque disturbances and dynamic uncertainties. The proposed controls are robust to external torque disturbances and can overcome the effects of the unknown dynamic parameters. The stability of the closed-loop system and the asymptotic convergences of tracking errors are proved using Lyapunov synthesis. The proposed control strategies have been designed to drive the system motion converges to the desired manifold and, at the same time, guarantees the boundedness of all the closed-loop signals. Simulation results validate that the system trajectory converge to the desired one.

Comparison between a backstepping mode control and a sliding mode control for a boost DC-DC converter of a photovoltaic panel

This paper focuses on the development of renewable energy systems. The main goal is the optimal exploitation from photovoltaic panels. Therefore, two robust control laws will be applied on the DC-DC boost converter in order to maintain a robust output voltage regulation. The first part of this communication is devoted to the backstepping mode control. In the second part, we will present the sliding mode control. Finally, we will present simulations to illustrate the validity of the proposed approaches and to compare their performances.

Adaptive robust tracking control for mobile manipulators in the task‐space under uncertainties

Purpose – The purpose of this paper is to address the trajectory tracking control in task space of a non‐holonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm is robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. The system stability and the convergence of tracking errors to zero are rigorously proved using a Lyapunov theory.Design/methodology/approach – The proposed algorithm is derived based on the advantage of the robot regressor dynamics that express the highly non‐linear robot dynamics in a linear form in terms of the known and unknown robot parameters. The update law for the unknown dynamic parameters is obtained using Lyapunov theory.Findings – Simulation experiments show the effectiveness of the proposed robust adaptive based controller in comparison with a classical passivity based controller.Originality/value – The proposed adaptive approach is inte...

Higher Order Sliding Mode Control of Uncertain Robot Manipulators

This chapter deals with the tracking problem of robot manipulators. These systems are described by highly nonlinear and coupled equations. Higher order sliding mode controllers are then proposed to ensure stability and robustness of uncertain robot manipulators. The motivation for using high order sliding mode mainly relies on its appreciable features, such as high precision and elimination of chattering in addition that ensures the same performance of conventional sliding mode like robustness. In this chapter we propose two high order sliding mode controllers. The first guarantees a continuous control eliminating the chattering phenomenon. Instead of a regular control input, the derivative of the control input is used in the proposed control law. The discontinuity in the controller is made to act on the time derivative of the control input. The actual control signal obtained by integrating the derivative control signal is smooth and chattering free. The second controller is an adaptive version of high order sliding mode controller. The goal is to obtain a robust high order sliding mode adaptive gain control law to respect to uncertainties and perturbations without the knowledge of uncertainties/perturbations bound. The proposed controller ensures robustness, precision and smoothness of the control signal. The stability and the robustness of the proposed controllers can be easily verified by using the classical Lyapunov criterion. The proposed controllers are tested to a three-degree-of-freedom robot to prove their effectiveness.

Non linear controllers applied to a DC-DC boost converter

The regulation problem of the DC-DC boost converter is very complicated due to the non-minimum phase system character. In order to find a suitable controller for this kind of converters, we will compare the proposed sliding mode Controller (PSCM) with others non linear controllers such as : Generalized PI SMC, Classical SMC and Ramirez SMC, Backstepping Controller(BC) and Parallel Damped Passivity Based Controller (PDPBC).

Adaptive sliding-mode control of nonholonomic wheeled mobile robot

This paper designs an adaptive sliding mode dynamic controller for the trajectory tracking of wheeled mobile robot. First, a kinematic controller is introduced for the wheeled mobile robot. Then, the adaptive sliding mode dynamic controller (ASMDC) is proposed to make the real velocity of the wheeled mobile robot reach the desired velocity command, in presence of system uncertainties and disturbances. The convergence of the complete equations of motion of wheeled mobile robot is proved by the Lyapunov stability theory. Computer simulation results illustrate the effectiveness of the proposed controller.

Fault diagnosis and isolation of a complex system using a neural network observer

In this work, we use the approach based on neural observer in order to introduce the diagnosis of a non-linear system. The synthesis of such a trained specific observer using the back-propagation algorithm leads to an estimation study then a determination of fault diagnosis and isolation of single actuator fault based on residual generation. The robustness of the proposed observer is tested through a physical example. Finally, a comparison of observers’ performances will be interesting for judging the effectiveness of this approach. So, the obtained results will be compared to the sliding mode observer and the classic Luenberger observer.

Training a neural observer using a hybrid approach

In this work, we use the approach based on observers such as the neural observer in order to introduce the diagnosis of nonlinear systems. There are different techniques for training the neural networks. Among these techniques, we quote the backpropagation technique, the backpropagation technique with momentum and the hybrid one which is a mixture between the backpropagation technique and the sliding variable structure. The robustness of this kind of training for neural observer is tested through a physical example. The obtained results show that the third type of training is better than using a classic kind of training especially concerning the rapidity of convergence.

Dynamic redundancy resolution for mobile manipulators using position fuzzy controller

In this paper, we present a dynamic redundancy resolution technique for mobile manipulators using a position fuzzy controller. First, the dynamic model of the mobile manipulator in feasible motion space is given. Next, a control algorithm is proposed which resolve the redundancy by decoupling the motion of the system into the end-effector motion in the task space and an internal motion in the null space and controls them in prioritized basis with priority given to the primary task. In order to achieve a good end-effector trajectory tracking, a position fuzzy controller is used to provide the torques needed to move the end-effector along the desired trajectory. Simulation results are given to illustrate the coordination of two subsystems in executing the desired trajectories.

Dynamic redundancy resolution for mobile manipulators with joints velocity limits avoidance

In this paper, we present a dynamic redundancy resolution technique for mobile manipulator subject to joint velocity limits. First, the dynamic model of the mobile manipulator in feasible motion space is given. Next, a control algorithm is proposed which completely decouples the motion of the system into the end-effector motion in the task space and the internal motion in the null space and controls them in prioritized basis with priority given to the primary task space and enables the selection of characteristics in both subspaces separately. A special attention is given to the joints velocity limits avoidance where a normalized measure is proposed to solve problems inherent to velocity limits of the system. Simulation results are given to illustrate the coordination of two subsystems in executing the desired trajectory without violating the joint velocity limits.