Robust adaptive command filtered control of a robotic manipulator with uncertain dynamic and joint space constraints

Robotica ◽  
2018 ◽  
Vol 36 (5) ◽  
pp. 767-786 ◽  
Author(s):  
Joseph Jean-Baptiste Mvogo Ahanda ◽  
Jean Bosco Mbede ◽  
Achille Melingui ◽  
Bernard Essimbi Zobo

SUMMARYThe problem of robust adaptive control of a robotic manipulator subjected to uncertain dynamics and joint space constraints is addressed in this paper. Command filters are used to overcome the time derivatives of virtual control, thus reducing the need for desired trajectory differentiations. A barrier Lyapunov function is used to deal with the joint space constraints. A robust adaptive support vector regression architecture is used to reduce filtering errors, approximation errors and handle dynamic uncertainties. The stability analysis of the closed-loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all signals of the closed-loop system are bounded. Simulations show the effectiveness of the proposed control strategy.

Robotica ◽  
2017 ◽  
Vol 36 (4) ◽  
pp. 516-534 ◽  
Author(s):  
Joseph Jean-Baptiste Mvogo Ahanda ◽  
Jean Bosco Mbede ◽  
Achille Melingui ◽  
Bernard Essimbi

SUMMARYThis study derives a robust adaptive control of electrically driven robot manipulators using a support vector regression (SVR)-based command filtered adaptive backstepping approach. The robot system is supposed to be subject to model uncertainties, neglected dynamics, and external disturbances. The command filtered backstepping algorithm is extended to the case of the robot manipulators. A robust term is added to the common adaptive SVR algorithm, to mitigate the effects of the SVR approximation error in the path tracking performance. The stability analysis of the closed loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all the signals in the closed loop system are bounded. Simulations show the effectiveness of the proposed control strategy.


Author(s):  
Shiming Duan ◽  
Jun Ni ◽  
A. Galip Ulsoy

Piecewise affine (PWA) systems belong to a subclass of switched systems and provide good flexibility and traceability for modeling a variety of nonlinear systems. In this paper, application of the PWA system framework to the modeling and control of an automotive all-wheel drive (AWD) clutch system is presented. The open-loop system is first modeled as a PWA system, followed by the design of a piecewise linear (i.e., switched) feedback controller. The stability of the closed-loop system, including model uncertainty and time delays, is examined using linear matrix inequalities based on Lyapunov theory. Finally, the responses of the closed-loop system under step and sine reference signals and temperature disturbance signals are simulated to illustrate the effectiveness of the design.


Robotica ◽  
2020 ◽  
pp. 1-20
Author(s):  
Roger Datouo ◽  
Joseph Jean-Baptiste Mvogo Ahanda ◽  
Achille Melingui ◽  
Frédéric Biya-Motto ◽  
Bernard Essimbi Zobo

SUMMARY The problem of finite-time tracking control for n-link flexible-joint robot manipulators is addressed. An adaptive fuzzy finite-time command-filtered backstepping control scheme is presented to solve the following problems: “explosion of terms” problem, finite-time stabilization of the closed-loop system, and the reduction of computational cost. To this end, new virtual adaptive control signals and new finite-time error compensation mechanism are constructed using inherent properties of robot manipulator systems. Based on the Lyapunov theory, the finite-time stabilization of the closed-loop system is proved. Simulation studies show the effectiveness of the proposed method.


Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2776 ◽  
Author(s):  
Kan Xie ◽  
Yue Lai ◽  
Weijun Li

In order to maintain robotic manipulators at a high level of performance, their controllers should be able to address nonlinearities in the closed-loop system, such as input nonlinearities. Meanwhile, computational efficiency is also required for real-time implementation. In this paper, an unknown input Bouc–Wen hysteresis control problem is investigated for robotic manipulators using adaptive control and a dynamical gain-based approach. The dynamics of hysteresis are modeled as an additional control unit in the closed-loop system and are integrated with the robotic manipulators. Two adaptive parameters are developed for improving the computational efficiency of the proposed control scheme, based on which the outputs of robotic manipulators are driven to track desired trajectories. Lyapunov theory is adopted to prove the effectiveness of the proposed method. Moreover, the tracking error is improved from ultimately bounded to asymptotic tracking compared to most of the existing results. This is of important significance to improve the control quality of robotic manipulators with unknown input Bouc–Wen hysteresis. Numerical examples including fixed-point and trajectory controls are provided to show the validity of our method.


Author(s):  
Saeed Zaare ◽  
Mohammad Reza Soltanpour

In this paper, an optimal robust adaptive fuzzy backstepping control is presented to the position control of the electro-hydraulic servo (EHS) system in the presence of structured and unstructured uncertainties. Initially, the robust control using the backstepping technique is presented to overcome the existing uncertainties in the dynamic equations. Mathematical proof demonstrates that the closed-loop system in the presence of uncertainties has a global asymptotic stability. Then, to overcome the chattering problem, a very simple fuzzy approximator is presented where it approximates the bounds of the uncertainties. Although the proposed robust fuzzy backstepping control has a desirable performance, it has no mathematical analysis to prove the stability of the closed-loop system. Therefore, to solve this problem, the proposed fuzzy approximator has been transformed into a one-law adaptive fuzzy approximator with a single-input single-output fuzzy rule. Mathematical analysis illustrates that the closed-loop system in the presence of uncertainties has a global asymptotic stability under the proposed robust adaptive fuzzy backstepping control. Furthermore, a novel modified harmony search algorithm (MHSA) has been developed, by using the original harmony search algorithm (OHSA) as an optimization technique, to achieve the optimal values of the membership functions and the control coefficients. Finally, a comparative study has been conducted between the proposed control scheme under the MHSA and the OHSA, and other existing advanced control approaches to verify the effectiveness of the proposed control. Results show that the proposed control scheme under the MHSA can suppress the chattering problem and reduce the disturbances effectively while ensuring that the performance is tracked.


2005 ◽  
Vol 128 (2) ◽  
pp. 453-457 ◽  
Author(s):  
R. Outbib ◽  
X. Dovifaaz ◽  
A. Rachid ◽  
M. Ouladsine

In this paper we present a theoretical strategy for diesel engine control. More precisely, we propose a new approach to control the speed of the engine using the fuel rate as the control law and we show how this approach can be used to control the opacity. We first establish a mathematical model that describes the behavior of the engine. Afterward, we propose a new nonlinear method to design a controller for a class of nonlinear systems. The proposed method, based on Lyapunov theory, is used to design a smooth feedback law that renders the closed-loop system asymptotically stable around a desired engine speed value. Finally, simulation results are proposed to highlight the performances of the closed-loop system.


2013 ◽  
Vol 20 (2) ◽  
pp. 297-308 ◽  
Author(s):  
Y.C. Ding ◽  
F.L. Weng ◽  
Z.A. Yu

The problem of robustly active vibration control for a class of earthquake-excited structural systems with time-delay and saturation in the control input channel and parameter uncertainties appearing in all the mass, damping and stiffness matrices is concerned in this paper. The objective of the designing controllers is to guarantee the robust stability of the closed-loop system and attenuate the disturbance from earthquake excitation. Firstly, by using the linear combination of some matrices to deal with the system's uncertainties, a new system uncertainties description, namely rank-1 uncertainty description, is presented. Then, by introducing a linear varying parameter, the input saturation model is described as a linear parameter varying model. Furthermore, based on parameter-dependent Lyapunov theory and linear matrix inequality (LMI) technique, the LMIs-based conditions for the closed-loop system to be stable are deduced. By solving those conditions, the controller, considering the actuator saturation, input delay and parameters uncertainties, is obtained. Finally, a three-storey linear building structure under earthquake excitation is considered and simulation results are given to show the effectiveness of the proposed controllers.


Author(s):  
M M Arefi ◽  
M R Jahed-Motlagh

In this paper, an adaptive robust stabilization algorithm is presented for a class of non-linear systems with mismatched uncertainties. In this regard, a new controller based on the Lyapunov theory is proposed in order to overcome the problem of stabilizing non-linear time-varying systems with mismatched uncertainties. This method is such that the stability of the closed-loop system is guaranteed in the absence of the triangularity assumption. The proposed approach leads to asymptotic convergence of the states of the closed-loop system to zero for unknown but bounded uncertainties. Subsequently, this method is modified so that all the signals in the closed-loop system are uniformly ultimately bounded. Eventually, numerical simulations support the effectiveness of the given algorithm.


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