An approach to the dynamic modeling and sliding mode control of the constrained robot

Shi, Heng; Liang, Yanbing; Liu, Zhaohui

doi:10.1177/1687814017690470

Cited by 20 publications

(19 citation statements)

References 23 publications

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“…e parameter values used in the adaptive backstepping sliding mode control system are λ � diag [5,5], k 1 � diag[50, 50], h � diag [3,3], and the external disturbance is added by a pulse signal ϕ � 0.5δ(t) in 6 s, which is used to verify the robustness and stability of the two-link robotic manipulator system. e schematic for backstepping algorithm by using Matlab @ software is shown in Figure 3, and the schematic for the proposed control strategy is shown in Figure 4.…”

Section: Simulation and Discussionmentioning

confidence: 99%

“…e dynamic parameters which describe the dynamic model are important for the control algorithms, effective simulation results, and accurate trajectory tracking algorithms. Dynamic equation of the robotic manipulator withn-DOF has been characterized in many literature studies [1][2][3][4][5][6][7][8][9][10][11] as follows:…”

Section: Description Of Link Parameters Of Robotic Manipulatormentioning

confidence: 99%

“…e first stage of trajectory tracking is to establish the precise mathematical model of the robotic manipulator. However, the nonlinear part of the dynamic model of the robotic manipulator is ignored in many literatures [1][2][3][4][5] or parameter identification by many approaches [6][7][8]; even the torque in the joint space and the moment of inertia were ignored in [9]. By calculating kinetic energy, potential energy, and generalized force, the Lagrange equation was utilized to build the dynamic equation for robotic manipulator [10,11].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Zhu

Puchen

et al. 2020

Complexity

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To achieve precise trajectory tracking of robotic manipulators in complex environment, the precise dynamic model, parameters identification, nonlinear characteristics, and disturbances are the factors that should be solved. Although parameters identification and adaptive estimate method were proposed for robotic control in many literature studies, the essential factors, such as coupling and friction, are rarely mentioned as it is difficult to build the precise dynamic model of the robotic manipulator. An adaptive backstepping sliding mode control is proposed to solve the precise trajectory tracking under external disturbances with complex environment, and the dynamic response characteristics of a two-link robotic manipulator are described in this paper. First, the Lagrange kinetic method is used to derive the precise dynamic model which includes the nonlinear factor with friction and coupling. Moreover, the dynamic model of two-link robotic manipulator is built. Second, the estimate function for the nonlinear part is selected, and backstepping algorithm is used for analyzing the stabilities of the sliding mode controller by using Lyapunov theory. Furthermore, the convergence of the proposed controller is verified subject to the external disturbance. At last, numerical simulation results are reported to demonstrate the effectiveness of the proposed method.

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Section: Simulation and Discussionmentioning

confidence: 99%

Section: Description Of Link Parameters Of Robotic Manipulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Zhu

Puchen

et al. 2020

Complexity

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“…According to the dynamic equation of the manipulator established, the detailed matrix representations 27 of the 2-DOF constrained manipulator in Figure 1…”

Section: Simulated Examplementioning

confidence: 99%

A reduced-order approach to the adaptive fuzzy sliding mode control of the constrained manipulator

Liang

Shi

Tian

2018

Advances in Mechanical Engineering

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A reduced-order approach to the adaptive fuzzy sliding mode control of the constrained manipulator is proposed. Based on the Udwadia–Kalaba motion constraint equation, the dynamic equation of the constrained manipulator with both ideal and non-ideal constraints is obtained. Considering the uncertainty of the terminal non-ideal constrained force and the chattering phenomenon of sliding mode control, the adaptive fuzzy and the sliding mode control method are combined to control the constrained manipulator. Because the system is constrained, the model order reduction method is innovatively used in the control algorithm. The stability of the system is proved by Lyapunov theorem. For demonstrating the effectiveness of the control algorithm, the 2-degree-of-freedom manipulator is taken as the research object. Finally, the high-precision control of the manipulator is achieved and the chattering phenomenon caused by the sliding mode control is weakened.

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“…In this way, sliding mode control (SMC) is one of the most known robust controls in literature. 6–8 This theory is extensively adopted due to its computational simplicity and its good transient performances. A large number of results focusing on sliding mode control for robots and in some cases combined with fuzzy or neuro-fuzzy approaches are proposed.…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithm-based multi-objective design of optimal discrete sliding mode approach for trajectory tracking of nonlinear systems

Benamor

Boukadida

Messaoud

2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this paper, a novel multi-objective design of optimal control for robotic manipulators is considered. Generally, robots are known by their highly nonlinearities, unmodeled dynamics, and uncertainties. In order to design an optimal control law, based on the linear quadratic regulator, the robotic system is described as a linear time varying model. The compensation of both disturbances and uncertainties is ensured by the integral sliding mode control. The problem of deciding the optimal configuration of the linear quadratic regulator controller is considered as an optimization problem, which can be solved by the application of genetic algorithm. The main contribution of this paper is to consider a multi-objective optimization problem, which aims to minimize not only the chattering phenomenon but also other control performances including the rise time, the settling-time, the steady-state error and the overshoot. For that, a novel dynamically aggregated objective function is proposed. As a result, a set of nondominated optimal solutions are provided to the designer and then he selects the most preferable alternative. To demonstrate the efficacy and to show complete performance of the new controller, two nonlinear systems are treated in this paper: firstly, a selective compliance assembly robot arm robot is considered. The results show that the manipulator tracing performance is considerably improved with the proposed control scheme. Secondly, the proposed genetic algorithm-based linear quadratic regulator control strategy is applied for pitch and yaw axes control of two-degrees-of-freedom laboratory helicopter workstation, which is a highly nonlinear and unstable system. Experimental results substantiate that the weights optimized using genetic algorithm, result in not only reduced tracking error but also improved tracking response with reduced oscillations.

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An approach to the dynamic modeling and sliding mode control of the constrained robot

Cited by 20 publications

References 23 publications

Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

A reduced-order approach to the adaptive fuzzy sliding mode control of the constrained manipulator

Genetic algorithm-based multi-objective design of optimal discrete sliding mode approach for trajectory tracking of nonlinear systems

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