Unknown System Dynamics Estimator for Motion Control of Nonlinear Robotic Systems

Na, Jing; Jing, Baorui; Huang, Yingbo; Gao, Guanbin; Zhang, Chao

doi:10.1109/tie.2019.2920604

Cited by 109 publications

(58 citation statements)

References 37 publications

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“…Similarly, Li et al [16] proposed an optimization-based dual Recurrent Neural Network (RNN) algorithm for controlling multiple manipulators simultaneously. Control algorithms based on Jacobian matrix estimation [31,32] and adaptive control are also proposed [33,34,35,36,37,38,39].…”

Section: Introductionmentioning

confidence: 99%

Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach

Khan

Chen

et al. 2020

Neurocomputing

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In this paper, we propose a topology of Recurrent Neural Network (RNN) based on a metaheuristic optimization algorithm for the tracking control of mobile-manipulator while enforcing nonholonomic constraints. Traditional approaches for tracking control of mobile robots usually require the computation of Jacobian-inverse or linearization of its mathematical model. The proposed algorithm uses a nature-inspired optimization approach to directly solve the nonlinear optimization problem without any further transformation. First, we formulate the tracking control as a constrained optimization problem. The optimization problem is formulated on position-level to avoid the computationally expensive Jacobian-inversion. The nonholonomic limitation is ensured by adding equality constraints to the formulated optimization problem. We then present the Beetle Antennae Olfactory Recurrent Neural Network (BAORNN) algorithm to solve the optimization problem e ciently using very few mathematical operations. We present a theoretical analysis of the proposed algorithm and show that its computational cost is linear with respect to the degree of freedoms (DOFs), i.e., O(m). Additionally, we also prove its stability and convergence. Extensive simulation results are prepared using a simulated model

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Section: Introductionmentioning

confidence: 99%

Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach

Khan

Chen

et al. 2020

Neurocomputing

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“…As long as the system remains on the sliding surface, the desired deactuation dynamics are produced. The nonlinear control term in the controller design is formulated such that it forces the system toward the sliding surface even in the presence of unknown model uncertainties and bounded external disturbances [34]. The convergence of the proposed controller is proved using the Lyapunov stability criterion and experimentally demonstrated using a soft robotic experimental platform [35]- [37].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots

Khan

2020

IEEE Access

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This paper proposes a novel active vibration damping mechanism for soft robots. In recent years, soft robots have gained increasing research attention for robotic researchers and industrial developers alike. Soft robots offer a significant number of advantages when it comes to the handling of fragile objects, clinical rehabilitation tasks, and human-machine interaction. Soft robots demonstrate a high degree of compliance and safety because of their inherent softness, achieving the same with rigid robots will require intricate controller design and sensing mechanisms. However, the most commonly used soft robots use pneumatic systems for actuation. These pneumatic soft robots undergo large amplitude vibrations when deactuated suddenly. These vibrations not only decrease the accuracy of these soft robots but also compromise their structural integrity, which results in a decrease in their useable lifespan. An active vibration damping mechanism is very much needed to increase the utility of soft robots in industrial applications. To accurately control the dynamic behavior of soft robots, we propose a sliding mode based controller with PID sliding surface. The proposed controller uses feedback error to define a PID sliding surface, and a nonlinear sliding mode controller works to keep the system attached to the sliding surface. The coefficients of the PID sliding surface determine the dynamic behavior of the soft robot. The performance of the proposed controller is verified by using a multi-chambered parallel soft robot. The experimental results demonstrate that the proposed controller can suppress vibration amplitude to a decidedly smaller range. INDEX TERMS Soft robot, sliding mode control, active damping, parallel-soft robot, multi-chambered soft robot.

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“…But to control designers, the control of a robot under a substantial payload variation is a formidable challenge. Even without any payload, a robot manipulator alone is already difficult to control owing to the strong nonlinearities and unmodeled dynamics [4], [5]. Introducing a substantial payload immediately increases the inertia matrix and the gravity torque, significantly changing robot dynamics behavior, and complicating its control [6], [7].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive PID Control for Robot Manipulators Under Substantial Payload Variations

Lee

Chang

et al. 2020

IEEE Access

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Significant payload variations often occur in many practical tasks for robotic applications. But its adequate control is a formidable challenge to control designers, and previous research works have exhibited either limited performance or noticeable difficulties in implementation. In this paper, we have proposed an adaptive PID control that is simple, model-free, and robust against payload variations. These advantages, already verified from the adaptive time-delay control (TDC), have been inherited to the proposed PID control through the equivalence relationship between the two controls. As a result, the proposed PID shares the simplicity, robustness, and the model free property, as well as the high levels of stability and performance with the adaptive TDC. In particular, the selection of its gains becomes especially simple and straightforward, while the adaptation becomes efficient under substantial payload variations. These positive attributes have been verified through simulations and experiments on robots under substantial payload variation. In particular, the proposed PID control was applied to the control of a WAM robot holding a baseball bat, with a result better than a standard PID control.INDEX TERMS Adaptive control, payload variations, PID control, robot manipulator, time-delay estimation.

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Unknown System Dynamics Estimator for Motion Control of Nonlinear Robotic Systems

Cited by 109 publications

References 37 publications

Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach

Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach

Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots

An Adaptive PID Control for Robot Manipulators Under Substantial Payload Variations

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