Results 151 to 160 of about 475,550 (200)
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1996
Abstract A theory of iterative learning control for refinement of motions of robotic systems is presented, together with simulation results. It is shown that the passivity of such non-linear mechanical systems plays a key role in the ability to acquire a desired and skilled movement through repeated practice.
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Abstract A theory of iterative learning control for refinement of motions of robotic systems is presented, together with simulation results. It is shown that the passivity of such non-linear mechanical systems plays a key role in the ability to acquire a desired and skilled movement through repeated practice.
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An iterative learning controller with initial state learning
IEEE Transactions on Automatic Control, 1999In iterative learning control (ILC), a common assumption is that the initial states in each repetitive operation should be inside a given ball centred at the desired initial states which may be unknown. This assumption is critical to the stability analysis, and the size of the ball will directly affect the final output trajectory tracking errors.
Chen, Y., Wen, C., Gong, Z., Sun, M.
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An iterative learning controller for nonholonomic robots
Proceedings of IEEE International Conference on Robotics and Automation, 2002We present an iterative learning controller for nonholonomic systems in chained form. The learning algorithm relies on the fact that chained-form systems are linear under piecewise-constant inputs. The proposed control scheme requires the execution of a small number of experiments in order to drive the system to the desired state in finite time, with ...
ORIOLO, Giuseppe +2 more
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2019
The chapter presents original research results in the area of nonlinear iterative-learning control. We propose a novel ILC scheme developed using neural networks. The following two cases are described: dynamic and static learning controllers and in both cases the controller is designed in such a way as to minimize the tracking error.
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The chapter presents original research results in the area of nonlinear iterative-learning control. We propose a novel ILC scheme developed using neural networks. The following two cases are described: dynamic and static learning controllers and in both cases the controller is designed in such a way as to minimize the tracking error.
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Adaptive iterative learning control
IEE Colloquium on Adaptive Control, 1996Describes the basic ideas underpinning the notion of iterative learning control (ILC) for systems where the experimental set-up permits the use of repetition to enable the controller to increase its accuracy in tracking of a specified set-point signal r(t).
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Hybrid iterative learning control
2017This chapter presents hybrid iterative learning control schemes with acceleration feedback for control of flexible manipulator systems. The learning schemes considered are PD-type, PI-type and PID-type. A collocated PD controller is considered for rigid-body motion control, and this is extended to incorporate noncollocated and iterative learning ...
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Iterative learning of impedance control
Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289), 2003This paper proposes an iterative learning control scheme for impedance control of robotic tasks when the tool endpoint covered by soft and deformable material presses a rigid object or environment at a prescribed periodic force pattern. To this end, an iterative learning control scheme for a class of linear dynamical systems with a negative feedback ...
null Pham Thuc Anh Nguyen +3 more
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Data-Driven Indirect Iterative Learning Control
IEEE Transactions on CyberneticsIn this work, a data-driven indirect iterative learning control (DD-iILC) is presented for a repetitive nonlinear system by taking a proportional-integral-derivative (PID) feedback control in the inner loop. A linear parametric iterative tuning algorithm for the set-point is developed from an ideal nonlinear learning function that exists in theory by ...
Ronghu Chi +3 more
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Universal adaptive iterative learning control
Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 2002This paper provides convergence/stability criteria for universal adaptive high-gain iterative learning control systems based on the use of the current trial feedback for a class of linear MIMO state space systems. Weak and strong (norm) convergence of the tracking error sequences {e/sub k/}/sub k/spl ges/0/ to zero in L/sub 2//sup m/(0,T) is analysed ...
D.H. Owens, G.S. Munde
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Predictive optimal iterative learning control
International Journal of Control, 1998A new optimization-based iterative learning control algorithm is proposed and its properties derived. An important characteristic of this algorithm is that it uses present and future predicted errors to compute the current control, in a similar manner to model-based predictive control using a receding horizon.
Amann, N, Owens, D H, Rogers, E
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