In this paper,a novel D-type iterative learning control(ILC)law is proposed for discrete-time antilinear systems.This D-type control law is different from the previous linear(nonlinear)D-type ILC law.The main feature ...In this paper,a novel D-type iterative learning control(ILC)law is proposed for discrete-time antilinear systems.This D-type control law is different from the previous linear(nonlinear)D-type ILC law.The main feature is that we take the conjugate of the(t+1)-th error to construct the proposed controller.The convergence proofs are given for their corresponding ILC schemes.展开更多
This paper presents a model-free adaptive iterative learning control(ILC)scheme called a proportional-type ILC scheme for non-linear systems.The obvious characteristic of the proposed ILC scheme is that we can easily ...This paper presents a model-free adaptive iterative learning control(ILC)scheme called a proportional-type ILC scheme for non-linear systems.The obvious characteristic of the proposed ILC scheme is that we can easily finish the ILC task just utilising the Lipschitz constant of the system.In the proposed ILC scheme,the time-vary learning gain can be produced merely by input and output(I/O)measurements.Moreover,the convergence conclusion can be expressed by the ranges of the pseudo-partial derivative and the learning gain.In actual operation,a reasonable and useful convergence condition by a constant is also provided for selection.At last,the effectiveness of the proposed ILC scheme is shown by simulations.展开更多
文摘In this paper,a novel D-type iterative learning control(ILC)law is proposed for discrete-time antilinear systems.This D-type control law is different from the previous linear(nonlinear)D-type ILC law.The main feature is that we take the conjugate of the(t+1)-th error to construct the proposed controller.The convergence proofs are given for their corresponding ILC schemes.
文摘This paper presents a model-free adaptive iterative learning control(ILC)scheme called a proportional-type ILC scheme for non-linear systems.The obvious characteristic of the proposed ILC scheme is that we can easily finish the ILC task just utilising the Lipschitz constant of the system.In the proposed ILC scheme,the time-vary learning gain can be produced merely by input and output(I/O)measurements.Moreover,the convergence conclusion can be expressed by the ranges of the pseudo-partial derivative and the learning gain.In actual operation,a reasonable and useful convergence condition by a constant is also provided for selection.At last,the effectiveness of the proposed ILC scheme is shown by simulations.