Robust ILC design using Möbius transformations
نویسندگان
چکیده
Abstract: In this paper a general ILC algorithm is examined and it is found that the filters involved can be selected to satisfy frequency-wise uncertainty limits on the plant model. The probability of the plant model being at a given point in the uncertainty space is specified, and the filters are then chosen to maximise the convergence rate that can be expected in practice. The magnitude of the change in input over successive trials and the residual error have also been incorporated into the cost function. Experimental results are presented using a non-minimum phase test facility to show the effectiveness of the design method.
منابع مشابه
Möbius Transformations For Global Intrinsic Symmetry Analysis
The goal of our work is to develop an algorithm for automatic and robust detection of global intrinsic symmetries in 3D surface meshes. Our approach is based on two core observations. First, symmetry invariant point sets can be detected robustly using critical points of the Average Geodesic Distance (AGD) function. Second, intrinsic symmetries are self-isometries of surfaces and as such are con...
متن کاملl1-Optimal Robust Iterative Learning Controller Design
In this paper we consider the robust iterative learning control (ILC) design problem for SISO discretetime linear plants subject to unknown, bounded disturbances. Using the supervector formulation of ILC, we apply a Youla parameterization to pose a MIMO l1-optimal control problem. The problem is analyzed for three situations: (1) the case of arbitrary ILC controllers that use current iteration ...
متن کاملRobust iterative learning control with current feedback for uncertain linear systems
Considering an uncertain plant in iterative learning control (ILC), robust convergence and robust stability are important issues. Since the feedback controller robustly stabilizes the uncertain plant and has an e ect on the convergence, it plays as signi® cant a role as the learning controller does in the ILC system. To deal with both convergence and stability in ILC, we take account of an ILC...
متن کاملRobust Iterative Learning Control for Linear Systems Subject to Time-Invariant Parametric Uncertainties and Repetitive Disturbances169 Robust Iterative Learning Control for Linear Systems Subject to Time-Invariant Parametric Uncertainties and Repetitive Disturbances
This paper presents the design of a robust Iterative Learning Control (ILC) algorithm for linear systems in the presence of parametric uncertainties and repetitive disturbances. The robust ILC design is formulated as a min-max problem with a quadratic performance index subjected to constraints of the control input. Employing Lagrange duality, we can reformulate the robust ILC design as a convex...
متن کاملRobust ILC design with application to stroke rehabilitation
Iterative learning control (ILC) is a design technique which can achieve accurate tracking by learning over repeated task attempts. However, long-term stability remains a critical limitation to widespread application, and to-date robustness analysis has overwhelmingly considered structured uncertainties. This paper substantially expands the scope of existing ILC robustness analysis by addressin...
متن کامل