1,723,443 research outputs found
Control and Filtering for Discrete Linear Repetitive Processes with H infty and ell 2--ell infty Performance
No full textRepetitive processes are characterized by a series of sweeps, termed passes, through a set of dynamics defined over a finite duration known as the pass length. On each pass an output, termed the pass profile, is produced which acts as a forcing function on, and hence contributes to, the dynamics of the next pass profile. This can lead to oscillations which increase in amplitude in the pass to pass direction and cannot be controlled by standard control laws. Here we give new results on the design of physically based control laws for the sub-class of so-called discrete linear repetitive processes which arise in applications areas such as iterative learning control. The main contribution is to show how control law design can be undertaken within the framework of a general robust filtering problem with guaranteed levels of performance. In particular, we develop algorithms for the design of an H? and dynamic output feedback controller and filter which guarantees that the resulting controlled (filtering error) process, respectively, is stable along the pass and has prescribed disturbance attenuation performance as measured by and – norms
Comments on 'On the equivalence of causal LTI iterative learning control and feedback control
No full textThe area of Iterative Learning Control (ILC) now has a large and increasing body of research with an increasing number of applications (supported by a sizable number of actual experimental verification studies). The paper by Goldsmith (Automatica, 38, pp.~703-708) contains a number of assumptions and technical errors that invalidate its conclusion that normal feedback control is preferable to causal ILC, and the purpose of this note is to state the problems with this paper and clearly articulate the technical and practical validity of the ILC concept
Output Feedback Control of Discrete Linear Repetitive Processes
No full textRepetitive processes are a distinct class of 2D systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. Here we give new results on the relatively open problem of the design of physically based control laws using an LMI setting. These results are for the sub-class of so-called discrete linear repetitive processes which arise in applications areas such as iterative learning control
LQ performance bounds for adaptive output feedback controllers for functionally uncertain systems
No full textIterative learning control for spatio-temporal dynamics using Crank-Nicholson discretization
No full textIterative learning control is now well established for linear and nonlinear dynamics in terms of both the underlying theory and experimental application. This approach is specifically targeted at cases where the same operation is repeated over a finite duration with resetting between successive repetitions. Each repetition or pass is known as a trial and the key idea is to use information from previous trials to update the control input used on the current one with the aim of improving performance from trial-to-trial. In this paper, new results on ILC applied to systems that arise from discretization of bi-variate partial differential equations describing spatio-temporal systems or processes are developed. Theses are based on Crank-Nicholson discretization of the governing partial differential equation, resulting in an unconditionally numerically stable approximation of the dynamics. It is also shown that this setting allows the selection of a finite number of points for sensing and actuation. The resulting control laws can be computed using Linear Matrix Inequalities (LMIs). Finally, an illustrative example is given and areas for further research are discussed
On the Development of SCILAB Compatible Software for the Analysis and Control of Repetitive Processes
No full textIn this paper further results on the development of a SCILAB compatible software package for the analysis and control of repetitive processes is described. The core of the package consists of a simulation tool which enables the user to inspect the response of a given example to an input, design a control law for stability and/or performance, and also simulate the response of a controlled process to a specified reference signal
Poles and zeros – examples of the behavioral approach applied to discrete linear repetitive processes
No full textIn this paper the behavorial approach is applied to discrete linear repetitive processes, which are class of 2D systems of both systems theoretic and applications interest. The main results are on poles and zeros for these processes, which have exponential trajectory interpretations
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