PI output feedback control of differential linear repetitive processes

Repetitive 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. These are for the sub-class of so-called differential linear repetitive processes which arise in applications areas such as iterative learning control. They show how a form of proportional-integral (PI) control based only on process outputs can be designed to give stability plus performance and disturbance rejection

<i>H</i>₂ and mixed <i>H</i>₂/<i>H</i>_∞ Stabilization and Disturbance Attenuation for Differential Linear Repetitive Processes

Repetitive processes are a distinct class of two-dimensional systems (i.e., information propagation in two independent directions) of both systems theoretic and applications interest. A systems theory for them cannot be obtained by direct extension of existing techniques from standard (termed 1-D here) or, in many cases, two-dimensional (2-D) systems theory. Here, we give new results towards the development of such a theory in H2 and mixed H2/H∞ settings. These results are for the sub-class of so-called differential linear repetitive processes and focus on the fundamental problems of stabilization and disturbance attenuation

Elucidating the role of DEPTOR in Alzheimer's disease

This article has been made available through the Brunel Open Access Publishing Fund.The mammalian or mechanistic target of rapamycin (mTOR) is a Ser/Thr protein kinase that, in response to nutrient stimulation, regulates cellular growth, proliferation, survival, protein synthesis and gene transcription. It has also been implicated in Alzheimer's disease (AD) with neuronal cells and hippocampal slices of AD transgenic mice experiencing dysregulated mTOR and synaptic plasticity in response to treatment with the toxic amyloid β (Aβ1-42) peptide, which has been implicated in AD. DEP domain-containing mTOR-interacting protein (DEPTOR) is a protein which can bind to mTOR and cause its inhibition, and functions as a regulatory protein of mTOR to control its activity. The inhibition of mTOR has been shown to have a neuroprotective effect; in an animal model, it was shown to protect against Aβ-induced neurotoxicity. In the present study, to investigate to role of DEPTOR in a model of AD, we neuronally differentiated the SH-SY5Y cell line and examined the effects of treatment with an Aβ42 peptide, thus mimicking plaque formation. This resulted in a significant increase in mTOR and a significant decrease in DEPTOR expression compared to the unstimulated controls. Moreover, to the best of our knowledge, we demonstrate for the first time a reduction in the protein level of DEPTOR in the precentral gyrus, postcentral gyrus and occipital lobe of a brain with AD compared to a normal control, as well as a significant reduction in DEPTOR expression in samples from late-onset AD (LOAD) compared to early-onset familial AD (EOFAD). The reduction in DEPTOR expression in cases of AD compared to healthy controls can lead to an augmentation of mTOR signalling, leading to Aβ accumulation, which in turn leads to a further reduction in DEPTOR expression. This results in the accumulation of amyloid plaque, shifting the balance from neuroprotection to neurodegeneration

Optimal control of non-stationary differential linear repetitive processes

Differential repetitive processes are a distinct class of continuousdiscrete 2D linear systems of both systems theoretic and applications interest. The feature which makes them distinct from other classes of such systems is the fact that information propagation in one of the two independent directions only occurs over a finite interval. Applications areas include iterative learning control and iterative solution algorithms for classes of dynamic nonlinear optimal control problems based on the maximum principle, and the modelling of numerous industrial processes such as metal rolling, and long-wall cutting etc. The new results in is paper solve a general optimal problem in the presence of non-stationary dynamics

On the Development of SCILAB Compatible Software for the Analysis and Control of Repetitive Processes

In 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

LMI based Stability and Stabilization of Second-order Linear Repetitive Processes

This paper develops new results on the stability and control of a class of linear repetitive processes described by a second-order matrix discrete or differential equation. These are developed by transformation of the secondorder dynamics to those of an equivalent first-order descriptor state-space model, thus avoiding the need to invert a possibly ill-conditioned leading coefficient matrix in the original model

On control laws for discrete linear repetitive processes with dynamic boundary conditions

Repetitive 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 in the sequence of pass profiles produced which increase in amplitude in the pass-to-pass direction and cannot be controlled by application of standard control laws. Here we give new results on the design of physically based control laws for so-called discrete linear repetitive processes which arise in applications areas such as iterative learning control

PACOSS program overview and status

Many future civilian and military large space structures (LSS) will have as performance objectives stringent pointing accuracies, short settling times, relatively fast response requirements, or combinations thereof. Many of these structures will be large, light weight, and will exhibit high structural modal density at low frequency and within the control bandwidth. Although it is possible in principle to achieve structural vibration control through purely active means, experience with complex structures has shown that the realities of plant model inaccuracies and sensor/actuator dynamics frequently combine to produce substandard performance. A more desirable approach is to apply passive damping technology to reduce the active control burden. Development of the technology to apply this strategy is the objective of the PACOSS (Passive and Active Control OF Space Structures) program. A key element in the PACOSS program is the Representative System Article (RSA). The RSA is a generic paper system that serves as a testbed for damping and controls studies. It also serves as a basis for design of the smaller Dynamic Test Article (DTA), a hardware testbed for the laboratory validation of analysis and design practices developed under PACOSS

On controllability and control laws for discrete linear repetitive processes

Repetitive 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 the direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. This article develops significant new results on the relationships between one physically motivated concept of controllability for the so-called discrete linear repetitive processes and the structure and design of control laws, including the case when disturbances are present

On the Control of Distributed Parameter Systems using a Multidimensional Systems Setting

The unique characteristic of a repetitive process is a series of sweeps, termed passes, through a set of dynamics defined over a finite duration with resetting before the start of the each new one. 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 leads to the possibility that the output, i.e. the sequence of pass profiles, will contain oscillations which increase in amplitude in the pass-to-pass direction. Such behavior cannot be controlled by standard linear systems approach and instead they must be treated as a multidimensional system, i.e. information propagation in more than one independent direction. Physical examples of such processes include long-wall coal cutting and metal rolling. In this paper, stability analysis and control systems design algorithms are developed for a model where a plane, or rectangle, of information is propagated in the passto- pass direction. The possible use of these in the control of distributed parameter systems is then described using a fourthorder wavefront equation