Seismological evidence for crustal-scale thrusting in the Zagros mountain belt (Iran)

International audienceCrustal receiver functions computed from the records of 45 temporary seismological stations installed on a 620-km long profile across central Zagros provide the first direct evidence for crustal thickening in this mountain belt. Due to a rather short 14-km average station spacing, the migrated section computed from radial receiver functions displays the Moho depth variations across the belt with good spatial resolution. From the coast of the Persian Gulf to 25 km southwest of the Main Zagros Thrust (MZT), the Moho is almost horizontal with slight depth variations around 45 km. Crustal thickness then increases abruptly to a maximum of ~70 km beneath the Sanandaj-Sirjan metamorphic zone, between 50 and 90 km northeast of the surface exposure of the MZT. Further northeast, the Moho depth decreases to ~42 km beneath the Urumieh-Dokhtar magmatic assemblage and the southern part of the Central Iranian micro-continent. The region of thickest crust is located ~75 km to the northeast of the Bouguer anomaly low at –220 mgals. Gravity modelling shows that the measured Moho depth variations can be reconciled with gravity observations by assuming that the crust of Zagros underthrusts the crust of central Iran along the MZT considered as a crustal-scale structure. This hypothesis is compatible with shortening estimates by balanced cross-sections of the Zagros folded belt, as well as with structural and petrological studies of the metamorphic Sanandaj-Sirjan zone

Challenges of Adaptive Control-Past, Permanent and Future

This paper reviews three different types of challenges to adaptive control. The first group comprises challenges met in the subject's development. They include difficulties associated with the MIT rule, bursting, the Rohr's counterexample and unplanned instability in iterative identification and control. An understanding of these phenomena and mitigating strategies are now available. The second group comprises difficulties that are intrinsic to virtually any adaptive control algorithm, and that have frequently been overlooked. For example, if a plant is unknown, and a control objective is set, the objective may in practical terms be unachievable, and any adaptive control algorithm needs to deal with that possibility. The third group comprises some issues to which researchers are currently devoting significant attention, including multiple model adaptive control and model-free design

Historical, Generic and Current Challenges of Adaptive Control

This paper reviews three different types of challenges to adaptive control. The first group comprises challenges met in the subject's development. They include difficulties associated with the MIT rule, bursting, the Rohr's counterexample and unplanned instability in iterative identification and control. An understanding of these phenomena and mitigating strategies are now available. The second group comprises difficulties that are intrinsic to virtually any adaptive control algorithm, and that have frequently been overlooked. For example, if a plant is unknown, and a control objective is set, the objective may in practical terms be unachievable, and any adaptive control algorithm needs to deal with that possibility. The third group comprises some issues to which researchers are currently devoting significant attention, including multiple model adaptive control and model free design

Stability and Performance Verification before switching in new controllers using closed-loop data

Consider an interconnection of an unknown or partially known linear plant and a known linear stabilizing controller, and assume that some knowledge of the closed-loop system is available. Suppose, on the basis of that knowledge, the use of a new controller appears attractive. We provide analysis and introduce novel tests utilizing a limited amount of experimental and possibly noisy data obtained from the existing closed-loop for verifying that the introduction of a proposed new controller will not only stabilize the plant but also provide assurance for the closed-loop performance before the insertion of a new controller. The importance of this capability arises in iterative identification and control algorithms, multiple-model adaptive control, and multi-controller adaptive switching

Unfalsified adaptive control: A new controller implementation and some remarks

The concept of unfalsified adaptive control using multiple controllers and switching ideas has been developed and extensively investigated over the past decade [1]-[16]. In this literature of unfalsified adaptive control, it is required that the controller set only contains linear, bi-proper minimum-phase controllers. In this note, we propose a controller implementation scheme which overcomes this restrictive assumption on the controller set though retaining linearity. Furthermore, we advocate caution in some circumstances where the unfalsified adaptive control algorithm actually connects up a destabilizing controller in the closed-loop for a long period of time, and explain how this phenomenon can arise

Practical Novel Tests for Ensuring Safe Adaptive Control

In this paper, we further illustrate the versatility and effectiveness of our novel tests for ensuring safe adaptive control in practice. The tests utilize a limited amount of experimental and possibly noisy data obtained from a closedloop-consisting of an existing known stabilizing controller connected to an unknown plant-to infer if the introduction of a prospective controller will stabilize the unknown plant. The need and importance of this arise in iterative identification and control algorithms, multiple-model adaptive control (MMAC), and multi-controller adaptive switching

An Η∞ model referencing design utilizing a two degree of freedom controller scheme

In this paper, we propose an ℋ∞ controller design method which Improves model referencing feature and extends the applicability of the Internal Model Control (IMC) design method to the generic class of LTI systems (SISO, MIMO, stable, unstable) by in

Improved robust performance in a system for automatic administration of a vasoactive drug

The problem of automatic administration of vasoactive drugs to regulate mean arterial pressure in surgical and postsurgical patients can be considered as a setpoint tracking problem involving a system which is characterised by significant modelling uncertainty in the form of uncertain parameters, unmodelled dynamics and disturbances. Yet, specific levels of performance are required and patient safety must be guaranteed. As part of the development process of a novel Multiple-Model Adaptive Control (MMAC) architecture for this application, we have adopted a mixed-μ synthesis approach to controller design. Simulation results show that the new controllers are capable of improved disturbance rejection and robustness even in the face of large system delays and parametric uncertainty