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1. An S-band Automatically Tunable Bandpass Filter Based on a Machine Learning Approach

   Adhikari, Pintu and (October 2021, 2021 IEEE 21st Annual Wireless and Microwave Technology Conference (WAMICON))

   This paper presents a novel automatic tuning mechanism that eliminates hand-tuning and is suitable for electronically-tunable microwave filters. The proposed method is based on a deep Q-learning approach using physics-based filter characteristic parameters like resonant frequency, bandwidth, insertion loss, and return loss. The whole tuning process is done automatically and does not require any pre-tuning or human expertise. Furthermore, unlike single-frequency post-production tuning techniques, the presented methodology is applicable to continuously-tunable filters covering a wide frequency range. This method is experimentally demonstrated on a 2-3.5 GHz evanescent-mode electronically-tunable bandpass filter. To the best of our knowledge, this is the first demonstration of such an automatic tuning mechanism where the user can specify any frequency of interest and the filter tunes automatically to that frequency within the entire operating range of the filter. 

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2. An Observer-Based Control for a Networked Control of Permanent Magnet Linear Motors under a False-Data-Injection Attack

   https://doi.org/10.1109/DSC61021.2023.10354110  

   Bonab, Parisa Ansari; Holland, James; Sargolzaei, Arman (November 2023, IEEE)

   In a centralized Networked Control System (NCS), agents share local data with the central processing unit that generates control commands for agents. The control center in an NCS receives information from the agents through a communication network and produces control commands for agents. Despite all of the advantages of an NCS, such as reduced design cost and simplicity, the integration of networked connectivity can expose the NCS to adversarial attacks, such as false data injection (FDI). In this paper, a novel control approach will be developed to mitigate the FDI attack’s effect and guarantee the control objective in a networked system of permanent magnet linear motors. To achieve this, a non-singular terminal sliding mode control will be designed using an observer to ensure the tracking objective. The extended state observer will estimate the state of the system and estimate the FDI attack in real time. The control center will produce a control signal which is robust to the FDI attack and any disturbance. A Lyapunov-based stability analysis will be used to prove the stability of the observer-based controller. A three-agent permanent magnet linear motor network is selected for the simulation to show the effectiveness of the proposed scheme. 

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3. Distributed Cooperative Kalman Filter Constrained by Discretized Poisson Equation for Mobile Sensor Networks

   https://doi.org/10.23919/ACC55779.2023.10156161  

   Zhang, Ziqiao; Mayberry, Scott T.; Wu, Wencen; Zhang, Fumin (May 2023, 2023 American Control Conference)

   This paper proposes cooperative Kalman filters for distributed mobile sensor networks where the mobile sensors are organized into cells that resemble a mesh grid to cover a spatial area. The mobile sensor networks are deployed to map an underlying spatial-temporal field modeled by the Poisson equation. After discretizing the Poisson equation with finite volume method, we found that the cooperative Kalman filters for the cells are subjected to a set of distributed constraints. The field value and gradient information at each cell center can be estimated by the constrained cooperative Kalman filter using measurements within each cell and information from neighboring cells. We also provide convergence analysis for the distributed constrained cooperative Kalman filter. Simulation results with a five cell network validates the proposed distributed filtering method. 

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4. Finite Dimensional Functional Observer Design for Parabolic Systems

   https://doi.org/10.1109/CDC45484.2021.9682848  

   Demetriou, Michael A.; Hu, Weiwei (December 2021, 2021 60th IEEE Conference on Decision and Control)

   This paper combines two control design aspects for a class of infinite dimensional systems, and each of the designs aims at significantly reducing the implementation complexity and computational load. A functional observer, and its extension of an unknown input functional observer, aims to reconstruct a functional of the infinite dimensional state. The resulting compensator only requires the solution to an operator Sylvester equation plus one differential equation for each dimension of the control signal, as opposed to an infinite dimensional filter evolution equation and an associated operator Riccati equation for the filter operator covariance. When the functional to be estimated coincides with the expression of a full state feedback control signal, then the functional observer becomes the minimum order compensator. When the parabolic system admits a decomposition whereby the system is decomposed into a lower finite dimensional subspace comprising the unstable eigenspectrum and an infinite stable subspace, then the functional observer-based compensator design becomes the minimum order compensator for the finite dimensional subsystem. This approach dramatically reduces the computation for solving the ARE needed for the full state controller and the associated Sylvester equation needed for the functional observer. Numerical results for a parabolic PDE in one and two spatial dimensions are included. 

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5. Effective seismic force retrieval from surface measurement for SH-wave reconstruction

   https://doi.org/10.1016/j.soildyn.2022.107682  

   Guidio, Bruno; Goh, Heedong; Jeong, Chanseok (February 2023, Soil Dynamics and Earthquake Engineering)

   We present a new method to obtain dynamic body force at virtual interfaces to reconstruct shear wave motions induced by a source outside a truncated computational domain. Specifically, a partial differential equation (PDE)-constrained optimization method is used to minimize the misfit between measured motions at a limited number of sensors on the ground surface and their counterparts reconstructed from optimized forces. Numerical results show that the optimized forces accurately reconstruct the targeted ground motions in the surface and the interior of the domain. The proposed optimization framework yields a particular force vector among other valid solutions allowed by the domain reduction method (DRM). Per this optimized or inverted force vector, the reconstructed wave field is identical to its reference counterpart in the domain of interest but may differ in the exterior domain from the reference one. However, we remark that the inverted solution is valid and introduce a simple post-process that can modify the solution to achieve an alternative force vector corresponding to the reference wave field. We also study the desired sensor spacing to accurately reconstruct the wave responses for a given dominant frequency of interest. We remark that the presented method is omnidirectionally applicable in terms of the incident angle of an incoming wave and is effective for any given material heterogeneity and geometry of layering of a reduced domain. The presented inversion method requires information on the wave speeds and dimensions of only a reduced domain. Namely, it does not need any informa- tion on the geophysical profile of an enlarged domain or a seismic source profile outside a reduced domain. Thus, the computational cost of the method is compact even though it leads to the high-fidelity reconstruction of wave re- sponse in the reduced domain, allowing for studying and predicting ground and structural responses using real seismic measurements. 

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