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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. Efficient Filters for Geometric Intersection Computations using GPU

   Liu, Yiming; Puri, Satish (November 2020, ACM SIGSPATIAL 2020)

   null (Ed.)

   Geometric intersection algorithms are fundamental in spatial analysis in Geographic Information System (GIS). Applying high performance computing to perform geometric intersection on huge amount of spatial data to get real-time results is necessary. Given two input geometries (polygon or polyline) of a candidate pair, we introduce a new two-step geospatial filter that first creates sketches of the geometries and uses it to detect workload and then refines the sketches by the common areas of sketches to decrease the overall computations in the refine phase. We call this filter PolySketch-based CMBR (PSCMBR) filter. We show the application of this filter in speeding-up line segment intersections (LSI) reporting task that is a basic computation in a variety of geospatial applications like polygon overlay and spatial join. We also developed a parallel PolySketch-based PNP filter to perform PNP tests on GPU which reduces computational workload in PNP tests. Finally, we integrated these new filters to the hierarchical filter and refinement (HiFiRe) system to solve geometric intersection problem. We have implemented the new filter and refine system on GPU using CUDA. The new filters introduced in this paper reduce more computational workload when compared to existing filters. As a result, we get on average 7.96X speedup compared to our prior version of HiFiRe system. 

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