pwc-archive/papers-with-abstracts huggingface dataset:
DENT-DDSP: Data-efficient noisy speech generator using differentiable digital signal processors for explicit distortion modelling and noise-robust speech recognition
Authors: Z. Guo, C. Chen, E. S. Chng
Date: 2022-08-01 00:00:00
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Robust Speech Recognition, speech-recognition, Speech Recognition

The performances of automatic speech recognition (ASR) systems degrade drastically under noisy conditions. Explicit distortion modelling (EDM), as a feature compensation step, is able to enhance ASR systems under such conditions by simulating the in-domain noisy speeches from the clean counterparts. Yet, existing distortion models are either non-trainable or unexplainable and often lack controllability and generalization ability. In this paper, we propose a fully explainable and controllable model: DENT-DDSP to achieve EDM. DENT-DDSP utilizes novel differentiable digital signal processing (DDSP) components and requires only 10 seconds of training data to achieve high fidelity. The experiment shows that the simulated noisy data from DENT-DDSP achieves the highest simulation fidelity compared to other baseline models in terms of multi-scale spectral loss (MSSL). Moreover, to validate whether the data simulated by DENT-DDSP are able to replace the scarce in-domain noisy data in the noise-robust ASR tasks, several downstream ASR models with the same architecture are trained using the simulated data and the real data. The experiment shows that the model trained with the simulated noisy data from DENT-DDSP achieves similar performances to the benchmark with a 2.7\% difference in terms of word error rate (WER). The code of the model is released online.
Information-Aware Guidance for Magnetic Anomaly based Navigation
Authors: J. Humberto Ramos, Jaejeong Shin, Kyle Volle, Paul Buzaud, Kevin Brink, Prashant Ganesh
Date: 2022-08-01 00:00:00
Tasks: Autonomous Vehicles, Decision Making

In the absence of an absolute positioning system, such as GPS, autonomous vehicles are subject to accumulation of positional error which can interfere with reliable performance. Improved navigational accuracy without GPS enables vehicles to achieve a higher degree of autonomy and reliability, both in terms of decision making and safety. This paper details the use of two navigation systems for autonomous agents using magnetic field anomalies to localize themselves within a map; both techniques use the information content in the environment in distinct ways and are aimed at reducing the localization uncertainty. The first method is based on a nonlinear observability metric of the vehicle model, while the second is an information theory based technique which minimizes the expected entropy of the system. These conditions are used to design guidance laws that minimize the localization uncertainty and are verified both in simulation and hardware experiments are presented for the observability approach.
Event-triggered Consensus Control of Heterogeneous Multi-agent Systems: Model- and Data-based Analysis
Authors: Xin Wang, Jian Sun, Gang Wang, Jie Chen
Date: 2022-08-01 00:00:00

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme. A dynamic periodic transmission protocol is developed to significantly alleviate the transmission frequency and computational burden, where the followers can interact locally with each other approaching the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived in form of linear matrix inequalities (LMIs), as well as a design method for obtaining the distributed controllers and event-triggering parameters. Upon collecting noise-corrupted state-input measurements during open-loop operation, a data-driven leader-following MAS representation is presented, and employed to solve the data-driven consensus control problem without requiring any knowledge of the agents' models. This result is then extended to the case of guaranteeing an $\mathcal{H}_{\infty}$ performance. A simulation example is finally given to corroborate the efficacy of the proposed distributed event-triggering scheme in cutting off data transmissions and the data-driven design method.
Iterative shaping of optical potentials for one-dimensional Bose-Einstein condensates
Authors: Andreas Deutschmann-Olek, Mohammadamin Tajik, Martino Calzavara, Jörg Schmiedmayer, Tommaso Calarco, Andreas Kugi
Date: 2022-08-01 00:00:00

The ability to manipulate clouds of ultra-cold atoms is crucial for modern experiments on quantum manybody systems and quantum thermodynamics as well as future metrological applications of Bose-Einstein condensate. While optical manipulation offers almost arbitrary flexibility, the precise control of the resulting dipole potentials and the mitigation of unwanted disturbances is quite involved and only heuristic algorithms with rather slow convergence rates are available up to now. This paper thus suggests the application of iterative learning control (ILC) methods to generate fine-tuned effective potentials in the presence of uncertainties and external disturbances. Therefore, the given problem is reformulated to obtain a one-dimensional tracking problem by using a quasicontinuous input mapping which can be treated by established ILC methods. Finally, the performance of the proposed concept is illustrated in a simulation scenario.
A sensitivity-based approach to optimal sensor selection for process networks
Authors: Siyu Liu, Xunyuan Yin, Zhichao Pan, Jinfeng Liu
Date: 2022-08-01 00:00:00
Tasks: Chemical Process, Sensitivity, State Estimation

Sensor selection is critical for state estimation, control and monitoring of nonlinear processes. However, evaluating the performance of each possible combination of $m$ out of $n$ sensors is impractical unless $m$ and $n$ are small. In this paper, we propose a sensitivity-based approach to determine the minimum number of sensors and their optimal locations for state estimation. The local sensitivity matrix of the measured outputs to initial states is used as a measure of the observability. The minimum number of sensors is determined in a way such that the local sensitivity matrix is full column rank. The subset of sensors that satisfies the full-rank condition and provides the maximum degree of observability is considered as the optimal sensor placement. Successive orthogonalization of the sensitivity matrix is conducted in the proposed approach to significantly reduce the computational complexity in selecting the sensors. To validate the effectiveness of the proposed method, it is applied to two processes including a chemical process consisting of four continuous stirred-tank reactors and a wastewater treatment plant. In both cases, the proposed approach can obtain the optimal sensor subsets.
NFT Hydroponic Control Using Mamdani Fuzzy Inference System
Authors: Indra Agustian, Bagus Imam Prayoga, Hendy Santosa, Novalio Daratha, Ruvita Faurina
Date: 2022-07-31 00:00:00

The Nutrient Film Technique (NFT) method is one of the most popular hydroponic cultivation methods. This method has advantages such as easier maintenance, faster and optimal plant growth, better use of fertilizers, and less deposition. The disadvantages of NFT include the consumption of electrical power and the faster spread of disease. Therefore, NFT requires a good nutrient control and monitoring system to save electricity and achieve optimal growth and resistance to pests and diseases. In this study, a nutrient control was designed with indicators of pH and TDS levels and equipped with an Internet of Things (IoT) based monitoring system. The control system used is the Mamdani Fuzzy Inference System. The output of the system is the active time of the pH Up, pH Down, and AB Mix nutrient pumps, which aim to normalize the pH and TDS of nutrient liquids. The experimental results show that one to three control steps are needed to normalize pH. One control step has a response time of 60 seconds, and it can prevent pH Up and pH Down oscillations. As for TDS control, the prediction of AB mix pump active time works accurately, and TDS levels can be normalized in one control step. Overall, based on surface control, simulations, and real experimental data, it is indicated that the control system operates very well and can normalize pH and TDS to the desired normal standard.
Decentralized Intermittent Feedback Adaptive Control of Non-triangular Nonlinear Time-varying Systems
Authors: Libei Sun, Xiucai Huang, Yongduan Song
Date: 2022-07-31 00:00:00
Tasks: Philosophy

This paper investigates the decentralized stabilization problem for a class of interconnected systems in the presence of non-triangular structural uncertainties and time-varying parameters, where each subsystem exchanges information only with its neighbors and only intermittent (rather than continuous) states and input are to be utilized. Thus far to our best knowledge, no solution exists priori to this work, despite its high prevalence in practice. Two globally decentralized adaptive control schemes are presented based on the backstepping technique, the first one is developed in a continuous fashion by combining the philosophy of the modified congelation of variables based approach with the special treatment of non-triangular structural uncertainties, which avoids the derivative of time-varying parameters and eliminates the limitation of the triangular condition, thus largely broadens the scope of application. By making use of the important property that the partial derivatives of the constructed virtual controllers in each subsystem are all constant, the second scheme is developed through directly replacing the states in the preceding scheme with the triggered ones. Consequently, the non-differentiability of the virtual control stemming from intermittent state feedback is completely obviated. The internal signals under both schemes are rigorously shown to be globally uniformly bounded with the aid of several novel lemmas, while the stabilization performance can be enhanced by appropriately adjusting design parameters. Moreover, the inter-event intervals are ensured to be lower-bounded by a positive constant. Finally, numerical simulation verifies the benefits and efficiency of the proposed method.
On-CMOS High-Throughput Multi-Modal Amperometric DNA Analysis with Distributed Thermal Regulation
Authors: Hamed M. Jafari, Xilin Liu, Roman Genov
Date: 2022-07-30 00:00:00
Tasks: DNA analysis

Accurate temperature regulation is critical for amperometric DNA analysis to achieve high fidelity, reliability, and throughput. In this work, a 9x6 cell array of mixed-signal CMOS distributed temperature regulators for on-CMOS multi-modal amperometric DNA analysis is presented. Three DNA analysis methods are supported, including constant potential amperometry (CPA), cyclic voltammetry (CV), and impedance spectroscopy (IS). In-cell heating and temperature sensing elements are implemented in standard CMOS technology without post-processing. Using proportional-integral-derivative (PID) control, the local temperature can be regulated to within +/-0.5C of any desired value between 20C and 90C. The two computationally intensive operations in the PID algorithm, multiplication, and subtraction, are performed by an in-cell dual-slope multiplying ADC in the mixed-signal domain, resulting in a small area and low power consumption. Over 95% of the circuit blocks are synergistically shared among the four operating modes, including CPA, CV, IS, and the proposed temperature regulation mode. A 3mmx3mm CMOS prototype fabricated in a 0.13um CMOS technology has been fully experimentally characterized. Each channel occupies an area of 0.06mm2 and consumes 42uW from a 1.2V supply. The proposed distributed temperature regulation design and the mixed-signal PID implementation can be applied to a wide range of sensory and other applications.
Novel Maximum Likelihood Estimation of Clock Skew in One-Way Broadcast Time Synchronization
Authors: Fanrong Shi, Huailiang Li, Simon X. Yang, Xianguo Tuo, Maosong Lin
Date: 2022-07-30 00:00:00

Clock skew compensation is essential for accurate time synchronization in wireless networks. However, contemporary clock skew estimation is based on inaccurate transmission time measurement, which makes credible estimation challenging. Based on one-way broadcast synchronization, this study presents a novel maximum likelihood estimation (MLE) with an innovative implementation to minimize the clock skew estimation error caused by delay. A multiple one-way broadcast model is developed for observation and set collection, while the distribution of actual delay is discussed. A clock skew MLE based on Gaussian delay is then proposed and its Cramer-Rao lower bound provided. The developed MLE is independent of the clock offset estimation, and requires only two synchronization periods to generate an accurate estimation. Extensive experimental results indicate that the performance of the proposed MLE is better than the methods popularly used in existing time synchronization protocols.
Fast Convergence Time Synchronization in Wireless Sensor Networks Based on Average Consensus
Authors: Fanrong Shi, Xianguo Tuo, Lili Ran, Zhenwen Ren, Simon X. Yang
Date: 2022-07-30 00:00:00

Average consensus theory is intensely popular for building time synchronization in wireless sensor network (WSN). However, the average consensus-based time synchronization algorithm is based on iteration that pose challenges for efficiency, as they entail high communication cost and long convergence time in large-scale WSN. Based on the suggestion that the greater the algebraic connectivity leads to the faster the convergence, a novel multi-hop average consensus time synchronization (MACTS) is developed with innovative implementation in this paper. By employing multi-hop communication model, it shows that virtual communication links among multi-hop nodes are generated and algebraic connectivity of network increases. Meanwhile, a multihop controller is developed to balance the convergence time, accuracy and communication complexity. Moreover, the accurate relative clock offset estimation is yielded by delay compensation. Implementing the MACTS based on the popular one-way broadcast model and taking multi-hop over short distances, we achieve hundreds of times the MACTS convergence rate compared to ATS.
Rapid-Flooding Time Synchronization for Large-Scale Wireless Sensor Networks
Authors: Fanrong Shi, Xianguo Tuo, Simon X. Yang, Jing Lu, Huailiang Li
Date: 2022-07-30 00:00:00

Accurate and fast-convergent time synchronization is very important for wireless sensor networks. The flooding time synchronization converges fast, but its transmission delay and by-hop error accumulation seriously reduce the synchronization accuracy. In this article, a rapidflooding multiple one-way broadcast time-synchronization (RMTS) protocol for large-scale wireless sensor networks is proposed. To minimize the by-hop error accumulation, the RMTS uses maximum likelihood estimations for clock skew estimation and clock offset estimation, and quickly shares the estimations among the networks. As a result, the synchronization error resulting from delays is greatly reduced, while faster convergence and higher-accuracy synchronization is achieved. Extensive experimental results demonstrate that, even over 24-hops networks, the RMTS is able to build accurate synchronization at the third synchronization period, and moreover, the by-hop error accumulation is slower when the network diameter increases.
Reducing Attack Opportunities Through Decentralized Event-Triggered Control
Authors: Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Date: 2022-07-30 00:00:00

Decentralized control systems are widely used in a number of situations and applications. In order for these systems to function properly and achieve their desired goals, information must be propagated between agents, which requires connecting to a network. To reduce opportunities for attacks that may be carried out through the network, we design an event-triggered mechanism for network connection and communication that minimizes the amount of time agents must be connected to the network, in turn decreasing communication costs. This mechanism is a function of only local information and ensures stability for the overall system in attack-free scenarios. Our approach distinguishes itself from current decentralized event-triggered control strategies by considering scenarios where agents are not always connected to the network to receive critical information from other agents and by considering scenarios where the communication graph is undirected and connected. An algorithm describing this network connection and communication protocol is provided, and our approach is illustrated via simulation.
Distributed Scheduling at Non-Signalized Intersections with Mixed Cooperative and Non-Cooperative Vehicles
Authors: Feihong Yang, Yuan Shen
Date: 2022-07-30 00:00:00
Tasks: Management, Scheduling, Trajectory Planning

Intersection management with mixed cooperative and non-cooperative vehicles is crucial in next-generation transportation systems. For fully non-cooperative systems, a minimax scheduling framework was established, while it is inefficient in mixed systems as the benefit of cooperation is not exploited. This letter focuses on the efficient scheduling in mixed systems and proposes a two-stage policy that makes full use of the cooperation relation. Specifically, a long-horizon self-organization policy is first developed to optimize the passing order of cooperative vehicles in a distributed manner, which is proved convergent when inbound roads are sufficiently long. Then a short-horizon trajectory planning policy is proposed to improve the efficiency when an ego-vehicle faces both cooperative and non-cooperative vehicles, and its safety and efficiency are theoretically validated. Furthermore, numerical simulations verify that the proposed policies can effectively reduce the scheduling cost and improve the throughput for cooperative vehicles.
Coordinated control in multi-terminal VSC-HVDC systems to improve transient stability: Impact on electromechanical-oscillation damping
Authors: Javier Renedo, Luis Rouco, Aurelio Garcia-Cerrada, Lukas Sigrist
Date: 2022-07-29 00:00:00

Multi-terminal high-voltage Direct Current technology based on Voltage-Source Converter stations (VSC-MTDC) is expected to be one of the most important contributors to the future of electric power systems. In fact, among other features, it has already been shown how this technology can contribute to improve transient stability in power systems by the use of supplementary controllers. Along this line, this paper will investigate in detail how these supplementary controllers may affect electromechanical oscillations, by means of small-signal stability analysis. The paper analyses two control strategies based on the modulation of active-power injections (P-WAF) and reactive-power injections (Q-WAF) in the VSC stations. Both control strategies use global signals of the frequencies of the VSC-MTDC system and they presented significant improvements on transient stability. The paper will provide guidelines for the design of these type of controllers to improve both, large- and small-disturbance angle stability. Small-signal stability techniques (in Matlab) will be used to assess electromechanical-oscillation damping, while non-linear time domain simulation (in PSS/E) will be used to confirm the results. Results will be illustrated in Nordic32A test system with an embedded VSC-MTDC system. The paper analyses the impact of the controller gains and communication latency on electromechanical-oscillation damping. The main conclusion of the paper is that transient-stability-tailored supplementary controllers in VSC-MTDC systems can be tuned to damp inter-area oscillations too, maintaining their effectiveness for transient-stability improvement.
Coordinating Flexible Ramping Products with Dynamics of the Natural Gas Network
Authors: Reza Bayani, Saeed D. Manshadi
Date: 2022-07-29 00:00:00
Tasks: Distributed Optimization, Privacy Preserving

In electricity networks with high penetration levels of renewable resources, Flexible Ramping Products (FRPs) are among the utilized measures for dealing with the potential fluctuations in the net demand. This paper investigates the impacts of FRPs on the operation of interdependent electricity and natural gas networks. To accurately model and reflect the effects of variations in the natural gas fuel demand on the natural gas network, a dynamic Optimal Gas Flow (OGF) formulation is utilized. The non-convex dynamic model of the natural gas system is represented in a convex form via a tight relaxation scheme. An improved distributed optimization method is proposed to solve the coordinated operation problem in a privacy-preserving manner, where the two infrastructures only share limited information. We introduce the Inexact Varying Alternating Direction Method of Multipliers (IV-ADMM) and show that compared with the classic ADMM, it converges considerably faster and in fewer iterations. Through a comparison of day-ahead and real-time operation planning results, it is concluded that without accounting for natural gas network dynamics, the FRP model is not a trustworthy tool in day-ahead planning against uncertainties.
Spline-Shaped Microstrip Edge-Fed Antenna for 77 GHz Automotive Radar Systems
Authors: Marco Salucci, Lorenzo Poli, Paolo Rocca, Claudio Massagrande, Pietro Rosatti, Mohammad Abdul Hannan, Mirko Facchinelli, Andrea Massa
Date: 2022-07-26 00:00:00

An innovative millimeter-wave (mm-wave) microstrip edge-fed antenna (EFA) for 77 GHz automotive radars is proposed. The radiator contour is modeled with a sinusoidal spline-shaped (SS) profile characterized by a reduced number of geometrical descriptors, but still able to guarantee a high flexibility in the modeling for fulfilling challenging user-defined requirements. The SS-EFA descriptors are effectively and efficiently optimized with a customized implementation of the System-by-Design (SbD) paradigm. The synthesized EFA layout, integrated within a linear arrangement of identical replicas to account for the integration into the real radar system, exhibits suitable impedance matching, isolation, polarization purity, and stability of the beam shaping/pointing within the target band [76:78][GHz]. The experimental assessment, carried out with a Compact Antenna Test Range (CATR) system on a printed circuit board (PCB)-manufactured prototype, assess the reliability of the outcomes from the full-wave (FW) simulations as well as the suitability of the synthesized SS-EFA for automotive radars.
Evaluating evolution as a learning algorithm
Authors: Miles Miller-Dickson, Christopher Rose, C. Brandon Ogbunugafor, I. Saira Mian
Date: 2022-08-01 00:00:00

We interpret the Moran model of natural selection and drift as an algorithm for learning features of a simplified fitness landscape, specifically genotype superiority. This algorithm's efficiency in extracting these characteristics is evaluated by comparing it to a novel Bayesian learning algorithm developed using information-theoretic tools. This algorithm makes use of a communication channel analogy between an environment and an evolving population. We use the associated channel-rate to determine an informative population-sampling procedure. We find that the algorithm can identify genotype superiority faster than the Moran model but at the cost of larger fluctuations in uncertainty.