Imperial College London

ProfessorEricYeatman

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Head of Department of Electrical and Electronic Engineering
 
 
 
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Contact

 

+44 (0)20 7594 6204e.yeatman CV

 
 
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Assistant

 

Ms Anna McCormick +44 (0)20 7594 6189

 
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Location

 

610aElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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362 results found

Liu M, Zhang Y, Fu H, Qin Y, Ding A, Yeatman EMet al., 2023, A seesaw-inspired bistable energy harvester with adjustable potential wells for self-powered internet of train monitoring, Applied Energy, Vol: 337, ISSN: 0306-2619

Energy harvesting provides a potential solution to power distributed sensors for train condition monitoring in a self-sustained manner, but the broadband and random nature of the available vibration energy makes effective energy harvesting very challenging. In this paper, a novel seesaw-inspired bistable energy harvester is developed to facilitate self-powered monitoring of trains and the realization of the Internet of Trains. The seesaw-inspired nonlinear harvester is realized for the first time using the attractive magnetic forces between a moving magnet and two fixed magnets to implement the gravitational force effect in seesaws and the restoring spring forces from limit springs to realize the supporting effect of legs to prevent seesaws from being hitting on the floor. A theoretical model is established to describe the dynamics of the whole systems, and the dynamics of the bistable energy harvester are numerically studied for different structural parameters to explore is potential well adjustability and its impact on energy harvesting performance. Through the numerical analysis, it is identified that different fixed magnet positions and spring lengths correspond to different harvesters’ potential well distribution, operational frequency ranges, and changing the coil positions also affects the output power. The results of the theoretical model are validated by a developed prototype and experimental results. The bistable energy harvester performs well over a wide frequency range of 18–38 Hz. An output power of 7.4 mW was obtained at 38 Hz with a 600 Ω load resistor. Finally, this energy harvester is used to fully power a wireless sensor node with a micro-controller, a Bluetooth module and an accelerometer, showing its capability in realizing self-powered condition monitoring of trains.

Journal article

Li X, Keshavarz M, Kassanos P, Kidy Z, Roddan A, Yeatman E, Thompson Aet al., 2023, SERS detection of breast cancer-derived exosomes using a nanostructured Pt-black template, Advanced Sensor Research, Pages: 1-12, ISSN: 2751-1219

At present, there are no cancer treatments that are both non-invasive and highly accurate. New tests that can diagnose cancer at an early stage would help to facilitate such improved therapies, and many recent studies have focused on the development of liquid biopsy tests for this purpose. Exosomes are extracellular vesicles secreted by cells as a means of communication that can be simply collected from blood samples. Current studies have shown the potential of surface-enhanced Raman spectroscopy (SERS) in differentiating cancerous cells from healthy cells. Herein, a bespoke platinum-black (Pt-black) SERS template is developed—via a cost-effective fabrication method of electroplating—to detect malfunctioned (cancerous) exosomes. The results demonstrate that the Pt-black SERS substrate exhibits stable and consistent spectra, which produces the high reproducibility required for a reliable diagnostic template. More importantly, using the Pt-black SERS template allows for the differentiation of cancer-derived exosomes (extracted from 4T1 cells—a triple-negative breast cancer cell line) and exosomes from healthy fibroblast cells with an 83.3% sensitivity and a 95.8% specificity. This study establishes the potential of the Pt-black template in detecting cancerous exosomes and lays a solid foundation for future studies in the clinical application of SERS in cancer diagnosis.

Journal article

Zhang D, Gorochowski TE, Marucci L, Lee H-T, Gil B, Li B, Hauert S, Yeatman Eet al., 2023, Advanced medical micro-robotics for early diagnosis and therapeutic interventions, FRONTIERS IN ROBOTICS AND AI, Vol: 9, ISSN: 2296-9144

Journal article

Wright SW, Kiziroglou ME, Yeatman EM, 2022, Inductive power line harvester with flux guidance for self-powered sensors, IEEE Sensors Journal, ISSN: 1530-437X

Self-powered sensors are expected to enable new large-scale deployment and location access capabilities for sensor systems. Energy harvesting devices have been shown to provide adequate power densities but their dependence on very specific environmental conditions restricts their applicability. Energy harvesting from power line infrastructure offers an architecture for addressing this challenge, because such infrastructure is widely available. In this paper an inductive power line harvester concept is presented, based on a flux concentration approach adapted to a closed-loop core geometry. Flux concentration is studied by simulation, showing a 26% flux increase using a 1:3 geometrical concentration ratio in a closed-loop core. A 20×20×25 mm prototype with a U-shaped soft-core sheet and a 200-turn Cu coil around a 5 mm diameter, 20 mm long soft-core rod is introduced. The total device volume is 9.1 cm 3 . Characterization results on a power line evaluation setup for currents up to 35 A RMS and a 50 Hz – 1 kHz range are presented. Power between 2.2 mW (50 Hz) and 233 mW (1 kHz) is demonstrated on an ohmic load, from a 10 A RMS power line current, employing impedance matching with reactance cancellation. The corresponding power densities are 0.24 mW/cm 3 and 25 mW/cm 3 respectively, per total device volume. This performance is adequate for enabling self-powered wireless sensor networks installed along power distribution lines.

Journal article

Blagojevic M, Dieudonne A, Kamecki L, Kiziroglou ME, Krastev K, Marty D, Piguet D, Spasic S, Wright SW, Yeatman EMet al., 2022, Autonomous electrical current monitoring system for aircraft, IEEE Transactions on Aerospace and Electronic Systems, Pages: 1-13, ISSN: 0018-9251

Aircraft monitoring systems offer enhanced safety, reliability, reduced maintenance cost and improved overall flight efficiency. Advancements in wireless sensor networks (WSN) are enabling unprecedented data acquisition functionalities, but their applicability is restricted by power limitations, as batteries require replacement or recharging and wired power adds weight and detracts from the benefits of wireless technology. In this paper, an energy autonomous WSN is presented for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A RMS, DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funnelling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. The proposed system offers a unique energy autonomous WSN platform for aircraft monitoring.

Journal article

Cursi F, Bai W, Yeatman EMM, Kormushev Pet al., 2022, Task Accuracy Enhancement for a Surgical Macro-Micro Manipulator With Probabilistic Neural Networks and Uncertainty Minimization, IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, ISSN: 1545-5955

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, Optimization of surgical robotic instrument mounting in a macro-micro manipulator setup for improving task execution, IEEE Transactions on Robotics, Vol: 38, Pages: 2858-2874, ISSN: 1552-3098

In Minimally Invasive Robotic Surgery (MIRS),the surgical instrument is usually inserted inside the patient’sbody through a small incision, which acts as a Remote Centerof Motion (RCM). Serial-link manipulators can be used asmacro robots on which micro surgical robotic instruments aremounted to increase the number of degrees of freedom (DOFs)of the system and ensure safe task and RCM motion execution.However, the surgical instrument needs to be placed in anappropriate configuration when completing the motion tasks.The contribution of this work is to present a novel frameworkthat preoperatively identifies the best base configuration, interms or Roll, Pitch, and Yaw angles, of the micro surgicalinstrument with respect to the macro serial-link manipulator’send-effector in order to achieve the maximum accuracy anddexterity in performing specified tasks. The framework relieson Hierarchical Quadratic Programming (HQP) for the control,Genetic Algorithm (GA) for the optimization, and on a resilienceto error strategy to make sure deviations from the optimum donot affect the system’s performance.Simulation results show that the mounting configuration ofthe surgical instrument significantly impacts the performanceof the whole macro-micro manipulator in executing the desiredmotion tasks, and both the simulation and experimental resultsdemonstrate that the proposed optimization method improves theoverall performance.

Journal article

Chen X, Kiziroglou ME, Yeatman EM, 2022, Linear displacement and force characterisation of a 3D-printed flexure-based delta actuator, Smart Materials and Structures, Vol: 31, Pages: 1-9, ISSN: 0964-1726

Piezoelectric beams provide a fast, high-force and scalable actuation mechanism that could offer precise motion control to medical microdevices including invasive micromanipulators, catheters and diagnosis tools. Their small displacement range can be addressed by motion amplification mechanisms. In this paper, a piezoelectric-actuated delta-robot actuator is proposed for probe-based confocal laser endomicroscopy (pCLE) microsystems. A prototype is designed and fabricated using three-dimensional (3D) polymer compound printing for a multi-flexure compliant motion amplifier and commercial piezoelectric beams. The flexure material is optimised for maximum linear output motion. The overall robot length is 76 mm and its maximum lateral dimension is 32 mm, with 10 g overall mass, including three piezoelectric beams. An axial motion control range of 0.70 mm and a maximum axial force of 20 mN are demonstrated, at 140 V actuation voltage. The proposed actuator architecture is promising for controlling lens, fibre and micromanipulator components for medical microrobotic applications.

Journal article

Holmes AS, Kiziroglou ME, Yang SKE, Yuan C, Boyle DE, Lincoln DM, McCabe JDJ, Szasz P, Keeping SC, Williams DR, Yeatman EMet al., 2022, Minimally invasive online water monitor, IEEE Internet of Things Journal, Vol: 9, Pages: 14325-14335, ISSN: 2327-4662

Sensor installation on water infrastructure is challenging due to requirements for service interruption, specialised personnel, regulations and reliability as well as the resultant high costs. Here, a minimally invasive installation method is introduced based on hot-tapping and immersion of a sensor probe. A modular architecture is developed that enables the use of interchangeable multi-sensor probes, non-specialist installation and servicing, low-power operation and configurable sensing and connectivity. A prototype implementation with a temperature, pressure, conductivity and flow multi-sensor probe is presented and tested on an evaluation rig. This paper demonstrates simple installation, reliable and accurate sensing capability as well as remote data acquisition. The demonstrated minimally invasive multi-sensor probes provide an opportunity for the deployment of water quality sensors that typically require immersion such as pH and spectroscopic composition analysis. This design allows dynamic deployment on existing water infrastructure with expandable sensing capability and minimal interruption, which can be key to addressing important sensing parameters such as optimal sensor network density and topology.

Journal article

Wales DJ, Keshavarz M, Howe C, Yeatman Eet al., 2022, 3D Printability Assessment of Poly(octamethylene maleate (anhydride) citrate) and Poly(ethylene glycol) Diacrylate Copolymers for Biomedical Applications, ACS APPLIED POLYMER MATERIALS, Vol: 4, Pages: 5457-5470, ISSN: 2637-6105

Journal article

Xiao B, Lam H-K, Xuan C, Wang Z, M Yeatman Eet al., 2022, Optimization for interval type-2 polynomial fuzzy systems: a deep reinforcement learning approach, IEEE Transactions on Artificial Intelligence, Pages: 1-12, ISSN: 2691-4581

It is known that the interval type-2 (IT2) fuzzy controllers are superior compared to their type-1 counterparts in terms of robustness, flexibility, etc. However, how to conduct the type reduction optimally with the consideration of system stability under the fuzzy-model-based (FMB) control framework is still an open problem. To address this issue, we present a new approach through the membership-function-dependent (MFD) and deep reinforcement learning (DRL) approaches. In the proposed approach, the reduction of IT2 membership functions of the fuzzy controller is completing during optimizing the control performance. Another fundamental issue is that the stability conditions must hold subject to different type-reduction methods. It is tedious and impractical to resolve the stability conditions according to different type-reduction methods, which could lead to infinite possibility. It is more practical to guarantee the holding of stability conditions during type-reduction rather than resolving the stability conditions, the MFD approach is proposed with the imperfect premise matching (IPM) concept. Thanks to the unique merit of the MFD approach, the stability conditions according to all the different embedded type-1 membership functions within the footprint of uncertainty (FOU) are guaranteed to be valid. During the control processes, the state transitions associated with properly engineered cost/reward function can be used to approximately calculate the deterministic policy gradient to optimize the acting policy and then to improve the control performance through determining the grade of IT2 membership functions of the fuzzy controller. The detailed simulation example is provided to verify the merits of the proposed approach.

Journal article

Cursi F, Bai W, Li W, Yeatman EM, Kormushev Pet al., 2022, Augmented neural network for full robot kinematic modelling in SE(3), IEEE Robotics and Automation Letters, Vol: 7, Pages: 7140-7147, ISSN: 2377-3766

Due to the increasing complexity of robotic structures, modelling robots is becoming more and more challenging, and analytical models are very difficult to build. Machine learning approaches have shown great capabilities in learning complex mapping and have widely been used in robot model learning and control. Generally, the inverse kinematics is directly learned, yet, learning the forward kinematics is simpler and allows computing exploiting the optimality of the controllers. Nevertheless, the learning method has no knowledge about the differential relationship between the position and velocity mappings. Currently, few works have targeted learning full robot poses considering both position and orientation. In this letter, we present a novel feedforward Artificial Neural network (ANN) architecture to learn full robot pose in SE(3) incorporating differential relationships in the learning process. Simulation and real world experiments show the capabilities of the proposed network to properly model the robot pose and its advantages over standard ANN.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, Model learning with backlash compensation for a tendon-driven surgical Robot, IEEE Robotics and Automation Letters, Vol: 7, Pages: 7958-7965, ISSN: 2377-3766

Robots for minimally invasive surgery are becoming more and more complex, due to miniaturization and flexibility requirements. The vast majority of surgical robots are tendon-driven and this, along with the complex design, causes high nonlinearities in the system which are difficult to model analytically. In this work we analyse how incorporating a backlash model and compensation can improve model learning and control. We combine a backlash compensation technique and a Feedforward Artificial Neural Network (ANN) with differential relationships to learn the kinematics at position and velocity level of highly articulated tendon-driven robots. Experimental results show that the proposed backlash compensation is effective in reducing nonlinearities in the system, that compensating for backlash improves model learning and control, and that our proposed ANN outperforms traditional ANN in terms of path tracking accuracy.

Journal article

Arteaga JM, Mitcheson PD, Yeatman EM, 2022, Development of a fast-charging platform for buried sensors using high frequency IPT for agricultural applications, 2022 IEEE Applied Power Electronics Conference and Exposition (APEC), Publisher: IEEE, Pages: 1116-1121

This paper describes the methodology and experimental results for wireless power delivery to a soil-sensors power and data distribution unit from an unmanned aerial vehicle (UAV), using a high frequency inductive power transfer (HF-IPT) link. The configuration features, at the transmit side, a lightweight single-turn air-core coil driven by a 13.56 MHz Class EF inverter mounted on a Matrice 100 drone by DJI, and at the receive side, a two-turn PCB coil with a voltage-tipler Class D rectifier, an off-the-shelf 42 V battery charger and a supercapacitors module for energy storage. The experiments were conducted with a coil-to-coil gap of 250 mm, which corresponds to a coupling factor lower than 5%. In the experiments, a 10 F, 42 V supercapacitors module was charged in eleven minutes with an energy efficiency of 34% from the 80 V DC source that feeds the inverter on the drone to the supercapacitor-based energy storage unit in the sensor module. At higher power (50 W) the HF-IPT system was able to achieve a 68% DC-DC efficiency with a coupling factor of 3.5%. The work reported in this paper is part of a multiple-discipline project which looks to enable the optimal usage of water in agriculture with broader sensing techniques and more frequent sensing cycles.

Conference paper

Kiziroglou ME, Wright SW, Yeatman EM, 2022, Power supply based on inductive harvesting from structural currents, IEEE Internet of Things Journal, Vol: 9, ISSN: 2327-4662

Monitoring infrastructure offers functional optimisation, lower maintenance cost, security, stability and data analysis benefits. Sensor nodes require some level of energy autonomy for reliable and cost-effective operation, and energy harvesting methods have been developed in the last two decades for this purpose. Here, a power supply that collects, stores and delivers regulated power from the stray magnetic field of currentcarrying structures is presented. In cm-scale structures the skin effect concentrates current at edges at frequencies even below 1 kHz. A coil-core inductive transducer is designed. A fluxfunnelling soft magnetic core shape is used, multiplying power density by the square of funnelling ratio. A power management circuit combining reactance cancellation, voltage doubling, rectification, super-capacitor storage and switched inductor voltage boosting and regulation is introduced. The power supply is characterised in house and on a full-size industrial setup, demonstrating a power reception density of 0.36 mW/cm3, 0.54 mW/cm3 and 0.73 mW/cm3 from a 25 A RMS structural current at 360 Hz, 500 Hz and 800 Hz respectively, corresponding to the frequency range of aircraft currents. The regulated output is tested under various loads and cold starting is demonstrated. The introduced method may enable power autonomy to wireless sensors deployed in current-carrying infrastructure.

Journal article

Bai W, Cursi F, Guo X, Huang B, Lo B, Yang G-Z, Yeatman EMet al., 2022, Task-Based LSTM Kinematic Modeling for a Tendon-Driven Flexible Surgical Robot, IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, Vol: 4, Pages: 339-342

Journal article

Bacha SC, Bai W, Wang Z, Xiao B, Yeatman EMet al., 2022, Deep Reinforcement Learning-Based Control Framework for Multilateral Telesurgery, IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, Vol: 4, Pages: 352-355

Journal article

Gil Rosa B, Akingbade OE, Guo X, Gonzalez-Macia L, Crone MA, Cameron LP, Freemont P, Choy K-L, G├╝der F, Yeatman E, Sharp DJ, Li Bet al., 2022, Multiplexed immunosensors for point-of-care diagnostic applications, Biosensors and Bioelectronics, Vol: 203, ISSN: 0956-5663

Accurate, reliable, and cost-effective immunosensors are clinically important for the early diagnosis and monitoring of progressive diseases, and multiplexed sensing is a promising strategy for the next generation of diagnostics. This strategy allows for the simultaneous detection and quantification of multiple biomarkers with significantly enhanced reproducibility and reliability, whilst requiring smaller sample volumes, fewer materials, and shorter average analysis time for individual biomarkers than individual tests. In this opinionated review, we compare different techniques for the development of multiplexed immunosensors. We review the state-of-the-art approaches in the field of multiplexed immunosensors using electrical, electrochemical, and optical methods. The barriers that prevent translating this sensing strategy into clinics are outlined together with the potential solutions. We also share our vision on how multiplexed immunosensors will continue their evolution in the coming years.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, GlobDesOpt: a global optimization framework for optimal robot manipulator design, IEEE Access, Vol: 10, Pages: 5012-5023, ISSN: 2169-3536

Robot design is a major component in robotics, as it allows building robots capable of performing properly in given tasks. However, designing a robot with multiple types of parameters and constraints and defining an optimization function analytically for the robot design problem may be intractable or even impossible. Therefore black-box optimization approaches are generally preferred. In this work we propose GlobDesOpt, a simple-to-use open-source optimization framework for robot design based on global optimization methods. The framework allows selecting various design parameters and optimizing for both single and dual-arm robots. The functionalities of the framework are shown here to optimally design a dual-arm surgical robot, comparing the different two optimization strategies.

Journal article

Bai W, Wang Z, Cao Q, Yokoi H, Fujie MG, Yeatman EM, Yang G-Zet al., 2022, Anthropomorphic dual-arm coordinated control for a single-port surgical robot based on dual-step optimization, IEEE Transactions on Medical Robotics and Bionics, Vol: 4, Pages: 72-84, ISSN: 2576-3202

Effective teleoperation of the small-scale and highly-integrated robots for single-port surgery (SPS) imposes unique control and human-robot interaction challenges. Traditional isometric teleoperation schemes mainly focus on end-to-end trajectory mapping, which is problematic when applied to SPS robotic control, especially for dual-arm coordinated operation. Inspired by the human arm configuration in boxing maneuvers, an optimized anthropomorphic coordinated control strategy based on a dual-step optimization approach is proposed. Theoretical derivation and solvability of the problem are addressed, and the effectiveness of the method is further demonstrated in detailed simulation and in-vitro experiments. The proposed control strategy has been shown to perform dexterous SPS bimanual manipulation more effectively, involving less instrument-interference and is free from singularities, thereby improving the safety and efficiency of SPS operations.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, Adaptive Kinematic Model Learning for Macro-Micro Surgical Manipulator Control, 7th IEEE International Conference on Advanced Robotics and Mechatronics, Publisher: IEEE, Pages: 494-501

Conference paper

Zhou X, Bai W, Ren Y, Yang Z, Wang Z, Lo B, Yeatman EMet al., 2022, An LSTM-based Bilateral Active Estimation Model for Robotic Teleoperation with Varying Time Delay, 7th IEEE International Conference on Advanced Robotics and Mechatronics, Publisher: IEEE, Pages: 725-730

Conference paper

Moorthy V, Kassanos P, Burdet E, Yeatman Eet al., 2022, Stencil Printing of Low-Cost Carbon-Based Stretchable Strain Sensors, IEEE Sensors Conference, Publisher: IEEE, ISSN: 1930-0395

Conference paper

Rosa BMG, Lo B, Yeatman E, 2022, Prototype smartwatch device for prolonged physiological monitoring in remote environments, IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks (BSN) / 18th IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Publisher: IEEE, ISSN: 2376-8886

Conference paper

Holmes AS, Yang SKE, Kiziroglou ME, Boyle DE, Lincoln DM, McCabe JDJ, Szasz P, Williams DR, Yeatman EMet al., 2022, Miniaturized Wet-Wet Differential Pressure Sensor, IEEE Sensors Conference, Publisher: IEEE, ISSN: 1930-0395

Conference paper

Sanchez J, Arteaga JM, Zeisiger C, Young DJ, Goel R, Mitcheson PD, Yeatman EM, Roundy Set al., 2022, Integration of a High Frequency Inductive Power Transfer System to Energize Agricultural Sensors Through Soil, Wireless Power Week (WPW), Publisher: IEEE, Pages: 366-371

Conference paper

Vyas K, Yeatman E, Dasgupta R, 2022, Rapid digital histology of urothelial carcinoma using line-scan confocal laser endomicroscopy

We present a high-speed line-scan confocal laser endomicroscope, which enables digital histopathology of freshly excised un-fixed bladder tissue specimens in real-time.

Conference paper

Wang Z, Lam HK, Guo Y, Xiao B, Li Y, Su X, Yeatman EM, Burdet Eet al., 2022, Adaptive Event-Triggered Control for Nonlinear Systems With Asymmetric State Constraints: A Prescribed-Time Approach, IEEE Transactions on Automatic Control, ISSN: 0018-9286

Finite/Fixed-time control yields a promising tool to optimize a system&#x0027;s settling time, but lacks the ability to separately define the settling time and the convergence domain (known as <italic>practically prescribed-time stability</italic>, PPTS). We provide a sufficient condition for PPTS based on a new piecewise exponential function, which decouples the settling time and convergence domain into separately user-defined parameters. We propose an adaptive event-triggered prescribed-time control scheme for nonlinear systems with asymmetric output constraints, using an exponential-type barrier Lyapunov function. We show that this PPTS control scheme can guarantee tracking error convergence performance, while restricting the output state according to the prescribed asymmetric constraints. Compared with traditional finite/fixed-time control, the proposed methodology yields separately user-defined settling time and convergence domain without the prior information on disturbance. Moreover, asymmetric state constraints can be handled in the control structure through bias state transformation, which offers an intuitive analysis technique for general constraint issues. Simulation and experiment results on a heterogeneous teleoperation system demonstrate the merits of the proposed control scheme.

Journal article

Sun L, Huang Y, Wang Z, Xiao B, Yeatman EMet al., 2022, Dual Quaternion Based Finite-Time Tracking Control for Mechatronic Systems with Actuation Allocation

This paper investigates the tracking control performance regulation and actuation allocation of mechatronic systems subject to coupling motions. In particular, the kinematic and dynamic model is described by dual quaternion, which captures the coupling effect between translation and rotation movements. Considering external disturbances and system uncertainties, a non-singular fast terminal sliding controller is then developed to ensure finite-time tracking performance. In addition, the unwinding problem caused by the redundancy of dual quaternion is addressed with the help of a novel attitude error function. Furthermore, an improved simplex method is designed for distributing the developed control commands to proper actuators. Numerical simulations demonstrate the effectiveness with respect to disturbance suppression, fast tracking, high accuracy, and finite-time stability of the proposed method.

Conference paper

Yang S, Kiziroglou M, Yeatman E, Holmes Aet al., 2021, Passive acoustic transducer as a fluid flow sensor, IEEE Sensors Conference, Publisher: IEEE, Pages: 1-4

Autonomy and minimal disruption are key desirable features for sensors to be deployed in medical, industrial, vehicle and infrastructure monitoring systems. Using a passive structure to transduce the quantity of interest into an acoustic or electromagnetic wave could offer an attractive solution for remote sensing, lifting the requirements of installing active materials, electronics, and power sources in remote, inaccessible, sensitive, or harsh environment locations. Here, we report a simple cavity and ball structure that transduces fluid flow through a pipe into an acoustic signal. A microphone on the outside wall of the pipe records the intensity and arrival rate of the sound pulses generated by collisions between the ball and the cavity walls. Using this approach external measurement of flow is demonstrated with adequate repeatability before any acoustic signal processing. This result is expected to open the way to the implementation of passive, remotely readable sensors for fluid flow and other fluid properties of interest.

Conference paper

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