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IEEE International Conference on robotics and Automation (ICRA)

作者： Jialun Liu MennaAllah Soliman Dana D. Damian Automatic Control and Systems Engineering Department Sheffield Robotics University of Sheffield Sheffield UK Insigneo Institute for in Silico Medicine University of Sheffield UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Soft robots have shown remarkable distinct capabilities due to their high deformation. Recently increasing attention has been dedicated to developing fully soft robots to exploit their full potential, with a recognition that electronic powering may limit this achievement. Alternative powering sources compatible with soft robots have been identified such as combustion and chemical reactions. A further milestone to such systems would be to increase the controllability and responsiveness of their underlying reactions in order to achieve more complex behaviors for soft robots. In this paper, we present a thermally-activated reactor incorporating a biocompatible hydrogel valve that enables control of the biochemical reaction of sugar and yeast. The biochemical reaction is utilized to generate contained pressure, which in turn powers a fluidic soft actuator. Experiments were conducted to evaluate the response time of the hydrogel valves with three different crosslinker concentrations. Among the tested concentrations, we found that the lowest crosslinker concentration yielded the fastest response time of the valve at an ambient temperature of 50°C. We also evaluated the pressure generation capacity of the reactor, which can reach up to 0.22 bar, and demonstrated the thermoresponsive behavior of the reactor to trigger a biochemical reaction for powering a fluidic soft actuator. This work opens up the possibility to power and control tetherless and fully soft robots.

关键词： Actuators Electric potential Deformation Hydrogels Soft robotics Valves Time factors

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Output Tracking for Uncertain Time-Delay systems via Robust Reinforcement Learning control

Output Tracking for Uncertain Time-Delay Systems via Robust ...

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第43届中国控制会议

作者： Zezhi Tang J Anthony Rossiter Xin Jin Benyuan Zhang George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The composite optimal output tracking control problem of time-delay uncertain systems is investigated in this paper. To improve the robustness of the uncertain systems, a disturbance observer-based(DOB) compensation scheme is proposed to reduce the influence of the *** further enhance the control efficiency, we incorporate a Smith predictor into the control framework to precisely predict future states of the delayed system. Subsequently, a composite actor-critic reinforcement learning(RL) scheme is built for approximating both the ideal value function associated with the compensated system and the optimal control policy in real-time, by augmenting the system states with the output tracking error. To counteract the impact of the probing signal, concurrent learning is employed in this paper with the data collected from the known system *** results based on an experimental platform of slot die coating machines demonstrate the effectiveness of the proposed scheme.

关键词： Smith Output Tracking for Uncertain Time-Delay systems via Robust Reinforcement Learning control

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Analysing and Modelling Human Trust to a Navigation Robot 2

Analysing and Modelling Human Trust to a Navigation Robot

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Onyeoru, Happy Chidi Wirth, Christopher Giles, Joshua Arvaneh, Mahnaz University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom School of Medical Sciences University of Manchester United Kingdom

ISBN: (纸本)9798350300802

Human trust plays a crucial role in Human-Machine Interactions (HMIs) within autonomous systems. This paper delves into the factors that influence human trust in machines, including varying error rates and types made by the machine, as well as the human's ability to intervene and rectify errors. To explore these factors, we conducted three scenarios involving a simulated claw robot navigating through multiple objects to detect and locate a target object. The first scenario examined the effect of changing error rates on human trust in the machine. In the second scenario, we investigated how variability in speed and accuracy of reaching the target impacted human trust. Lastly, we explored whether human trust in the machine changed when individuals had the capability to intervene and correct severe errors made by the machine. We then proposed a regression model to estimate human trust. Our results showed that human trust is significantly affected by changes in error rates. Our participants reported a higher trust on robot with low speed but higher accuracy in performing the task than the robot with high speed but lower accuracy. Interestingly, the ability to intervene and correct the robot's errors improved the participants' trust in the robot. Our regression result showed that we can estimate trust using different type of errors committed by machine which can be applied in real world scenarios. © 2023 IEEE.

关键词： computational modelling error rates human-machine interactions (HMIs) machine or robot action perceptions target identification trust

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A non-iterative approach to Linear Quadratic Static Output Feedback

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IFAC-PapersOnLine 2023年第2期56卷 9540-9545页

作者： Hadriano Morales Escamilla Paul Trodden Visakan Kadirkamanathan Department of Automatic Control and Systems Engineering ACSE The University of Sheffield Sheffield UK

This paper considers the problem of static output feedback (SOF) synthesis for linear time-invariant (LTI) systems. Static output feedback, and more generally structured controller synthesis, is of special interest to any industrial application where a reduced-order controller is desired, e.g., high-order systems, or a specific structure is to be imposed, i.e., distributed/decentralised control. A simple two-step process is proposed, solving one Riccati equation and one optimisation problem with linear matrix inequality (LMI) constraints, enabled via a dilation using the distance to the full-state feedback optimum gain. Numerical analysis shows considerable computational savings, with negligible differences in the performance, when compared to current iterative methods.

关键词： Output feedback control controller constraints and structure Linear multivariable systems Linear matrix inequalities Optimal control Static controller synthesis S-procedure

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Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI)

Sparse Identification of Nonlinear Dynamics with Side Inform...

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American control Conference (ACC)

作者： Gabriel F. Machado Morgan Jones Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Modern societies have an abundance of data yet good system models are rare. Unfortunately, many of the current system identification and machine learning techniques fail to generalize outside of the training set, producing models that violate basic physical laws. This work proposes a novel method for the Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI). SINDy-SI is an iterative method that uses Sum-of-Squares (SOS) programming to learn optimally fitted models while guaranteeing that the learned model satisfies side information, such as symmetries and physical laws. Guided by the principle of Occam's razor, that the simplest or most regularized best fitted model is typically the superior choice, during each iteration SINDy-SI prunes the basis functions associated with small coefficients, yielding a sparse dynamical model upon termination. Through several numerical experiments we will show how the combination of side information constraints and sparse polynomial representation cultivates dynamical models that obey known physical laws while displaying impressive generalized performance beyond the training set.

关键词： Training Programming Numerical simulation Data models Polynomials Numerical models System identification

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Optimal Flight Trajectories of Hybrid Electric Aircraft with In-Flight Charging

Optimal Flight Trajectories of Hybrid Electric Aircraft with...

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European control Conference (ECC)

作者： Yuanbo Nie Paing Ko Ross Drummond Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

The transition towards electric aircraft is particularly challenging due to the relatively low specific energy densities of electrical energy storage systems. If electric aircraft are to be realised, flight paths must be optimised to take advantage of the unique features of electric propulsion systems. In this paper, the problem of determining the optimal flight trajectories for aircraft powered by a combination of a fuel cell stack and lithium-ion battery pack is considered. Particular emphasis is given to the role of the battery pack's temperature and in-flight charging requirements on the results. Solutions that minimise the fuel consumption and the flight time are first considered. For both cases, the optimal solution was observed to discharge the battery during the climb with only minimal in-flight recharging of the battery by the fuel cell. A scenario that requires a fast climb and descent and the battery to be charged upon arrival was identified and shown to lead to an oscillatory profile for optimal in-flight charging. These results demonstrate the potential of solving optimal control problems to generate tailored electric aircraft trajectories.

关键词： Lithium-ion batteries Shafts Fuel cells Optimal control Motors Trajectory Aircraft

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Creating Whole Story Virtual Laboratories for a First Course in control

Creating Whole Story Virtual Laboratories for a First Course...

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UKACC International Conference on control (control)

作者： J. A. Rossiter Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

There has a been a growing interest in virtual laboratories as a supplement to hardware laboratories in supporting student learning and experience. This paper focuses specifically on virtual laboratories built using the MATLAB environment and highlights some recent developments. Specifically, these virtual laboratories aim to give users an overview of the core content of an entire 1st course in control in a single virtual laboratory interface. This paper highlights two such laboratories and shows how they can be used to supplement other learning resources and activities.

关键词： Laboratories Hardware Matlab

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Optimized Spatial Filter Selection for Transfer Learning in Brain-Computer Interface

Optimized Spatial Filter Selection for Transfer Learning in ...

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： Mohamed A A Mohamed Joshua Giles Mahnaz Arvaneh Automatic control and Systems Engineering Department University of Sheffield Sheffield UK

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

The Common Spatial Patterns (CSP) algorithm has shown great efficacy in extracting features for Brain-Computer Interfaces (BCIs), particularly in motor imagery BCIs. However, CSP performs poorly when dealing with limited labeled data, which leads to long calibration time at the beginning of each session. To overcome this challenge, we leverage source data, i.e., labeled data from other subjects, to transfer knowledge across subjects. This work proposes a novel approach termed Scaled and Warped CSP-based Transfer Learning (SW-CSP-TL). This method aligns source data with the temporal and amplitude structure of target data before computing CSP filters, ensuring optimization for capturing discriminative features relevant to the target domain. We evaluate the proposed SW-CSP-TL algorithm using the publicly available dataset 2a from BCI Competition IV and compare its performance with that of the classical CSP algorithm and the transfer learning CSP algorithm (CSP-TL) without amplitude scaling and temporal warping. Our algorithm exhibits superior performance particularly when the training data size is relatively small. Results demonstrate that for 5 and 15 training trials per class from the target session, SW-CSP-TL outperformed the classical CSP by an average of 10%, and 8%, respectively.

关键词： Training Transfer learning Training data Neural engineering Feature extraction Spatial filters Motors Brain-computer interfaces Standards Optimization

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Application of Statistical Methods to Support Automation of Pricing in Business 21st

Application of Statistical Methods to Support Automation o...

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21st Polish control Conference, PCC 2023

作者： Grobler-Debska, Katarzyna Kucharska, Edyta Mularczyk, Rafal Jagodziński, Mieczyslaw Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland Department of Systems Biology and Engineering Silesian University of Technology Gliwice Poland

ISBN: (纸本)9783031351723

This paper presents the possibility of using statistical modeling to automate the process of dynamic pricing management with revenue control and adaptation to current legislation in this area. In addition, it is proposed the use of integration of Python tools with the ERP and BI systems popularly used in the industry. This integration in order to facilitates decision-making in this area for the business without the end of programming. The proposed solutions support the CEO enterprises make decisions regarding pricing strategies and optimize their revenues. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Optimal Energy Exchange of Two Electric Vehicle Charging Stations with Solar-Hydrogen-Battery Storage systems 58

Optimal Energy Exchange of Two Electric Vehicle Charging Sta...

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58th International Universities Power engineering Conference, UPEC 2023

作者： Duan, Lijia Lai, Chun Sing Taylor, Gareth Zhang, Xin Brunel University Department of Electronic and Electrical Enginnering London United Kingdom University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom

ISBN: (纸本)9798350316834

This paper presents an optimisation method for the direct energy exchange between two electric vehicle (EV) charging stations located in the UK. Each EV charging station consists of solar panels, hydrogen and battery energy storage systems (SHBS). The stations are interconnected through a energy exchange system that enables the transfer of excess energy from one station to the other. The objective function of SHBS charging stations is to minimize the capital and operation and maintenance costs of the stations. The system constraints are the power output of individual components, as well as the power balance between SHBS charging stations and EV charging demand. Genetic Algorithm is used to optimize the system, considering various factors such as the size of the solar panels and hydrogen storage tanks, the capacity of the electric vehicle chargers, and the amount of energy exchanged between the two stations. The optimized system yields substantial cost savings. © 2023 IEEE.

关键词： Genetic algorithms

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