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The challenge of advanced FDI algorithms for aircraft systems 11th

The challenge of advanced FDI algorithms for aircraft system...

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11th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Goupil, Philippe Zolghadri, Ali Airbus Operat SAS Aircraft Control 316 Route Bayonne F-31060 Toulouse France Univ Bordeaux CNRS IMS Lab F-33405 Talence France

What is the Achilles' heel of academic Fault Detection and Isolation (FDI) methods when it comes to application to real aircraft systems? This paper discusses some major and decisive issues that stand in the way of their transition from lab developments and simulations to real life applications in aeronautics. Often underestimated by academics, these issues determine the survivability of a new design for final V&V (Verification & Validation) activities. The paper recalls some practical items that should be considered at the design stage to help reach high Technological Readiness Level (TRL) scales for a given FDI algorithm. The paper will also take a look in the future and the way forward to anticipate future *** (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license(https://***/licenses/by-nc-nd/4.0/)

关键词： Fault Detection Isolation Application to aircraft systems

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Kinematic modelling and design of a tendon actuated soft manipulator 13

Kinematic modelling and design of a tendon actuated soft man...

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13th ifac symposium on Robot control (SYROCO)

作者： Banovic, Nikola Maric, Filip Seder, Marija Petrovic, Ivan Univ Zagreb Lab Autonomous Syst & Mobile Robot Fac Elect Engn & Comp Zagreb Croatia Univ Toronto Inst Aerosp Studies Space & Terr Autonomous Robot Syst Lab Toronto ON Canada

ISBN: (纸本)9781713867890

Soft robots have garnered significant attention in recent years due to their ability to perform complex and organic motions, while being simple in structure. In particular, soft manipulators have enabled safer collaboration with humans and larger margins of error in applications such as grasping. Unfortunately, the lack of conventional mechanical joints and a large variety of designs necessitate the development of specialized kinematic models. In this paper, we present a novel mathematical framework for kinematic modelling of multi-section soft manipulators actuated by four pulling tendons per section embedded in an elastic, deformable material such as silicone. We use piecewise constant curvature approximation to capture the shape of the manipulator and derive an analytical forward kinematic mapping. Further, we accompany this model with a simple and effective numerical inverse kinematics approach. Finally, we develop a hardware prototype and perform a qualitative validation of both the forward and inverse kinematics. Our experiments indicate that this kinematic model is a feasible for the proposed robot *** (c) 2022 The Authors This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： soft robotics soft manipulator design motion control systems kinematics

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Fault Tolerant control System for a Mini Hydropower Plant 11th

Fault Tolerant Control System for a Mini Hydropower Plant

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11th ifac symposium on control of Power and Energy systems (CPES)

作者： Muresan, Vlad Abrudean, Mihail Moga, Daniel Petreu, Dorin Stroia, Nicoleta Bondici, Cristian Fisca, Marius Cohut, Mircea Tech Univ Cluj Napoca RO-400114 Cluj Napoca Romania

In this paper, a solution for the fault tolerant control of a mini hydropower plant is proposed. The mathematical model which describes the dynamics of the electrical energy production process is identified based on processing the experimental data measured during the plant operation. The main real power and frequency control strategy is based on implementing the cascade control structure. In order to obtain the fault tolerance property, the initial form of the cascade structure is augmented by introducing additional elements which identify the faults and reject their effects. In order to implement the faults identifier and the correction mechanism, artificial intelligence methods, based on neural networks, are used.

关键词： Mini hydropower plant cascade control structure fault tolerant control islanded microgrid experimental data neural networks modelling simulation turbine synchronous generator group

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Reliable Unknown Input Observer for Continuous-Time Linear systems 11th

Reliable Unknown Input Observer for Continuous-Time Linear S...

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11th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Meslem, Nacim Hably, Ahmad Raissi, Tarek Wang, Zhenhua Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France Conservatoire Natl Arts & Metiers 292 Rue St Martin F-75141 Paris France Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China

This work proposes a set-valued extension of the classical unknown input observers for linear continuous-time systems without using set-by-step set-membership computations or imposing the positivity property of the dynamics of the estimation error. In fact, based on an explicit set-integration method of the estimation error, the framing and convergence properties of the proposed set-valued unknown input observer are demonstrated. Moreover, thanks to the proposed design approach, robust threshold on the residual can be established a priori. Simulation results are reported to highlight the effectiveness of the proposed state estimator in the presence of unknown inputs. Copyright (C) 2022 The Authors.

关键词： State estimation continuous-time linear systems unknown input observer interval observer set-membership estimation reachability analysis

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Adaptive Contraction-based control of Uncertain Nonlinear Processes using Neural Networks 13th

Adaptive Contraction-based Control of Uncertain Nonlinear Pr...

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13th ifac symposium on Dynamics and control of Process systems, including Biosystems (DYCOPS)

作者： Wei, Lai McCloy, Ryan Bao, Jie UNSW Sydney Sch Chem Engn Sydney NSW 2052 Australia

Driven by the flexible manufacturing trend in the process control industry and the uncertain nature of chemical process models, this article aims to achieve offset-free tracking for a family of uncertain nonlinear systems (e.g., using process models with parametric uncertainties) with adaptable performance. The proposed adaptive control approach incorporates into the control loop an adaptive neural network embedded contraction-based controller (to ensure convergence to time-varying references) and an online parameter identification module coupled with reference generation (to ensure modelled parameters converge those of the physical system). The integrated learning and control approach involves training a state and parameter dependent neural network to learn a contraction metric parameterized by the uncertain parameter and a differential feedback gain. This neural network is then embedded in an adaptive contraction-based control law which is updated by parameter estimates online. As uncertain parameter estimates converge to the corresponding physical values, offset-free tracking, simultaneously with improved convergence rates, can be achieved, resulting in a flexible, efficient and less conservative approach to the reference tracking control of uncertain nonlinear processes. An illustrative example is included to demonstrate the overall approach. Copyright (C) 2022 The Authors.

关键词： Artificial intelligence and machine learning Dynamic modelling and simulation for control and operation Modeling and identification Process control

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Selection of the estimation model for robust observer-based controller against plant uncertainties 10th

Selection of the estimation model for robust observer-based ...

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10th ifac symposium on Robust control Design (ROCOND)

作者： Shikada, Kana Sebe, Noboru Sato, Masayuki Kyushu Inst Technol Kitakyushu Fukuoka Japan Japan Aerosp Explorat Agcy Chofu Tokyo Japan

This paper is concerned with the design of robust controllers with observers. In general, the nominal model is selected as the state-space model for the observer to estimate the states even if the plant has uncertainties. However, the properness of this strategy is ambiguous. This paper evaluates the properness of selecting the nominal model for state estimation of the plant with uncertainties. Sato (2018a) proposed a new type of controller so-called observer-structured controller. The controller introduces additional freedom for selecting the state-space model used for the state estimation. With this type of controller, this paper demonstrates that the adequate selection of estimation model improves the closed-loop control performance through numerical examples. Copyright (C) 2022 The Authors.

关键词： Robust estimation Observer for linear systems Robust control

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Wrench Estimation and Impedance-based control applied to a Flying Parallel Robot Interacting with the Environment 11

Wrench Estimation and Impedance-based Control applied to a F...

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11th ifac symposium on Intelligent Autonomous Vehicles (IAV)

作者： Liu, Shiyu Fantoni, Isabelle Chriette, Abdelhamid Six, Damien Ecole Cent Nantes Lab Sci Numer Nantes LS2N 1 Rue Noe F-44321 Nantes France Ctr Natl Rech Sci LS2N 1 Rue Noe F-44321 Nantes France

Multi-vehicle aerial robots present great potential in accomplishing manipulation tasks, because of their high payload capacity and full manipulability in 3-dimensional space. Belonging to this class of aerial robots, the Flying Parallel Robot (FPR) is an architecture where a moving platform is supported collectively by a team of quadrotors with passive kinematic chains. While the modelling and control of the FPR in free space has been studied in the previous work, there is lack of consideration in robot-environment interaction, which is however significant to develop the industrial applications of such robots. In this paper, we implement an external wrench estimator and an impedance-based controller with force tracking capability to achieve the disturbance rejection and the physical interaction with the environment. Extensive experimental validations have shown the FPR capable of hovering in presence of additional payload and strong wind perturbations, and performing contact-based interaction tasks. Copyright (C) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/)

关键词： Aerial systems: Mechanics and control Impedance control Multi-vehicle systems

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Learning Stochastic Parametric Differentiable Predictive control Policies 10th

Learning Stochastic Parametric Differentiable Predictive Con...

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10th ifac symposium on Robust control Design (ROCOND)

作者： Drgona, Jan Mukherjee, Sayak Tuor, Aaron Halappanavar, Mahantesh Vrabie, Draguna Pacific Northwest Natl Lab Richland WA 99352 USA

The problem of synthesizing stochastic explicit model predictive control policies is known to be quickly intractable even for systems of modest complexity when using classical control-theoretic methods. To address this challenge, we present a scalable alternative called stochastic parametric differentiable predictive control (SP-DPC) for unsupervised learning of neural control policies governing stochastic linear systems subject to nonlinear chance constraints. SP-DPC is formulated as a deterministic approximation to the stochastic parametric constrained optimal control problem. This formulation allows us to directly compute the policy gradients via automatic differentiation of the problem's value function, evaluated over sampled parameters and uncertainties. In particular, the computed expectation of the SP-DPC problem's value function is backpropagated through the closed-loop system rollouts parametrized by a known nominal system dynamics model and neural control policy which allows for direct model-based policy optimization. We demonstrate the computational efficiency and scalability of the proposed policy optimization algorithm in three numerical examples, including systems with a large number of states or subject to nonlinear constraints. Copyright (C) 2022 The Authors.

关键词： Stochastic explicit model predictive control offline model-based policy optimization deep neural networks differentiable programming parametric programming

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LPV control design based on ultra-local model for trajectory tracking problem 10th

LPV control design based on ultra-local model for trajectory...

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10th ifac symposium on Robust control Design (ROCOND)

作者： Hegedus, Tamas Fenyes, Daniel Szabo, Zoltan Nemeth, Balazs Gaspar, Peter Inst Comp Sci & Control SZTAKI Eotvos Lorand Res Network ELKH Kende U 13-17 H-1111 Budapest Hungary

Model Free control (MFC) is a novel technique to overcome some modeling and control challenges of highly nonlinear systems. The MFC control strategy consists of two parts, i.e., ultra-local model-based control and state feedback control. This paper proposes the robust Linear Parameter-Varying (LPV) method for design the state feedback control part of the strategy. In the design of robust LPV control the effect of the ultra-local model, formed as a disturbance, is involved. The contribution of this extension to the original concept of MFC design is that a desired performance of the closed-loop system can be achieved. The effectiveness of the presented control strategy is demonstrated through a trajectory tracking problem of autonomous vehicles using the high-fidelity simulation software, IPG CarMaker. Copyright (C) 2022 The Authors.

关键词： ultra-local model trajectory tracking autonomous vehicles LPV control

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Robust Stealthy Covert Attacks on Cyber-Physical systems 11th

Robust Stealthy Covert Attacks on Cyber-Physical Systems

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11th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Li, Xuerong Zhang, Ping Dong, Hongli Northeast Petr Univ Inst Artificial Intelligence Energy Daqing 163318 Peoples R China Northeast Petr Univ Inst Heilongjiang Prov Key Lab Networking & Intell Daqing 163318 Peoples R China Tech Univ Kaiserslautern TUK Inst Automatic Control Erwin Schrodinger Str 12 D-67663 Kaiserslautern Germany

As networks become more widely used in control systems, the risk of cyber attacks increases significantly. The risk arising from stealthy attacks is that an adversary may take control of the plant through the communication network without being detected by the usual monitoring systems, with consequences that are often malicious or even destructive. This paper considers a new attack scheme called robust stealthy covert attack. Unlike the standard covert attack in Smith (2011), the robust covert attack can keep its stealthiness, even if the adversary doesn't have complete knowledge of plant model. It will be shown that the robust covert attack can be made stealthy by applying the time delayed control technique. An example is given to illustrate the stealthiness of the proposed robust covert attack in the presence of model *** (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Robust stealthy covert attacks cyber-physical systems time delayed control

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