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  • 1.
    Bai, S.
    et al.
    Department of Materials and Production, Aalborg University, Aalborg, Denmark.
    Christensen, S.
    Department of Materials and Production, Aalborg University, Aalborg, Denmark.
    Islam, M.
    Department of Materials and Production, Aalborg University, Aalborg, Denmark.
    Rafique, Sajid
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Masud, Nauman
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    O’Sullivan, L.
    University of Limerick, Limerick, Ireland.
    Power, V.
    University of Limerick, Limerick, Ireland.
    Development and testing of full-body exoskeleton AXO-SUIT for physical assistance of the elderly2019In: Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics, WeRob2018, October 16-20, 2018, Pisa, Italy / [ed] Maria Chiara Carrozza, Silvestro Micera, José L. Pons, Cham: Springer, 2019, Vol. 22, p. 180-184Conference paper (Refereed)
    Abstract [en]

    This paper presents the design and preliminary testing of a full-body assistive exoskeleton AXO-SUIT for older adults. AXO-SUIT is a system of modular exoskeletons consisting of lower-body and upper-body modules, and their combination as full body as well to provide flexible physical assistance as needed. The full-body exoskeleton comprises 27 degrees of freedom, of which 17 are passive and 10 active, which is able to assist people in walking, standing, carrying and handling tasks. In the paper, design of the AXO-SUIT is described. End-user testing results are presented to show the effectiveness of the exoskeleton in providing flexible physical assistance.

  • 2.
    Chistiakova, Tatiana
    et al.
    Uppsala university, Uppsala, Sweden.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Carlsson, Bengt
    Uppsala university, Uppsala, Sweden.
    Wigren, Torbjörn
    Ericsson.
    Nonlinear system identification of the dissolved oxygen to effluent ammonia dynamics in an activated sludge process2017In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 3917-3922Article in journal (Refereed)
    Abstract [en]

    Aeration of biological reactors in wastewater treatment plants is important to obtain a high removal of soluble organic matter as well as for nitrification but requires a significant use of energy. It is hence of importance to control the aeration rate, for example, by ammonium feedback control. The goal of this paper is to model the dynamics from the set point of an existing dissolved oxygen controller to effluent ammonia using two types of system identification methods for a Hammerstein model, including a newly developed recursive variant. The models are estimated and evaluated using noise corrupted data from a complex mechanistic model (Activated Sludge Model no.1). The performance of the estimated nonlinear models are compared with an estimated linear model and it is shown that the nonlinear models give a significantly better fit to the data. The resulting models may be used for adaptive control (using the recursive Hammerstein variant), gain-scheduling control, L2 stability analysis, and model based fault detection.

  • 3.
    Mattsson, Per
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.
    Zachariah, Dave
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Björsell, Niclas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.
    Flexible Models for Smart Maintenance2019In: Proceedings 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, 2019, p. 1772-1777Conference paper (Refereed)
    Abstract [en]

    Smart maintenance strategies are becoming increasingly important in the industry, and can contribute to environmentally and economically sustainable production. In this paper a recently developed latent variable framework for nonlinear-system identification is considered for use in smart maintenance. A model is first identified using data from a system operating under normal conditions. Then the identified model is used to detect when the system begins to deviate from normal behavior. Furthermore, for systems that operate on separate batches (units), we develop a new method that identifies individual models for each batch. This can be used both to detect anomalous batches and changes in the system behavior. Finally, the two methods are evaluated on two different industrial case studies. In the first, the purpose is to detect fouling in a heat exchanger. In the second, the goal is to detect when the tool in a wood moulder machine should be changed.

  • 4.
    Mattsson, Per
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Zachariah, Dave
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Stoica, Petre
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Identification of cascade water tanks using a PWARX model.2018In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 106, p. 40-48Article in journal (Refereed)
    Abstract [en]

    In this paper we consider the identification of a discrete-time nonlinear dynamical model for a cascade water tank process. The proposed method starts with a nominal linear dynamical model of the system, and proceeds to model its prediction errors using a model that is piecewise affine in the data. As data is observed, the nominal model is refined into a piecewise ARX model which can capture a wide range of nonlinearities, such as the saturation in the cascade tanks. The proposed method uses a likelihood-based methodology which adaptively penalizes model complexity and directly leads to a computationally efficient implementation.

  • 5.
    Mattsson, Per
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Zachariah, Dave
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Stoica, Petre
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Recursive nonlinear-system identification using latent variables2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 93, p. 343-351Article in journal (Refereed)
    Abstract [en]

    In this paper we develop a method for learning nonlinear system models with multiple outputs and inputs. We begin by modeling the errors of a nominal predictor of the system using a latent variable framework. Then using the maximum likelihood principle we derive a criterion for learning the model. The resulting optimization problem is tackled using a majorization–minimization approach. Finally, we develop a convex majorization technique and show that it enables a recursive identification method. The method learns parsimonious predictive models and is tested on both synthetic and real nonlinear systems.

  • 6.
    Medvedev, Alexander
    et al.
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Zhusubaliyev, Zhanybai T.
    Department of Computer Science, Southwest State University, Kursk, Russian Federation.
    Avrutin, Viktor
    Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany.
    Nonlinear dynamics and entrainment in a continuously forced pulse-modulated model of testosterone regulation2018In: Nonlinear dynamics, ISSN 0924-090X, E-ISSN 1573-269X, Vol. 94, no 2, p. 1165-1181Article in journal (Refereed)
    Abstract [en]

    Dynamical behaviors arising in a previously developed pulse-modulated mathematical model of non-basal testosterone regulation in the human male due to continuous exogenous signals are studied. In the context of endocrine regulation, exogenous signals represent, e.g., the influx of a hormone replacement therapy drug, the influence of the circadian rhythm, and interactions with other endocrine loops. This extends the scope of the autonomous pulse-modulated models of endocrine regulation to a broader class of problems, such as therapy optimization, but also puts it in the context of biological rhythms studied in chronobiology. The model dynamics are hybrid since the hormone metabolism is suitably captured by a continuous description and the control feedback is implemented in a discrete (i.e., event-based) manner by the hypothalamus of the brain. It is demonstrated that the endocrine loop with an exogenous signal entering the continuous part can be equivalently described by proper modifications in the pulse modulation functions of the autonomous model. The cases of a constant and a harmonic exogenous signal are treated in detail and illustrated by the results of bifurcation analysis. According to the model, adding a constant exogenous signal only reduces the mean value of testosterone, which result pertains to the effects of hormone replacement therapies under intact endocrine feedback regulation. Further, for the case of a single-tone harmonic positive exogenous signal, bistability and quasiperiodicity arise in the system. The convergence to either of the stationary solutions in a bistable regime is shown to be controlled by the phase of the exogenous signal thus relating this transition to the phenomenon of jet lag.

  • 7.
    Olsson, Fredrik
    et al.
    Department of Information Technology, Uppsala University, Sweden.
    Halvorsen, Kjartan
    Department of Information Technology, Uppsala University, Sweden; Department of Mecatronics, Tecnológico de Monterrey, Mexico.
    Zachariah, Dave
    Department of Information Technology, Uppsala University, Sweden.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Identification of Nonlinear Feedback Mechanisms Operating in Closed Loop using Inertial Sensors2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 473-478Article in journal (Refereed)
    Abstract [en]

    In this paper we study the problem of identifying linear and nonlinear feedback mechanisms, or controllers, operating in closed loop. A recently developed identification method for nonlinear systems, the LAVA method, is used for this purpose. Identification data is obtained from inertial sensors, that provide information about the movement of the system, in the form of linear acceleration and angular velocity measurements. This information is different from the information that is available to the controller to be identified, which makes use of unknown internal sensors instead. We provide two examples, a simulated neuromuscular controller in standing human balance, and a lead-filter controlling a physical position servo using a DC motor. Both linear and nonlinear controllers are used in the examples. We show that the LAVA method is able to identify sparse, parsimonious models of the controllers.

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