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Distributed Optimization Algorithms on Structurally Balanced Signed Networks |
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Wen Du, Yusheng Wei(University of North Texas, United States), Mingjun Du(Qilu University of Technology (Shandong Academy of Science), China) |
| In this paper, we consider the distributed optimization problem under structurally balanced signed graph. First, we convert the original distributed optimization problem into a conditional minimum problem under the condition that the graph is structurally balanced. Our goal is to find the saddle points of augmented Lagrange function. Inspired by the Lagrange multiplier method, we present our algorithms for both undirected graph and digraph, and show that our algorithms asymptotically converge to the global minimizer. Particularly, our algorithms for digraph can not only handle the weight balanced case but the weight unbalanced case. |
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Improved Combined Step-size Normalized Sign Algorithm with Novel Variable Mixing Factors |
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Minho Lee(POSTECH, Korea), Taesung CHO(POHANG UNIVERSITY OF SCIENCE AND TECHNOLOGY, Korea), Poogyeon Park(POSTECH, Korea) |
| This paper proposes novel variable mixing factors to combine two normalized sign algorithms robust against impulsive noises with improving the performance. The variable mixing factors resolve the trade-off problem between the convergence rate and steady-state misalignment by updating the mixing parameters at each iteration. The proposed variable mixing factors use a modified arctangent activation function and a modified rectified linear unit activation function used in various fields. These proposed mixing factors are updated by optimizing the absolute value of the system output error to get the robustness to impulsive noises. |
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A Simple Finite-time Position Tracking Controller for Servo Motor Systems |
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Ngo Phong Nguyen(UNIST, Korea), Hyondong Oh(Ulsan National Institute of Science and Technology, Korea), Jun Moon(Hanyang University, Korea) |
| This paper deals with the robust finite-time tracking control problem. First, a new simple finite-time tracking controller is developed for disturbed second-order systems. The stability of the proposed control scheme is analysed based on the Lyapunov stability theorem, and the finite-time convergence of the closed-loop system is proven. Then, we apply the designed framework to the position tracking control for servo motor systems under external disturbances and model uncertainties. Various simulation results are provided to illustrate the effectiveness of the proposed controller. |
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Patching Continuous-time Signals Using High-gain Observes and 3rd Order Splines |
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Jesus Alberto Meda-Campana(Instituto Politecnico Nacional, Mexico) |
| Under the assumptions that the reference signal is bounded, smooth and measurable for almost all t>=0, the main contribution of this work is to repair the continuous-time signal when disturbances or inherent measurement issues provoke the loss of a portion of such a signal. This, by constructing a high-gain observer to estimate the measurable signal and a spline to patch the lost or unreliable portion of the signal. |
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Adaptive Torque-based Vehicle Slip Control using Super-twisting Theorem for Steering Vehicle Control on Cornering Road |
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NORSHARIMIE MAT ADAM(Universiti Malaysia Pahang, Malaysia), ADDIE IRAWAN(Universiti Malaysia Pahang, Pekan, Pahang 26600, Malaysia 26600, Pekan, Pahang, Malaysia , Malaysia) |
| The inertia of vehicle's slip caused by oversteered is a crucial part that to be considered in vehicle dynamics and control system design. Kamaras et al. for example had emulated the environment friction force used by the vehicle's slip to design a slip control that can avoid disturbances. RSV is used as model plant in this research and the research is focusing on its velocity, inertia, and kinetic energy during maneuver in cornering road.
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Online Estimation of Mass and Moment of Inertia of Cargo Bike Payload using an Unscented Kalman Filter |
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Suvrath Pai, Benedikt Neuberger, Michael Buchholz(Ulm University, Germany) |
| The inertial properties of an electric cargo bike can vary greatly depending on the payload. Therefore, determination of its inertial properties is crucial for development of functional and reliable rider assistance systems. This paper presents an Unscented Kalman Filter (UKF) based algorithm, which estimates the mass, center of gravity and moment of inertia of the cargo load online. The force exerted by the load as well as the roll angle and roll acceleration of the cargo bike are provided as inputs to the algorithm. The developed algorithm is then validated against measurements on a test bench. Finally, the robustness of the estimation algorithm during dynamic scenarios is demonstrated. |
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