In this paper we present a novel switching function for multiplicative watermarking systems. The switching function is based on the algebraic structure of elliptic curves over finite fields. The resulting function all...
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In this paper we present a novel switching function for multiplicative watermarking systems. The switching function is based on the algebraic structure of elliptic curves over finite fields. The resulting function allows for both watermarking generator and remover to define appropriate system parameters, sharing only limited information, namely a private key. We prove that the resulting watermarking parameters lead to a stable watermarking scheme. Copyright (C) 2022 The Authors.
This work bounds extreme values of state functions for a class of input-affine continuous-time systems that are affected by polyhedral-bounded uncertainty. Instances of these systems may arise in data-driven peak esti...
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This work bounds extreme values of state functions for a class of input-affine continuous-time systems that are affected by polyhedral-bounded uncertainty. Instances of these systems may arise in data-driven peak estimation, in which the state function must be bounded for all systems that are consistent with a set of state-derivative data records corrupted under L-infinity bounded noise. Existing occupation measure-based methods form a convergent sequence of outer approximations to the true peak value, given an initial set, by solving a hierarchy of semidefinite programs in increasing size. These techniques scale combinatorially in the number of state variables and uncertain parameters. We present tractable algorithms for peak estimation that scale linearly in the number of faces of the uncertainty-bounding polytope rather than combinatorially in the number of uncertain parameters by leveraging convex duality and a theorem of alternatives (facial decomposition). The sequence of decomposed semidefinite programs will converge to the true peak value under mild assumptions (convergence and smoothness of dynamics). Copyright (C) 2022 The Authors.
Vehicle parameter estimation is an identification problem which is almost exclusively solved with least squares methods. In practical applications, some prerequisites for ordinary least squares are not satisfied, such...
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Vehicle parameter estimation is an identification problem which is almost exclusively solved with least squares methods. In practical applications, some prerequisites for ordinary least squares are not satisfied, such as the assumption of an error-free regressor and independent and normally distributed noise. In this work, three parameter estimators for dynamic systems are presented which address these problems: a total least squares estimator to deal with regressor errors, and a robust M-type Kalman filter for long-tailed error distributions from the literature are implemented. As the main contribution, a disturbance observer parameter estimator (DOPE) is proposed which observes a disturbance process instead of assuming independent noise in addition to the parameter estimation. The estimators are applied to a mass and friction identification problem for an electric tractor on a large number of experiments. The DOPE has the lowest median estimation error and the lowest sensitivity to bad measurement data. The results show that the disturbance observer is a valuable tool for practical Kalman filter parameter estimation. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)
Fault tolerance and constant, remote control of the process becomes important because of a continuous increase in complexity and high-performance demand for industrial systems. Therefore, there are developed advanced ...
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Fault tolerance and constant, remote control of the process becomes important because of a continuous increase in complexity and high-performance demand for industrial systems. Therefore, there are developed advanced controlsystems that can detect and identify faults without being present at the site. This article presents the methodology of designing a PLC based fault isolation and remote monitoring system using the Industrial Internet of Things technologies. An algorithm of fault detection and isolation based on Unknown Input Observer and its implementation on a PLC controller are described and analyzed based on the simulated level control process in a three-tank system. The article contains a description of multiple technologies related to the concept of Industry 4.0 that can increase the performance of modern industrial systems. Copyright (C) 2022 The Authors.
In this paper, the problem of stability, recursive feasibility and convergence conditions of stochastic model predictive control for linear discrete-time systems affected by a large class of correlated disturbances is...
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In this paper, the problem of stability, recursive feasibility and convergence conditions of stochastic model predictive control for linear discrete-time systems affected by a large class of correlated disturbances is addressed. A stochastic model predictive control that guarantees convergence, average cost bound and chance constraint satisfaction is developed. The results rely on the computation of probabilistic reachable and invariant sets using the notion of correlation bound. This control algorithm results from a tractable deterministic optimal control problem with a cost function that upper-bounds the expected quadratic cost of the predicted state trajectory and control sequence. The proposed methodology only relies on the assumption of the existence of bounds on the mean and the covariance matrices of the disturbance sequence. Copyright (C) 2022 The Authors.
This paper addresses the development of the robotic vessel setup for academic purposes. The setup provides experimental testing of algorithms for computer vision to measure coordinates of the vessel establishing the f...
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This paper addresses the development of the robotic vessel setup for academic purposes. The setup provides experimental testing of algorithms for computer vision to measure coordinates of the vessel establishing the feedback and motion control based on this feedback steering the vessel towards the given reference. The paper describes the structure of the setup and discusses problems and approaches relevant to dynamic positioning. The developed setup can be helpful for students in gaining hands-on experience in implementing the computer vision and motion control algorithms to the scaled but still real-life application. Copyright (C) 2022 The Authors.
The pandemic period has forced schools to find alternative solutions, particularly to be able to carry out laboratory activities. In addition to the possibility of organizing remote laboratories, in SUPSI we have anal...
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The pandemic period has forced schools to find alternative solutions, particularly to be able to carry out laboratory activities. In addition to the possibility of organizing remote laboratories, in SUPSI we have analyzed the possibility of creating small boards to be made available to students in order to carry out practical activities at home. Therefore, a board was created with 4 simple processes, which however offer the possibility to deepen many topics related to control, with activities ranging from parametric modeling and identification, up to advanced controllers (LQR, MPC, etc.). After the choice of 4 possible controlsystems, we proceeded to the theoretical description of the processes and the drafting of the first solutions. Copyright (C) 2022 The Authors.
作者:
Feng, YunWang, YaonanZhang, YazhiHunan Univ
Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ
Natl Engn Res Ctr Robot Visual Percept & Control Changsha 410082 Hunan Peoples R China Hunan Inst Engn
Coll Elect & Informat Engn Xiangtan 411104 Peoples R China
Different from the traditional model-based fault diagnosis paradigm which is established upon the well-known observer design and analysis, a novel data-driven framework is proposed by combing systems modeling with fau...
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Different from the traditional model-based fault diagnosis paradigm which is established upon the well-known observer design and analysis, a novel data-driven framework is proposed by combing systems modeling with fault detection for a class of 1-D unknown distributed parameter systems. The key idea is to transfer the on-line modeling error into the residual signal for fault detection. The proposed methodology only utilizes the I/O data and does not require extra knowledge of the system model, which increases its usability at large. Numerical simulations on a commonly used benchmark are presented for method validation. Copyright (C) 2022 The Authors.
This paper proposes a novel fault detection method for distributed uncertain systems based on moving horizon estimation (MHE). In the proposed design, the system is distributed into multiple subsystems and local MHEs ...
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This paper proposes a novel fault detection method for distributed uncertain systems based on moving horizon estimation (MHE). In the proposed design, the system is distributed into multiple subsystems and local MHEs are designed for each subsystem to estimate the local states. Interval arithmetic is applied to describe the unknown-but-bounded uncertainties. Based on this, a new MHE problem is formulated which incorporates the uncertainties. Data loss in the communication is also handled. The solution of the MHE problem provides an optimal estimate of the interval-valued states. Faults in the subsystems are detected by evaluating the result of the intersection of the calculated states with the local uncertain measurements. Finally, the proposed fault detection method is demonstrated using measured data of a nonlinear three-tank system. Furthermore, this method is compared with the classical MHE-based global approach. Copyright (C) 2022 The Authors.
In this paper we propose the use of a temperature control problem as a method to introduce fractional modeling and control to students. The control problem is based on a simple laboratory setup: a heated aluminum rod ...
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In this paper we propose the use of a temperature control problem as a method to introduce fractional modeling and control to students. The control problem is based on a simple laboratory setup: a heated aluminum rod that can be conveniently modeled from first principles by using fractional systems. The construction of the experiment only requires cheap components and can be easily replicated. Once a model is obtained, the student can control the temperature of the rod by using different control algorithms, fractional and integer, thus experiencing first-hand the benefits of fractional control and, more in general, exploring advanced control paradigms. Copyright (C) 2022 The Authors.
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