This paper develops a constructive time-delay approach to averaging for gradient-based extremum seeking (ES) control of nonlinear static maps of non-quadratic form. Under the assumption that some prior knowledge of th...
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This paper develops a constructive time-delay approach to averaging for gradient-based extremum seeking (ES) control of nonlinear static maps of non-quadratic form. Under the assumption that some prior knowledge of the nonlinear map with its derivatives is available, for the first time, we derive a quantitative analysis for ES close-loop systems with upper bounds on the tuning parameter that preserves the exponential stability and on the convergence error of extremum seeking. By transforming the ES system into a time-delay neutral type system with distributed delays, the developed method gives an accurate perturbed system of ES without employing any approximate calculation, and suggests a direct Lyapunov-Krasovskii approach in the form of linear matrix inequalities (LMIs), for the transformed time-delay plant to derive efficient stability conditions.
作者:
Langyu LiInstitute of Cyber-system and Control
College of Control Science and Engineering Zhejiang University Hangzhou Zhejiang 310027 China and State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou Zhejiang 310027 China
Hamiltonian simulation is one of the most promising applications of quantum computers, and the product formula is one of the most important methods for this purpose. Previous related work has mainly focused on the wor...
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Hamiltonian simulation is one of the most promising applications of quantum computers, and the product formula is one of the most important methods for this purpose. Previous related work has mainly focused on the worst-case, average-case, or actual-case scenarios. In this work we consider the simulation error under a fixed observable. Specifically, errors that commute with this observable become less significant. To illustrate this point, we define the observation error as the expectation under the observable and provide a commutativity-based upper bound using the Baker-Campbell-Hausdorff formula. Furthermore, we observe that the evolution order plays a critical role in determining the observation error. By leveraging a simulated annealing algorithm, we design an evolution order optimization algorithm, to identify an order that enhances commutativity with the observable, where the observation error indicated by this upper bound can be significantly compressed. In the experiment with the Heisenberg model, the observation bound compresses the Trotter number by nearly half compared to recent commutator bounds. The experiment on the hydrogen molecule Hamiltonian demonstrates that optimizing the order can lead to nearly half the reduction in the Trotter number.
This paper delves into the investigation of a distributed aggregative optimization problem within a network. In this scenario, each agent possesses its own local cost function, which relies not only on the local state...
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An analytical method,called the symplectic mathematical method,is proposed to study the wave propagation in a spring-mass chain with gradient arranged local resonators and nonlinear ground *** with the linearized pert...
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An analytical method,called the symplectic mathematical method,is proposed to study the wave propagation in a spring-mass chain with gradient arranged local resonators and nonlinear ground *** with the linearized perturbation approach,the symplectic transform matrix for a unit cell of the weakly nonlinear graded metamaterial is derived,which only relies on the state *** results of the dispersion relation obtained with the symplectic mathematical method agree well with those achieved by the Bloch *** is shown that wider and lower frequency bandgaps are formed when the hardening nonlinearity and incident wave intensity ***,the displacement response and transmission performance of nonlinear graded metamaterials with finite length are *** dual tunable effects of nonlinearity and gradation on the wave propagation are explored under different excitation *** small excitation frequencies,the gradient parameter plays a dominant role compared with the *** reason is that the gradient tuning aims at the gradient arrangement of local resonators,which is limited by the critical value of the local resonator *** contrast,for larger excitation frequencies,the hardening nonlinearity is dominant and will contribute to the formation of a new bandgap.
This paper introduces a learning-based framework for robot adaptive manipulating the object with a revolute joint in unstructured environments. We concentrate our discussion on various cabinet door opening tasks. To i...
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Distance measurements demonstrate distinctive scalability when used for relative state estimation in large-scale multi-robot systems. Despite the attractiveness of distance measurements, multi-robot relative state est...
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Distance measurements demonstrate distinctive scalability when used for relative state estimation in large-scale multi-robot systems. Despite the attractiveness of distance measurements, multi-robot relative state estimation based on distance measurements raises a tricky optimization problem, especially in the context of large-scale systems. Motivated by this, we aim to develop specialized computational techniques that enable robust and efficient estimation when deploying distance measurements at scale. We first reveal the commonality between the estimation problem and the one that finds realization of a sensor network, from which we draw crucial lesson to inspire the proposed methods. However, solving the latter problem in large-scale (still) requires distributed optimization schemes with scalability natures, efficient computational procedures, and fast convergence rates. Towards this goal, we propose a complementary pair of distributed computational techniques with the classical block coordinate descent (BCD) algorithm as a unified backbone. In the first method, we treat Burer-Monteiro factorization as a rank-restricted heuristic for rank-constrained semidefinite programming (SDP), where a specialized BCD-type algorithm that analytically solve each block update subproblem is employed. Although this method enables robust and (extremely) fast recovery of estimates from initial guesses, it inevitably fails as the initialization becomes disorganized. We therefore propose the second method, derived from a convex formulation named anchored edge-based semidefinite programming (ESDP), to complement it, at the expense of a certain loss of efficiency. This formulation is structurally decomposable so that BCD can be naturally employed, where each subproblem is convex and (again) solved exactly. Since in both methods BCD seeks to solve the subproblem exactly, fewer iterations, as well as the number of communication rounds, are expected. Extensive evaluation on 2D and 3D probl
Owing to uncertainties in both kinematics and dynamics, the current trajectory tracking framework for mobile robots like spherical robots cannot function effectively on multiple terrains, especially uneven and unknown...
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With the development of modern logistics industry, automated warehouses are becoming more and more widely used. An automated guided vehicle (AGV) is often used to carry goods in warehouse. Under specific limitations o...
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With the rapid development of global container business, there are higher requirements for the operation efficiency of container terminals. The vehicle dispatching system is an important link in the operation of conta...
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With the continuous growth of port container throughput, it is difficult to meet the port production demand by simply configuring automation equipments to improve the operation efficiency of machinery. The container t...
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