Automation and Remote Control最新文献

This paper explores the problem of influencing the environment by a group of autonomous robots through the creation and use of road infrastructure. The model object is ant roads (trails). We identify the main aspects of the behavior of different ant species in the process of collective foraging, and actions that together lead to the appearance of a phenomenon that the observer perceives as an ant road. We develop and describe an animat behavior model in the process of arranging a route. We define a list of mechanisms, a set of sensory capabilities, and effectors that are necessary for the robot to implement options for arranging the route. The results of simulation modeling for solving the foraging problem with route clearing are consistent with theoretical models. The simulation results confirm our assumption that the route arrangement can be carried out by individual efforts of animats (robots) and without the need to organize joint actions.

This paper considers linear multivariable systems with physical parameters varying from their known nominal values in an arbitrary and nonstationary manner. The plant is subjected to polyharmonic external disturbances containing an arbitrary number of unknown frequencies with unknown amplitudes having a bounded sum. The problem is to design a controller that robustly stabilizes the closed loop system and ensures desired errors for the controlled variables of the plant with nominal parameters in the steady-state mode. The system equations of the original problem are represented in the (W, Λ, K)-form; for this form, the standard H_∞ optimization problem is stated and solved. The desired accuracy of the system is achieved by analytically assigning the weight matrix of the controlled variables. The controller design method is illustrated by an example of solving a well-known benchmark problem.

The considered problem is to simultaneously stabilize a family of second order linear systems by static linear state feedback when applied to switched systems. The proposed synthesis approach is based on a known design method where a static regulator is found as a solution to the linear programming problem. This regulator makes all matrices from the family forming switched systems superstable in the closed loop state, which in turn guarantees exponential stability of the switched system. This approach is generalized for the case where not all matrices in the family can simultaneously be made superstable: for non-superstabilizable matrices one determines using D-decomposition linear bounds on the set of stabilizing regulators, which are used in the linear programming problem. The designed switched system properties are briefly studied. An example of a design problem solution using the proposed approach is presented.

This paper considers filtering for linear systems subjected to persistent exogenous disturbances. The filtering quality is characterized by the size of the bounding ellipsoid that contains the estimated output of the system. A regular approach is proposed to solve the nonfragile filtering problem. This problem consists in designing a filter matrix that withstands admissible variations of its coefficients. The concept of invariant ellipsoids is applied to reformulate the original problem in terms of linear matrix inequalities and reduce it to a parametric semidefinite programming problem easily solved numerically. This paper continues the series of author’s research works devoted to filtering under nonrandom bounded exogenous disturbances and measurement errors.

This paper demonstrates that robust control based on only a priori information about the object’s uncertainty can be significantly improved through the additional use of experimental data. Generalized H_∞-optimal controllers are designed for an unknown linear time-varying system on a finite horizon. These controllers optimize the damping level of exogenous and/or initial disturbances as well as the maximum deviation of the terminal state of the system. The design method does not require the persistent excitation condition or the rank condition, which ensure the identifiability of the system. As a result, the amount of experimental data can be significantly reduced.

This paper is dedicated to an optimization problem. Let A, B ⊂ ({{mathbb{R}}^{n}}) be compact convex sets. Consider the minimal number t⁰ > 0 such that t⁰B covers A after a shift to a vector x⁰ ∈ ({{mathbb{R}}^{n}}). The goal is to find t⁰ and x⁰. In the special case of B being a unit ball centered at zero, x⁰ and t⁰ are known as the Chebyshev center and the Chebyshev radius of A. This paper focuses on the case in which A and B are defined with their black-box support functions. An algorithm for solving such problems efficiently is suggested. The algorithm has a superlinear convergence rate, and it can solve hundred-dimensional test problems in a reasonable time, but some additional conditions on A and B are required to guarantee the presence of convergence. Additionally, the behavior of the algorithm for a simple special case is investigated, which leads to a number of theoretical results. Perturbations of this special case are also studied.

The time-optimal control problem for an arbitrary number of nonsynchronous oscillators with a limited scalar control is considered. An analytical investigation of the problem is performed. The property of strong accessibility and global controllability is proved, and a program control is found that brings the system from the origin to a fixed point in the shortest time. Trajectories satisfying both the motion equations of the system and the additional conditions based on the matrix nondegeneracy conditions of the relay control have been found for bringing a group of oscillators to the origin. Two classification methods of trajectories according to the number of control switchings are compared: the one based on the necessary extremum conditions and the Neustadt–Eaton numerical algorithm.

Coordination in multiagent systems with information influences is studied. In particular, a model of multiagent system in which information is transmitted with a constant delay for all agents is studied. Using the Nyquist criterion applied by Tsypkin for systems with delayed feedback, a formula is obtained for the boundary value of time-delay which is included as a parameter in the system of differential equations with an asymmetric constant Laplacian matrix. The condition of independence of stability from time-delay is founded. The results obtained generalize some previously results and can be applied in coordination analysis in a multiagent systems with complex protocol.

We consider a class of well-known high-order trinomial linear difference equations and analyze the non-asymptotic behavior of their solutions under non-zero initial conditions from the unit box. It is shown that, for certain subsets of coefficients in the stability domain, there always exist initial conditions leading to peak, a large deviation of solutions from the equilibrium position, and that these deviations may take arbitrarily large values. Various special cases are studied, numerical examples are presented.

The paper is devoted to the analysis of the feasibility domain of electric power systems. The problems of calculating feasible and marginal regimes of power systems, analyzing the geometry of the feasibility domain, and generating samples in this region are considered. Parallels are drawn with the works of B.T. Polyak on the analysis of the image of a quadratic map, modification of the Newton method and the development of methods for generating asymptotically uniform samples in areas with complex geometry. Particular attention is paid to Newton’s method with the transversality condition (TENR), its application for constructing a boundary oracle procedure and utilization for generating samples in the power system feasibility domain.