| 1. |
- Burdakov, S. F., et al.
(författare)
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Robust control of nonlinear mechanical systems using linear feedback
- 1999
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Ingår i: Automation and remote control. - NEW YORK, NY, USA. - 0005-1179 .- 1608-3032. ; 60:11, s. 1577-1586
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Tidskriftsartikel (refereegranskat)abstract
- A linear law of control of a mechanical system through drives nonrigidly connected to the system is suggested. The law involves measurement of the positions of links and angular velocities of drives and features a nonminimal-phase character of the transfer function. Stability conditions that remain valid with an increase in the gain are set zip. Results of the numerical modeling in solving problems of positioning anal tracking for robots (manipulators) are described.
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| 2. |
- Gholami, Omid, 1979-, et al.
(författare)
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Heuristic Algorithms to Maximize Revenue and the Number of Jobs Processed on Parallel Machines
- 2019
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Ingår i: Automation and remote control. - : MAIK NAUKA/INTERPERIODICA/SPRINGER. - 0005-1179 .- 1608-3032. ; 80:2, s. 297-316
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Tidskriftsartikel (refereegranskat)abstract
- A set of jobs has to be processed on parallel machines. For each job, there are given a release time and a due date and the job must be processed no later than its due date. If the job will be completed no later than the given due date, a benefit will be earned. Otherwise, this job will be rejected and the benefit will be discarded. The criterion under consideration is to maximize the weighted sum of the benefits and the number of jobs processed in time. Some properties of the objective function are found which allow to construct a optimal schedule. We develop a simulated annealing algorithm, a tabu search algorithm, and a genetic algorithm for solving this problem. The developed algorithms were tested on moderate and large instances with up to 500 jobs and 50 machines. Some recommendations are given showing how to use the obtained results and developed algorithms in production planning.
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| 3. |
- Krasheninnikov, Pavel V., et al.
(författare)
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Parameter Estimation for the Resulting Logical Channel Formed by Minimizing Channel Switching
- 2019
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Ingår i: Automation and remote control. - : Springer. - 0005-1179 .- 1608-3032. ; 80:2, s. 278-285
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Tidskriftsartikel (refereegranskat)abstract
- We propose a method for calculating the parameters of the resulting discrete channel for secondary users in cognitive radio systems formed by the algorithm for minimizing channel switchings. The availability of channel slots is defined by a simple Markov chain. We obtain mathematical expressions for determining the transition probabilities of a graph reduced to two states for any number of primary channels.
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| 4. |
- Ljung, Lennart
(författare)
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On Convexification of System Identification Criteria
- 2019
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Ingår i: Automation and remote control. - : MAIK NAUKA/INTERPERIODICA/SPRINGER. - 0005-1179 .- 1608-3032. ; 80:9, s. 1591-1606
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Tidskriftsartikel (refereegranskat)abstract
- System Identification is about estimating models of dynamical systems from measured input-output data. Its traditional foundation is basic statistical techniques, such as maximum likelihood estimation and asymptotic analysis of bias and variance and the like. Maximum likelihood estimation relies on minimization of criterion functions that typically are non-convex, and may cause numerical search problems and estimates trapped in local minima. Recent interest in identification algorithms has focused on techniques that are centered around convex formulations. This is partly the result of developments in semidefinite programming, machine learning and statistical learning theory. The development concerns issues of regular-ization for sparsity and for better tuned bias/variance trade-offs. It also involves the use of subspace methods as well as nuclear norms as proxies to rank constraints. A special approach is to look for difference-of-convex programming (DCP) formulations, in case a pure convex criterion is not found. Other techniques are based on Lagrangian relaxation and contraction theory. A quite different route to convexity is to use algebraic techniques to manipulate the model parameterizations. This article will illustrate all this recent development.
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