In the note two recursive algorithms recovering the nonlinearity in Hammerstein systems are proposed. The algorithms are based on Haar wavelet orthogonal series kernels and are of the simple generic standard form: whe...
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In the note two recursive algorithms recovering the nonlinearity in Hammerstein systems are proposed. The algorithms are based on Haar wavelet orthogonal series kernels and are of the simple generic standard form: where κ k ( x ) is an algorithm-dependent weighting factor. Convergence of both algorithms is examined for continuous and discontinuous nonlinearities and the convergence rates are established. Stability of the algorithms is also shown. Their performances for small numbers of measurements are numerically compared.
The safety problem in multi-vehicle systems seeks to establish collision-free and live vehicle motion, and it is a prominent problem for many configurations of these environments. Past work studying this problem in th...
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ISBN:
(纸本)9781424450381;9781424450404
The safety problem in multi-vehicle systems seeks to establish collision-free and live vehicle motion, and it is a prominent problem for many configurations of these environments. Past work studying this problem in the context of free-range vehicular systems through abstractions based on Resource Allocation System (RAS) theory, has implicitly assumed that its resolution through maximally permissive supervision is NP-hard, and therefore, it has typically pursued suboptimal (i.e., more restrictive) solutions. The work presented in this paper offers formal proof to this implicit assumption, closing the apparent gap in the existing literature.
In the paper a multicontroller-based switchable control system structure is proposed to control nonlinear MIMO plants. The considered structure contains a set of linear feedback controllers operating together with an ...
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In the paper a multicontroller-based switchable control system structure is proposed to control nonlinear MIMO plants. The considered structure contains a set of linear feedback controllers operating together with an additional, statically decoupled loop of the control system. The nonlinear model of a drilling vessel in three degrees of freedom (3DOF) on the sea surface is used as a MIMO plant to be controlled. The system synthesis is carried out by linearization of the adopted nonlinear plant model at its nominal “operating points” that depend on the preset ship yaw angle and the velocity of the see current. Performance of the proposed control systems is illustrated by examples of simulation results carried out in MATLAB/Simulink using the nonlinear model of low-frequency (LF) motions of WIMPEY SEALAB drilling vessel.
In this paper we analyze stability properties of multi-agent control system in a cluttered environment with an artificial potential based on bell-shaped functions. In our approach attractive and repulsive forces creat...
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In this paper we analyze stability properties of multi-agent control system in a cluttered environment with an artificial potential based on bell-shaped functions. In our approach attractive and repulsive forces created by potential gradient have the same form which allows definition of target formation that is parameter invariant. Due to the fact that agents are identical, the proposed structure of formation potential is invariant to the interchange of agents configurations, hence, target in which particular agent would eventually end up, depends only on formation initial condition and environment structure (obstacles). We show that position of unwanted stable equilibria can be controlled by parameters that define elementary potential functions. This fact has been used for synthesis of an adaptation algorithm, such that arrival of agents at required formation is guarantied. Simulation results, presented at the end of the paper, confirm correctness of the proposed control scheme.
In this paper we show the process of a class of algorithms parallelization which are used in digital signal processing. We present this approach on the instance of the popular LMS algorithm which is used in noise redu...
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In this paper we show the process of a class of algorithms parallelization which are used in digital signal processing. We present this approach on the instance of the popular LMS algorithm which is used in noise reduction, echo cancelation problems and digital signal processing in general. We propose an approach which uses a GPGPU technology. Parallel approach allows us decomposing the problem into a number of smaller ones, which can be computed faster. Obtained results, especially increase of speed and efficiency, show that the parallel method implemented on GPU is much more effective than other existing procedures and it can be used in the real-time systems.
job shop problem. A main idea of the proposed neighborhood is to execute a ‘long shot’ of an operation from the current operation’s machine to another machine of the same type, and then to the make a small move by ...
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job shop problem. A main idea of the proposed neighborhood is to execute a ‘long shot’ of an operation from the current operation’s machine to another machine of the same type, and then to the make a small move by using a local optimization algorithm without changing operationsto-machines assignment. We call this method ‘the golf neighborhood’. Computational experiments executed on the benchmark instances from the literature show the efficiency of this solution.
Performance boosting of modern computing systems is constrained by the chip/circuit power dissipation. Dynamic voltage scaling (DVS) has been applied for reducing the energy consumption by dynamically changing the sup...
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ISBN:
(纸本)9781424481927
Performance boosting of modern computing systems is constrained by the chip/circuit power dissipation. Dynamic voltage scaling (DVS) has been applied for reducing the energy consumption by dynamically changing the supply voltage. One can optimistically apply greedy online DVS scheduling algorithms by considering only the events that have arrived in the system. However, this might require a speed that is beyond a system's capability. Alternatively, one can pessimistically use a conservative speed to ensure timing guarantees, which might consume an excessive amount of energy as events might be processed faster than necessary. This paper presents an adaptive scheme that combines these two strategies for the scheduling of arbitrary event streams. The proposed adaptive DVS scheduler chooses the execution speed dynamically as long as it is below a certain threshold. Once the speed exceeds this threshold, the proposed scheduler operates at a constant (pessimistic) speed for guaranteeing the feasibility. The computation of the threshold speed is, however, not straight-forward. For deriving it, we make use of a framework based on timed model checking because the scheduler is strongly state-dependent. The resulting analysis framework allows to obtain the threshold speed for the proposed adaptive DVS scheduling algorithm such that both timing and speed constraints are guaranteed to be met and at the same time an energy-efficient execution is ensured.
Dynamic Voltage Scaling (DVS) has been widely used for decreasing the dynamic power dissipation of processors. For real-time systems, DVS techniques have been developed that permit to meet the timing constraints of mu...
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Dynamic Voltage Scaling (DVS) has been widely used for decreasing the dynamic power dissipation of processors. For real-time systems, DVS techniques have been developed that permit to meet the timing constraints of multiple real-time tasks and at the same time reduce the overall dynamic energy consumption. Known methods for static priority DVS scheduling are, however, either restricted to simple periodic/sporadic task release patterns or presume full a priori knowledge of task release times. Moreover, none of the present approaches considers the optimization of task priorities for reducing the energy consumption. In this paper we explore how to determine the static priorities and individual execution speeds (supply voltages) of multiple tasks with non-deterministic release times bounded by arrival curves such that the energy consumption is reduced and the real-time constraints are met. The result are different heuristics for the design of DVS-based real-time systems with static priorities. We show that the proposed methodology leads to energy-efficient system designs and demonstrate the applicability of the approach by means of experiments.
In this paper, we show that by using two adaptive neural networks (NNs), each of which is tailored for a specific task, the tracking performance of the hard-disk-drive (HDD) actuator can be significantly improved. The...
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