In this paper, an algorithm for the reconstruction of an outdoor environment using a mobile robot is presented. The focus of this algorithm is making the mapping process efficient by capturing the greatest amount of i...
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In this paper we describe a two-step scheme for approximate model checking of discrete time stochastic hybrid systems. In the first step, the stochastic hybrid system is approximated by a finite state Markov chain. In...
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Abstract A dual variational Bayes filter for states and parameter estimation in IDE based spatiotemporal dynamic systems is developed. Recursive updates are obtained from a restricted variational Bayesian perspective,...
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Abstract A dual variational Bayes filter for states and parameter estimation in IDE based spatiotemporal dynamic systems is developed. Recursive updates are obtained from a restricted variational Bayesian perspective, using a dual filtering formulation where parameters are allowed to evolve in time. The added benefit over conventional point estimate filters is that parameter distributions are readily available for one to take advantage of in the design of complex experiments or in adaptive control scenarios. The dual filter is evaluated in a simulation study and seen to perform favorably when compared to a standard SMC approach.
We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (D...
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Abstract In this paper an anti-slip predictive controller is designed and implemented in order to control the rear wheels of a V-PRA (Variable Powered Rear Axle) vehicle. The control algorithm is EPSAC, a Model based ...
Abstract In this paper an anti-slip predictive controller is designed and implemented in order to control the rear wheels of a V-PRA (Variable Powered Rear Axle) vehicle. The control algorithm is EPSAC, a Model based Predictive control (MPC) strategy. It uses explicitly a model of the system for the prediction of the future system output, in order to calculate the optimal control input which will bring the system to a required setpoint. The main goals of this predictive controller were setpoint trajectory following, disturbance rejection and maintain overall the stability of the V-PRA vehicle. Although the process is non-linear, being influenced by several parameters, linear discrete-time ARX models could be obtained based on system linearization around an operating point. An initial SISO controller was developed and tested, based on a Simulink model of the process. The control performances were tested successfully in presence of all kind of disturbances, denoting a robust controller.
In this paper,we derive in time domain the constitutive equation and relevant properties of the fractional order weighted distributed parameter Maxwell *** weight function can be replaced by the Fourier series,which l...
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In this paper,we derive in time domain the constitutive equation and relevant properties of the fractional order weighted distributed parameter Maxwell *** weight function can be replaced by the Fourier series,which leads to three types of fractional order distributed parameter *** inverse Laplace transformand asymptotic properties
In high-dimensional modelling cases, a fuzzy modelling approach based on the grid-partitioning of fuzzy sets always meets great challenges, as it cannot avoid the problem of introducing a huge number of fuzzy rules. T...
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In high-dimensional modelling cases, a fuzzy modelling approach based on the grid-partitioning of fuzzy sets always meets great challenges, as it cannot avoid the problem of introducing a huge number of fuzzy rules. To tackle this issue, a new grid-partitioning based fuzzy modelling paradigm is proposed in this paper to construct a compact fuzzy system by including 'short fuzzy rules', in which only a few but strategic premises are used. In the proposed approach, the generation of fuzzy rules is data-orientated, a consideration which can greatly reduce the computational complexity. A new framework for fuzzy reasoning and defuzzification is also devised, which employs some archived reference data to help choose the most suitable fuzzy rules. In material engineering, describing the behaviour of mechanical properties of alloys is often a high dimensional modelling problem, which involves the complexity of materials' chemical composites and their underlying physical processing mechanisms. In this paper, the proposed approach was successfully applied to generate models of ultimate tensile strength of alloy steel. Compared with the standard grid partitioning based fuzzy modelling paradigms, the new method shows an improvement in both complexity and interpretability. Compared with the clustering-based fuzzy modelling approaches, the proposed method can achieve the same accuracy level and is more transparent.
In the work presented in this paper Statistical Process control (SPC) techniques are applied to a model-based Fault Detection and Isolation (FDI) approach. The residuals, produced as outputs from the FDI system, are m...
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In the work presented in this paper Statistical Process control (SPC) techniques are applied to a model-based Fault Detection and Isolation (FDI) approach. The residuals, produced as outputs from the FDI system, are manipulated with typical SPC charts to improve the overall diagnosis process. The charts explained in this work: Shewhart control chart, Cumulative Sum (CUSUM) control chart and Exponentially Weighted Moving Average (EWMA) charts are able to accurately determine significant deviations in the residuals. The integration of model-based tools with SPC supervision can be a step towards robustness and effectiveness in fault detection. This scheme reduces the number of false alarms, which is an important aspect in FDI tasks, and can reduce the fault isolation time. This approach has been applied to a laboratory plant with real data, obtaining interesting results.
We study the existence of absolutely maximally entangled (AME) states in quantum mechanics and its applications to quantum information. AME states are characterized by being maximally entangled for all bipartitions of...
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We study the existence of absolutely maximally entangled (AME) states in quantum mechanics and its applications to quantum information. AME states are characterized by being maximally entangled for all bipartitions of the system and exhibit genuine multipartite entanglement. With such states, we present a parallel teleportation protocol which teleports multiple quantum states between groups of senders and receivers. The notable features of this protocol are that (i) the partition into senders and receivers can be chosen after the state has been distributed, and (ii) one group has to perform joint quantum operations while the parties of the other group only have to act locally on their system. We also prove the equivalence between pure state quantum secret sharing schemes and AME states with an even number of parties.
Earlier investigations show that the results of hazard identification (HAZID) and analysis (e.g. HAZOP or FMEA) can effectively be used for knowledge-based diagnosis of complex process systems in their steady-state op...
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