The paper deals with the problem of estimating an unknown input distribution matrix for non-linear discrete-time stochastic systems. In particular, it is shown how to use the unscented Kalman filter as an unknown inpu...
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The paper deals with the problem of estimating an unknown input distribution matrix for non-linear discrete-time stochastic systems. In particular, it is shown how to use the unscented Kalman filter as an unknown input filter. Subsequently, an analysis of the impact of unknown input decoupling on the fault detection is performed and a suitable fault detection condition is developed. Based on the achieved results, a numerical optimisation-based approach is proposed that can be used to estimate the unknown input distribution matrix. The final part of the paper presents an illustrative example with an induction motor, which confirms the performance of the proposed approach.
This paper gives new results on the design of iterative learning control laws that enables one step design of a stabilizing feedback controller in the time domain and a feedforward (learning) controller which guarante...
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ISBN:
(纸本)9781467345033
This paper gives new results on the design of iterative learning control laws that enables one step design of a stabilizing feedback controller in the time domain and a feedforward (learning) controller which guarantees convergence in the trial domain. The Kalman-Yakubovich-Popov lemma is central to the analysis and the resulting computations use convex optimization over linear matrix inequalities. An illustrative example is given based on the model of an experimental facility that has been used to compare alternative iterative learning control designs.
A cooperative ad hoc network is a collection of wireless devices that collaborate with each other to form a network system that dynamically adapts to changes in an unknown environment to achieve a given goal. Such a n...
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ISBN:
(纸本)9781612846842
A cooperative ad hoc network is a collection of wireless devices that collaborate with each other to form a network system that dynamically adapts to changes in an unknown environment to achieve a given goal. Such a network is often built from mobile devices. Mobility modeling is a critical element that influences the performance characteristics of an ad hoc network. In this paper, we describe an algorithm for calculating mobility patterns for mobile devices that is based on a cluster formation and an artificial potential function. Finally, we present the application of our mobility model to simulation-based design of a self-organizing and cooperative ad hoc network.
Self-organization mechanisms are used for building scalable systems consisting of a huge number of subsystems. In computer networks, self-organizing is especially important in ad hoc networking. A self-organizing ad h...
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In this introduction to the book, we discuss our current motivation for modeling and optimization applications involving network-based services. Our conceptual model of service science management and engineering (SSME...
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In recent years, driving fatigue and cognitive lapses have gained increasing attentions in the fields of public security, especially regarding the safe manipulation of vehicles. Studies have explored the relation betw...
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In recent years, driving fatigue and cognitive lapses have gained increasing attentions in the fields of public security, especially regarding the safe manipulation of vehicles. Studies have explored the relation between electroencephalogram (EEG) and driving behavior and several of them further proposed effective approaches (e.g., auditory feedback) to arouse subjects from drowsiness. However, these studies were performed under laboratory-oriented configurations using tethered, ponderous EEG equipment. In real environments, the setup of bulky cognitive monitoring equipment with a long-prep time is not feasible. Therefore, this study extends previous laboratory work by developing an on-line Drowsiness Monitoring and Management (DMM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. The DMM system can continuously observe EEG dynamics, deliver arousing feedback to users experiencing momentary cognitive lapses, and assess the efficacy of the feedback in near real-time.
The paper deals with the problem of designing observers for a class of discrete-time nonlinear systems with an unknown input. In particular, with the use of the Lyapunov method, a design procedure of an asymptotically...
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This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. Thi...
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ISBN:
(纸本)9781467320658
This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. This adaptive optimal control method finds in real-time approximations of the optimal value and the Stackelberg-equilibrium solution, while also guaranteeing closed-loop stability. The optimal-adaptive algorithm is implemented as a separate actor/critic parametric network approximator structure for every player, and involves simultaneous continuous-time adaptation of the actor/critic networks. Novel tuning algorithms are given for the actor/critic networks. The convergence to the closed-loop Stackelberg equilibrium is proven and stability of the system is also guaranteed. A simulation example shows the effectiveness of the new online algorithm.
This paper develops a new set of stability conditions for asymptotic stability of two-dimensional linear systems described by Roesser and Fornasini-Marchesini state-space models through extensive use of the Kalman-Yak...
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This paper develops a new set of stability conditions for asymptotic stability of two-dimensional linear systems described by Roesser and Fornasini-Marchesini state-space models through extensive use of the Kalman-Yakubovich-Popov lemma. The resulting tests are formulated in terms of a convex optimization problem over linear matrix inequality constraints. Testing the resulting conditions only requires computations on matrices with constant entries with consequent computational load advantages when compared with alternatives, especially when direct extension to stabilizing control law design is required. Illustrative numerical examples are also given.
This paper describes research towards the development of a robotic system for automated welded joint testing. The tests are often carried out manually by skilled personnel. Automating the inspection process would redu...
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