This paper shows how structured model order reduction can be applied to power systems. For power systems divided into a study area and an external area, the proposed algorithm can be used to reduce the external area t...
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ISBN:
(纸本)9781457710957
This paper shows how structured model order reduction can be applied to power systems. For power systems divided into a study area and an external area, the proposed algorithm can be used to reduce the external area to a low order linear system, while retaining the nonlinear description of the study system. The reduction of the external area is done in such a way that the study system is affected as little as possible. It is shown that a lower model order can be attained when information about the study system is taken into consideration, than if the external system is reduced independently of it.
In this article a new method for planning smooth and time-optimal trajectories for robot manipulators is proposed. Trajectory planning is considered as dynamic optimization problem in which the end-effector path as we...
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ISBN:
(纸本)9781457710957
In this article a new method for planning smooth and time-optimal trajectories for robot manipulators is proposed. Trajectory planning is considered as dynamic optimization problem in which the end-effector path as well as the limitations of the joint velocities, the actuator torques and the actuator torque rates are the constraints. These constraints transferred to the space of the path variable using the parametrized system dynamics border an admissible solution space in which time optimality and smoothness are defined. DAE models are derived to construct time-optimal trajectories inside the admissible solution space taking the maximum velocity curve and its properties into account.
We are interested in developing a multi-goal generator to provide detailed goal representations that help to improve the performance of the adaptive critic design (ACD). In this paper we propose a hierarchical structu...
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ISBN:
(纸本)9781467314886
We are interested in developing a multi-goal generator to provide detailed goal representations that help to improve the performance of the adaptive critic design (ACD). In this paper we propose a hierarchical structure of goal generator networks to cascade external reinforcement into more informative internal goal representations in the ACD. This is in contrast with previous designs in which the external reward signal is assigned to the critic network directly. The ACD control system performance is evaluated on the ball-and-beam balancing benchmark under noise-free and various noisy conditions. Simulation results in the form of a comparative study demonstrate effectiveness of our approach.
It is well known that competence in mathematics is essential for controlengineering modules and yet many students do not have the required competence. This paper gives an overview and evaluation of strategies in Shef...
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It is well known that competence in mathematics is essential for controlengineering modules and yet many students do not have the required competence. This paper gives an overview and evaluation of strategies in Sheffield for helping students engage with and learn mathematics. Evidence of the efficacy of the approach is also included.
This paper reviews triple mode predictive control for linear time invariant systems and considers the analogies with new approaches to conventional dual mode MPC algorithms deploying Laguerre polynomials. It is shown ...
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The paper generalises approaches to predictive control based on Laguerre and Kautz functions. It is shown that La- guerre and Kautz are special cases of generalised orthonor- mal basis functions and thus one can give ...
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ISBN:
(纸本)9780889868892
The paper generalises approaches to predictive control based on Laguerre and Kautz functions. It is shown that La- guerre and Kautz are special cases of generalised orthonor- mal basis functions and thus one can give a more gen- eral parameterisation using higher order orthonormal ba- sis functions. Specifically, a simple but efficient algorithm that uses generalised functions to parameterise the degrees of freedom in an optimal predictive control is presented. The efficacy of the proposed parameterisation within exist- ing predictive control algorithms that use a similar strategy, is demonstrated by examples.
This paper presents some implementation details of a three-phase to three-phase matrix converter prototype. The bidirectional semiconductor switches were built using discrete IGBTs and fast diodes. Design aspects such...
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This paper presents some implementation details of a three-phase to three-phase matrix converter prototype. The bidirectional semiconductor switches were built using discrete IGBTs and fast diodes. Design aspects such as protection against overvoltage and short-circuit, commutation process of bi-directional switches, and input filter are addressed in this paper.
The present work reports a sufficient condition for the consensus of a network of nonidentical Euler-Lagrange (EL) systems with variable time-delays in the communications. The EL-systems are controlled by simple Propo...
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ISBN:
(纸本)9781467320658
The present work reports a sufficient condition for the consensus of a network of nonidentical Euler-Lagrange (EL) systems with variable time-delays in the communications. The EL-systems are controlled by simple Proportional plus damping (P+d) schemes and the interconnection network is modeled as an undirected weighted graph. Additionally, for the case without delays, the paper reports a new Strict Lyapunov Function (SLF) for the closed-loop system. Experimental evidence, using three 3-Degrees-of-Freedom manipulators interconnected through the Internet, support the theoretical results of this paper.
We consider a dynamical formulation of network flows, whereby the network is modeled as a switched system of ordinary differential equations derived from mass conservation laws on directed graphs with a single origin-...
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ISBN:
(纸本)9781467320658
We consider a dynamical formulation of network flows, whereby the network is modeled as a switched system of ordinary differential equations derived from mass conservation laws on directed graphs with a single origin-destination pair and a constant inflow at the origin. The rate of change of the density on each link of the network equals the difference between the inflow and the outflow on that link. The inflow to a link is determined by the total flow arriving to the tail node of that link and the routing policy at that tail node. The outflow from a link is modeled to depend on the current density on that link through a flow function. Every link is assumed to have finite capacity for density and the flow function is modeled to be strictly increasing up to the maximum density. A link becomes inactive when the density on it reaches the capacity. A node fails if all its outgoing links become inactive, and such node failures can propagate through the network due to rerouting of flow. We prove some properties of these dynamical networks and study the resilience of such networks under distributed routing policies with respect to perturbations that reduce link-wise flow functions. In particular, we propose an algorithm to compute upper bounds on the maximum resilience over all distributed routing policies, and discuss examples that highlight the role of cascading failures on the resilience of the network.
To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learn...
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To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.
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