In this paper, PI control with input-output linearizaiton is presented for a three-phase neural point clamped boost rectifier. The control algorithm consists of a input-output linearization inner current loop in synch...
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ISBN:
(纸本)9781467324199
In this paper, PI control with input-output linearizaiton is presented for a three-phase neural point clamped boost rectifier. The control algorithm consists of a input-output linearization inner current loop in synchronous reference frame and a PI voltage control outer-loop. There are two reference signals for this cascade controller, which are the dc link voltage reference and the q-axis current reference. They are used to regulate the dc link voltage and achieve unity power factor. A model based design method for the inner-loop and outer-loop is presented. Simulation results show the dc link control performance and the current control performance. The control performance under a distorted voltage supply condition is also shown.
Traditionally, the frequency spectrum is licensed to users in a rigid manner where the licensee has the exclusive right to access the allocated band. However, an unlicensed (cognitive) user may share a frequency band ...
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ISBN:
(纸本)9781457720529
Traditionally, the frequency spectrum is licensed to users in a rigid manner where the licensee has the exclusive right to access the allocated band. However, an unlicensed (cognitive) user may share a frequency band with a licensed (primary) owner as long as the interference is below a certain threshold. This makes power control a critical important issue in these networks. In this paper, we consider a decentralized power control algorithm that satisfies the most two significant metrics in cognitive radio network, capacity of cognitive network and total interference to primary users. The problem might be formulated as a power optimization problem, where rate allocation and power control are modeled through the objective function in which each user utility depends not only on its variables but also on the variables of other user utilities. Geometric Programming (GP) Problem is used to convert nonconvex optimization problem to convex optimization problem by introducing auxiliary variables and adding extra equality constraints, thus transferring the coupling in the objective to coupling in the constraints, which can be decoupled by primal-dual decomposition method, then can be efficiently solved even with a large number of users. The benefits of the method are illustrated through numerical results.
Evolutionary algorithms (EAs) based on the concept of Pareto dominance seem the most suitable technique for multiobjective optimisation. In multiobjective optimisation, several criteria (usually conflicting) need to b...
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Evolutionary algorithms (EAs) based on the concept of Pareto dominance seem the most suitable technique for multiobjective optimisation. In multiobjective optimisation, several criteria (usually conflicting) need to be taken into consideration simultaneously to assess a quality of a solution. Instead of finding a single solution, a set of trade-off or compromise solutions that represents a good approximation to the Pareto optimal set is often required. This thesis presents an investigation on evolutionary algorithms within the framework of multiobjective optimisation. This addresses a number of key issues in evolutionary multiobjective optimisation. Also, a new evolutionary multiobjective (EMO) algorithm is proposed. Firstly, this new EMO algorithm is applied to solve the multiple 0/1 knapsack problem (a wellknown benchmark multiobjective combinatorial optimisation problem) producing competitive results when compared to other state-of-the-art MOEAs. Secondly, this thesis also investigates the application of general EMO algorithms to solve real-world nurse scheduling problems. One of the challenges in solving real-world nurse scheduling problems is that these problems are highly constrained and specific-problem heuristics are normally required to handle these constraints. These heuristics have considerable influence on the search which could override the effect that general EMO algorithms could have in the solution process when applied to this type of problems. This thesis outlines a proposal for a general approach to model the nurse scheduling problems without the requirement of problem-specific heuristics so that general EMO algorithms could be applied. This would also help to assess the problems and the performance of general EMO algorithms more fairly.
The aim of this work is to model a new electromechanical system for applications in the field of automated corking machines. The paper presents the dynamic modeling of a new automatic corking machine for threaded plas...
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ISBN:
(纸本)9781457700187
The aim of this work is to model a new electromechanical system for applications in the field of automated corking machines. The paper presents the dynamic modeling of a new automatic corking machine for threaded plastic caps. The model is obtained using the energy-based modeling technique named "Power-Oriented Graphs" (POG). The considered corking machine is an electromechanical system with two degrees of freedom composed by two electrical motors moving a ball screw/spline that realizes the linear/rotary motion necessary to screw a plastic cap on a bottle. The paper presents the dynamic model of the machine and the interaction between the cap and the bottle. In the paper a control algorithm is proposed. Some simulation results are presented and compared to experimental results.
Purpose of the paper is to demonstrate current research addressed to implementation of time changeable energy performance index obtained by Kalinski [1, 2], applied to three-wheeled mobile platform. In order to operat...
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ISBN:
(纸本)9781457709142
Purpose of the paper is to demonstrate current research addressed to implementation of time changeable energy performance index obtained by Kalinski [1, 2], applied to three-wheeled mobile platform. In order to operate optimally during performance of any operations, a mobile robot must understand the effects of its own dynamic model and interactions with the track. Propulsion system should be optimised to withstand environmental conditions and acquire precise motion control. Additionally, during the design process, it is required to consider limitation of accessible control platforms and systems. Therefore, it is natural to implement control algorithms to achieve prescribed optimal motion and immune system for imperfectness of the model, trajectory disturbances and electronics limitations.
Dynamic Spectrum Access (DSA) is a new spectrum management paradigm for facilitating effective utilization of the radio spectrum to meet demands in the growth of wireless services and applications. Cognitive radio has...
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ISBN:
(纸本)9781612849935
Dynamic Spectrum Access (DSA) is a new spectrum management paradigm for facilitating effective utilization of the radio spectrum to meet demands in the growth of wireless services and applications. Cognitive radio has been proposed as the key enabling technology of DSA. Several approaches for regulating transmit-power in cognitive radio networks have been proposed in recent years. In this paper we analyze the two transmit-power control algorithms which have attracted research attention, namely, no-regret learning algorithm and iterative water-filling algorithm. We introduce an adaptive scheme which incorporates the two algorithms into the design of the functional units of cognitive engine, to meet the requirements of transmit-power control.
This paper proposes the predictive controller design for a sensorless interior permanent magnet synchronous motor drive system. The predictive controllers include a current-loop predictive controller and a speed-loop ...
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ISBN:
(纸本)9781424490660
This paper proposes the predictive controller design for a sensorless interior permanent magnet synchronous motor drive system. The predictive controllers include a current-loop predictive controller and a speed-loop predictive controller. By using the proposed control algorithms, the closed-loop sensorless interior permanent magnet synchronous motor drive system can achieve fast transient responses, satisfactory load disturbance responses, and good tracking responses. A digital signal processor, TMS 320F2812, is used to perform the rotor position estimating algorithm and the predictive control algorithms. As a result, the hardware is very simple. Experimental results can validate the theoretical analysis and show the predictive controllers perform better than the PI controllers.
With increasing nominal wind park power, interest in the operating behavior of the plants and the wind park is developing. Main criteria for the quality of the operating behavior are based on mains pollution (e.g. har...
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ISBN:
(纸本)9781424488070
With increasing nominal wind park power, interest in the operating behavior of the plants and the wind park is developing. Main criteria for the quality of the operating behavior are based on mains pollution (e.g. harmonics) and the power fluctuation through variations of the wind speed. The dynamic and stationary operating behavior of wind energy converters (WEC) are defined by the drive train structure and the control algorithm. The essence of this paper is the investigation on the operating behaviors of different WECs generator systems in relation to their influence on the mechanical drive train's operating performance. Because of practical experiences so far, only a few concepts are suitable for the design of the electrical part. Therefore, in this paper, a theoretical and simulation based comparison will be carried out. Five different concepts (some state- of- the- art and some new creations especially for off- shore use) therefore, are compared in relation to necessary requirements.
This thesis describes implementations of motion control systems that are based on fuzzy logic; fuzzymotion controllers. The controllers are used by to drive a variety of simulated vehicles and computeranimatedcharacte...
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This thesis describes implementations of motion control systems that are based on fuzzy logic; fuzzymotion controllers. The controllers are used by to drive a variety of simulated vehicles and computeranimatedcharacters. The problem of heading towards a destination whilst simultaneously avoidingstatic and dynamic obstacles is addressed with fuzzy motion controllers. For situations where a levelabove reactive motion control is required, such as path-planning behaviour or traffic rule following,then hybrid algorithms are proposed; combining fuzzy motion controllers with other navigationalgorithms. Consideration is given to behavioural level of detail models, with transition between behaviouralmodels of different complexity based on the proximity, or visual importance of charactersto the *** controllers have a set of fuzzy rules, or a “rule base” that defines the inference of the *** is no assurance that hand-calibrated rule bases are optimal, and indeed that calibrationbased on fixed test environment will apply well to a dynamic environment. Special considerationis given to genetic-fuzzy systems, which use a genetic algorithm to automatically calibrate a rulebase. Various architectures for genetic-fuzzy system are proposed and evaluated including dynamicsystems, which have the ability to learn “on the fly”, rather than in fixed experiment scenarios. A relationshipbetween genetic algorithm parameters and time-efficient fitness improvement is *** requirements of training more complex “cascading” fuzzy systems are discussed. Distributedand parallel training models are also considered.A new, modular agent middleware is proposed, which is the underpinning software that perceivesthe complex environment, feeds inputs into the fuzzy motion controllers, and effects output actionsfor each character and vehicle. The middleware model is successfully used to drive a range ofvehicles and characters used in *** problem of evaluating motion
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