19 resultados para Mimo

em Aston University Research Archive


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We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

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Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases. © 2007 IOP Publishing Ltd.

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Traditional machinery for manufacturing processes are characterised by actuators powered and co-ordinated by mechanical linkages driven from a central drive. Increasingly, these linkages are replaced by independent electrical drives, each performs a different task and follows a different motion profile, co-ordinated by computers. A design methodology for the servo control of high speed multi-axis machinery is proposed, based on the concept of a highly adaptable generic machine model. In addition to the dynamics of the drives and the loads, the model includes the inherent interactions between the motion axes and thus provides a Multi-Input Multi-Output (MIMO) description. In general, inherent interactions such as structural couplings between groups of motion axes are undesirable and needed to be compensated. On the other hand, imposed interactions such as the synchronisation of different groups of axes are often required. It is recognised that a suitable MIMO controller can simultaneously achieve these objectives and reconciles their potential conflicts. Both analytical and numerical methods for the design of MIMO controllers are investigated. At present, it is not possible to implement high order MIMO controllers for practical reasons. Based on simulations of the generic machine model under full MIMO control, however, it is possible to determine a suitable topology for a blockwise decentralised control scheme. The Block Relative Gain array (BRG) is used to compare the relative strength of closed loop interactions between sub-systems. A number of approaches to the design of the smaller decentralised MIMO controllers for these sub-systems has been investigated. For the purpose of illustration, a benchmark problem based on a 3 axes test rig has been carried through the design cycle to demonstrate the working of the design methodology.

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Multiple-antenna systems offer significant performance enhancement and will be applied to the next generation broadband wireless communications. This thesis presents the investigations of multiple-antenna systems – multiple-input multiple-output (MIMO) and cooperative communication (CC) – and their performances in more realistic propagation environments than those reported previously. For MIMO systems, the investigations are conducted via theoretical modelling and simulations in a double-scattering environment. The results show that the variations of system performances depend on how scatterer density varies in flat fading channels, and that in frequency-selective fading channels system performances are affected by the length of the coding block as well as scatterer density. In realistic propagation environments, the fading correlation also has an impact on CC systems where the antennas can be further apart than those in MIMO systems. A general stochastic model is applied to studying the effects of fading correlation on the performances of CC systems. This model reflects the asymmetry fact of the wireless channels in a CC system. The results demonstrate the varied effects of fading correlation under different protocols and channel conditions. Performances of CC systems are further studied at the packet level, using both simulations and an experimental testbed. The results obtained have verified various performance trade-offs of the cooperative relaying network (CRN) investigated in different propagation environments. The results suggest that a proper selection of the relaying algorithms and other techniques can meet the requirements of quality of service for different applications.

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It is desirable that energy performance improvement is not realized at the expense of other network performance parameters. This paper investigates the trade off between energy efficiency, spectral efficiency and user QoS performance for a multi-cell multi-user radio access network. Specifically, the energy consumption ratio (ECR) and the spectral efficiency of several common frequency domain packet schedulers in a cellular E-UTRAN downlink are compared for both the SISO transmission mode and the 2x2 Alamouti Space Frequency Block Code (SFBC) MIMO transmission mode. It is well known that the 2x2 SFBC MIMO transmission mode is more spectrally efficient compared to the SISO transmission mode, however, the relationship between energy efficiency and spectral efficiency is undecided. It is shown that, for the E-UTRAN downlink with fixed transmission power, spectral efficiency improvement results into energy efficiency improvement. The effect of SFBC MIMO versus SISO on the user QoS performance is also studied. © 2011 IEEE.

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A new generalized sphere decoding algorithm is proposed for underdetermined MIMO systems with fewer receive antennas N than transmit antennas M. The proposed algorithm is significantly faster than the existing generalized sphere decoding algorithms. The basic idea is to partition the transmitted signal vector into two subvectors x and x with N - 1 and M - N + 1 elements respectively. After some simple transformations, an outer layer Sphere Decoder (SD) can be used to choose proper x and then use an inner layer SD to decide x, thus the whole transmitted signal vector is obtained. Simulation results show that Double Layer Sphere Decoding (DLSD) has far less complexity than the existing Generalized Sphere Decoding (GSDs).

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Owing to the limited cell size of eNodeB (eNB), the relay node has emerged as an attractive solution for the long-term evolution (LTE) system. The nonlinear limit of the alternative method to multipleinput and multiple-output (MIMO) based on frequency division multiplexing (FDM) for orthogonal FDM (OFDM) is analysed over varying transmission spans. In this reported work, it is shown that the degradation pattern over the linear, intermixing and nonlinear propagation regions is consistent for the 2 and the 2.6 GHz bands. The proposed bands experienced a linear increase in the error vector magnitude (EVM) for both the linear and the nonlinear regions proportional to the increasing transmission spans. In addition, an optical launch power between -2 and 2 dBm achieved a significantly lower EVM than the LTE limit of 8% for the 10-60 km spans. © The Institution of Engineering and Technology 2014.

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In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

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The multiple-input multiple-output (MIMO) technique can be used to improve the performance of ad hoc networks. Various medium access control (MAC) protocols with multiple contention slots have been proposed to exploit spatial multiplexing for increasing the transport throughput of MIMO ad hoc networks. However, the existence of multiple request-to-send/clear-to-send (RTS/CTS) contention slots represents a severe overhead that limits the improvement on transport throughput achieved by spatial multiplexing. In addition, when the number of contention slots is fixed, the efficiency of RTS/CTS contention is affected by the transmitting power of network nodes. In this study, a joint optimisation scheme on both transmitting power and contention slots number for maximising the transport throughput is presented. This includes the establishment of an analytical model of a simplified MAC protocol with multiple contention slots, the derivation of transport throughput as a function of both transmitting power and the number of contention slots, and the optimisation process based on the transport throughput formula derived. The analytical results obtained, verified by simulation, show that much higher transport throughput can be achieved using the joint optimisation scheme proposed, compared with the non-optimised cases and the results previously reported.

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We investigate a MIMO double-scattering model with both local and remote scatterers, aiming to investigate the effect of scatterer density on channel performances, such as capacity, correlation, and the condition number of the channel matrix in flat and frequency-selective fading channels. The investigations are carried out in terms of scatterer density. It is shown that in flat fading channels the scatterer density has a marginal effect on channel performances when the area of the two scatterer zones is fixed, while a significant impact is observed when the area of the scatterer zones is allowed to change. In frequency-selective fading channels, no matter the area of the scatterer zones is fixed or not, scatterer density can affect the channel capacity to a certain degree that depends on the length of the coding block of the transmitted signals. © 2010 IEEE.

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Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

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The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

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The unmitigated transmission of undesirable vibration can result in problems by way of causing human discomfort, machinery and equipment failure, and affecting the quality of a manufacturing process. When identifiable transmission paths are discernible, vibrations from the source can be isolated from the rest of the system and this prevents or minimises the problems. The approach proposed here for vibration isolation is active force cancellation at points close to the vibration source. It uses force feedback for multiple-input and multiple-output control at the mounting locations. This is particularly attractive for rigid mounting of machine on relative flexible base where machine alignment and motions are to be restricted. The force transfer function matrix is used as a disturbance rejection performance specification for the design of MIMO controllers. For machine soft-mounted via flexible isolators, a model for this matrix has been derived. Under certain conditions, a simple multiplicative uncertainty model is obtained that shows the amount of perturbation a flexible base has on the machine-isolator-rigid base transmissibility matrix. Such a model is very suitable for use with robust control design paradigm. A different model is derived for the machine on hard-mounts without the flexible isolators. With this model, the level of force transmitted from a machine to a final mounting structure using the measurements for the machine running on another mounting structure can be determined. The two mounting structures have dissimilar dynamic characteristics. Experiments have verified the usefulness of the expression. The model compares well with other methods in the literature. The disadvantage lies with the large amount of data that has to be collected. Active force cancellation is demonstrated on an experimental rig using an AC industrial motor hard-mounted onto a relative flexible structure. The force transfer function matrix, determined from measurements, is used to design H and Static Output Feedback controllers. Both types of controllers are stable and robust to modelling errors within the identified frequency range. They reduce the RMS of transmitted force by between 30?80% at all mounting locations for machine running at 1340 rpm. At the rated speed of 1440 rpm only the static gain controller is able to provide 30?55% reduction at all locations. The H controllers on the other hand could only give a small reduction at one mount location. This is due in part to the deficient of the model used in the design. Higher frequency dynamics has been ignored in the model. This can be resolved by the use of a higher order model that can result in a high order controller. A low order static gain controller, with some tuning, performs better. But it lacks the analytical framework for analysis and design.

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Transmission of a 73.7 Tb/s (96x3x256-Gb/s) DP-16QAM mode-division-multiplexed signal over 119km of few-mode fiber transmission line incorporating an inline multi mode EDFA and a phase plate based mode (de-)multiplexer is demonstrated. Data-aided 6x6 MIMO digital signal processing was used to demodulate the signal. The total demonstrated net capacity, taking into account 20% of FEC-overhead and 7.5% additional overhead (Ethernet and training sequences), is 57.6 Tb/s, corresponding to a spectral efficiency of 12 bits/s/Hz.

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We show transmission of a 3x112-Gb/s DP-QPSK mode-division-multiplexed signal up to 80km, with and without multi-mode EDFA, using blind 6x6 MIMO digital signal processing. We show that the OSNR-penalty induced by mode-mixing in the multi-mode EDFA is negligible.