Threshold-based substream selection for closed-loop spatial multiplexing

We propose a low-complexity closed-loop spatial multiplexing method with limited feedback over multi-input-multi-output (MIMO) fading channels. The transmit adaptation is simply performed by selecting transmit antennas (or substreams) by comparing their signal-to-noise ratios to a given threshold with a fixed nonadaptive constellation and fixed transmit power per substream. We analyze the performance of the proposed system by deriving closed-form expressions for spectral efficiency, average transmit power, and bit error rate (BER). Depending on practical system design constraints, the threshold is chosen to maximize the spectral efficiency (or minimize the average BER) subject to average transmit power and average BER (or spectral efficiency) constraints, respectively. We present numerical and Monte Carlo simulation results that validate our analysis. Compared to open-loop spatial multiplexing and other approaches that select the best antenna subset in spatial multiplexing, the numerical results illustrate that the proposed technique obtains significant power gains for the same BER and spectral efficiency. We also provide numerical results that show improvement over rate-adaptive orthogonal space-time block coding, which requires highly complex constellation adaptation. We analyze the impact of feedback delay using analytical and Monte Carlo approaches. The proposed approach is arguably the simplest possible adaptive spatial multiplexing system from an implementation point of view. However, our approach and analysis can be extended to other systems using multiple constellations and power levels.

Identification of dynamic systems under closed-loop control

This paper introduces a novel modelling framework for identifying dynamic models of systems that are under feedback control. These models are identified under closed-loop conditions and produce a joint representation that includes both the plant and controller models in state space form. The joint plant/controller model is identified using subspace model identification (SMI), which is followed by the separation of the plant model from the identified one. Compared to previous research, this work (i) proposes a new modelling framework for identifying closed-loop systems, (ii) introduces a generic structure to represent the controller and (iii) explains how that the new framework gives rise to a simplified determination of the plant models. In contrast, the use of the conventional modelling approach renders the separation of the plant model a difficult task. The benefits of using the new model method are demonstrated using a number of application studies.

Improvement of the Performance of Hysteresis Compensation in SMA Actuators by Using Inverse Preisach Model in Closed – Loop Control System

The aim of this paper is to increase the performance of hysteresis compensation for Shape Memory Alloy (SMA) actuators by using inverse Preisach model in closed — loop control system. This is used to reduce hysteresis effects and improve accuracy for the displacement of SMA actuators. Firstly, hysteresis is identified by numerical Preisach model implementation. The geometrical interpretation from first order transition curves is used for hysteresis modeling. Secondly, the inverse Preisach model is formulated and incorporated in closed-loop PID control system in order to obtain desired current-to-displacement relationship with hysteresis reducing. The experimental results for hysteresis compensation by using this method are also shown in this paper.

The Bright Side of Manufacturing–Remanufacturing Conflict in a Decentralised Closed-Loop Supply Chain

Researchers and managers broadly agree that original equipment manufacturers (OEMs), which have opportunities to produce both new and remanufactured products, are better off by centrally controlling their manufacturing and remanufacturing activities. Thus, OEMs should not remanufacture used products until the remanufacturing cost is sufficiently low to overcome the negative impact of new product cannibalisation. In this paper, we present a contrasting view of the manufacturing–remanufacturing conflict: OEMs sometimes benefit from the decentralised control mode under which they ignore the internal cannibalisation rather than the remanufacturing option. We consider a decentralised closed-loop supply chain in which one OEM can purchase new components from one supplier to produce new products and collect used products from consumers to produce remanufactured products. The key feature of our model is that the OEM can select a centralised or decentralised control mode to manage its manufacturing and remanufacturing activities before the supplier prices the new component. In a steady state period setting, we analyse the players’ optimal decisions and compare the OEM's profits under centralised and decentralised control modes. Our analytic results reveal that the decentralised control within the OEM can outperform the centralised control when the cost structure of producing new and remanufactured products satisfies certain conditions. Finally, the key findings are distilled in a conceptual framework and its managerial implications are discussed.

Distributed closed-loop spatial multiplexing for uplink multiuser systems

Focusing on the uplink, where mobile users (each with a single transmit antenna) communicate with a base station with multiple antennas, we treat multiple users as antennas to enable spatial multiplexing across users. Introducing distributed closed-loop spatial multiplexing with threshold-based user selection, we propose two uplink channel-assigning strategies with limited feedback. We prove that the proposed system also outperforms the standard greedy scheme with respect to the degree of fairness, measured by the variance of the time averaged throughput. For uplink multi-antenna systems, we show that the proposed scheduling is a better choice than the greedy scheme in terms of the average BER, feedback complexity, and fairness. The numerical results corroborate our findings

Low-power DWT-based quasi-averaging algorithm and architecture for epileptic seizure detection

In this paper, we have developed a low-complexity algorithm for epileptic seizure detection with a high degree of accuracy. The algorithm has been designed to be feasibly implementable as battery-powered low-power implantable epileptic seizure detection system or epilepsy prosthesis. This is achieved by utilizing design optimization techniques at different levels of abstraction. Particularly, user-specific critical parameters are identified at the algorithmic level and are explicitly used along with multiplier-less implementations at the architecture level. The system has been tested on neural data obtained from in-vivo animal recordings and has been implemented in 90nm bulk-Si technology. The results show up to 90 % savings in power as compared to prevalent wavelet based seizure detection technique while achieving 97% average detection rate. Copyright 2010 ACM.

Low-Power Process-Variation Tolerant Arithmetic Units Using Input-Based Elastic Clocking

In this paper we propose a design methodology for low-power high-performance, process-variation tolerant architecture for arithmetic units. The novelty of our approach lies in the fact that possible delay failures due to process variations and/or voltage scaling are predicted in advance and addressed by employing an elastic clocking technique. The prediction mechanism exploits the dependence of delay of arithmetic units upon input data patterns and identifies specific inputs that activate the critical path. Under iso-yield conditions, the proposed design operates at a lower scaled down Vdd without any performance degradation, while it ensures a superlative yield under a design style employing nominal supply and transistor threshold voltage. Simulation results show power savings of upto 29%, energy per computation savings of upto 25.5% and yield enhancement of upto 11.1% compared to the conventional adders and multipliers implemented in the 70nm BPTM technology. We incorporated the proposed modules in the execution unit of a five stage DLX pipeline to measure performance using SPEC2000 benchmarks [9]. Maximum area and throughput penalty obtained were 10% and 3% respectively.

Multiobjective design optimization of IGBT power modules considering power cycling and thermal cycling

Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.

A decision support system for managing irrigation in agriculture

In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.