Adaptive Decoupling Research Articles

The Control of Asymmetric Rolling Missiles Based on Improved Trajectory Linearization Control Method

According to motion characteristic of an asymmetric rolling missile with damage fin, a three-channel controlled model is established. The controller which is used to realize non-linear tracking and decoupling control of the roll and angle motion is introduced based on an improved trajectory linearization control method. The improved method is composed of the classic trajectory linearization control method and a compensation control law. The classic trajectory linearization control method is implemented in the time-scale separation principle. The Lipschitz non-linear state observer systematically obtained by solving the linear matrix inequality approach is provided to estimate state variables and unknown parameters, and then the compensation control law utilizing the estimated unknown parameters improves the TLC method. Simulation experiments show that the adaptive decoupling control ensure tracking performance, and the robustness and accuracy of missile attitude control are ensured under the condition of the system parameters uncertainty, random observation noise and external disturbance caused by damage fin.

Online Parameter Estimation Technique for Adaptive Control Applications of Interior PM Synchronous Motor Drives

This paper proposes an online parameter estimation method based on a discrete-time dynamic model for the interior permanent-magnet synchronous motors (IPMSMs). The proposed estimation technique, which takes advantage of the difference in dynamics of motor parameters, consists of two affine projection algorithms. The first one is designed to accurately estimate the stator inductances, whereas the second one is designed to precisely estimate the stator resistance, rotor flux linkage, and load torque. In this paper, the adaptive decoupling proportional–integral (PI) controllers with the maximum torque per ampere operation, which utilize the previously identified parameters in real time, are chosen to verify the effectiveness of the proposed parameter estimation scheme. The simulation results via MATLAB/Simulink and the experimental results via a prototype IPMSM drive system with a TI TMS320F28335 DSP are presented under various conditions. A comparative study with the conventional decoupling PI control method is carried out to demonstrate the better performances (i.e., faster dynamic response, less steady-state error, more robustness, etc.) of the adaptive decoupling PI control scheme based on the proposed online parameter estimation technique.

Photoperiod induced obesity in the Brandt's vole (Lasiopodomys brandtii): a model of 'healthy obesity'?

ABSTRACTBrandt's voles have an annual cycle of body weight and adiposity. These changes can be induced in the laboratory by manipulation of photoperiod. In the present study, male captive-bred Brandt's voles aged 35 days were acclimated to a short day (SD) photoperiod (8L:16D) for 70 days. A subgroup of individuals (n=16) were implanted with transmitters to monitor physical activity and body temperature. They were then randomly allocated into long day (LD=16L:8D) (n=19, 8 with transmitters) and SD (n=18, 8 with transmitters) groups for an additional 70 days. We monitored aspects of energy balance, glucose and insulin tolerance (GTT and ITT), body composition and organ fat content after exposure to the different photoperiods. LD voles increased in weight for 35 days and then re-established stability at a higher level. At the end of the experiment LD-exposed voles had greater white adipose tissue mass than SD voles (P=0.003). During weight gain they did not differ in their food intake or digestive efficiency; however, daily energy expenditure was significantly reduced in the LD compared with SD animals (ANCOVA, P<0.05) and there was a trend to reduced resting metabolic rate RMR (P=0.075). Physical activity levels were unchanged. Despite different levels of fat storage, the GTT and ITT responses of SD and LD voles were not significantly different, and these traits were not correlated to body fatness. Hence, the photoperiod-induced obesity was independent on disruptions to glucose homeostasis, indicating a potential adaptive decoupling of these states in evolutionary time. Fat content in both the liver and muscle showed no significant difference between LD and SD animals. How voles overcome the common negative aspects of fat storage might make them a useful model for understanding the phenomenon of ‘healthy obesity’.

Benchmark of AC and DC Active Power Decoupling Circuits for Second-Order Harmonic Mitigation in Kilowatt-Scale Single-Phase Inverters

This paper presents the benchmark study of ac and dc active power decoupling (APD) circuits for the second-order harmonic mitigation in kilowatt-scale single-phase inverters. First, a brief comparison of recently reported APD circuits is given, the best solution that can achieve high efficiency and high-power density is identified and comprehensively studied, and the commercially available film capacitors, the circuit topologies, and the control strategies adopted for APD are all considered. Then, an adaptive decoupling voltage control method is proposed to further improve the performance of dc decoupling in terms of efficiency and reliability. The feasibility and superiority of the identified solution for APD together with the proposed adaptive decoupling voltage control method are finally verified by both the simulation and experimental results obtained on a 2-kW single-phase inverter.

Adaptive decoupling synchronous control of dissimilar redundant actuation system for large civil aircraft

In order to meet the increasing reliability requirements of actuation system for large civil aircraft, the novel distributed dissimilar redundant actuation system composed of one hydraulic actuator (HA) and one electro-hydrostatic actuator (EHA) has been applied to the design of advanced aircraft. This configuration can greatly improve the system reliability and effectively avoid potential common-mode/common-cause (CM/CC) failure. However, this actuation configuration can exhibit force fighting problem between HA and EHA due to their different driving mechanisms and rigid coupling when they operate in the active/active mode, which may even cause damage to the control surface. To resolve this problem, an adaptive decoupling synchronous controller (ADSC) is proposed in this study. The coupling effect between HA and EHA is taken into account, and an adaptive decoupling controller is designed to eliminate the coupling term. Parameter adaption law is designed for the parametric uncertainties. In addition, a feed-forward compensator is proposed to compensate for the difference between HA and EHA by accelerating the dynamic response of EHA. Finally, the comparative simulation results indicate that the proposed ADSC controller has high speed/high robustness performances and can effectively reduce the force fighting between HA and EHA.

Clinal variation in Pinus hartwegii populations and its application for adaptation to climate change

Abstract In order to determine the genetic variation among populations of Pinus hartwegii along altitudinal gradients, and the possible adaptive decoupling due to climatic change, a common garden test was set up with 13 provenances collected along an altitudinal transect (3150 to 3750 masl; collection sites were every 50 m of altitudinal difference) from Pico de Tancítaro, Michoacán, west-central Mexico. The test evaluated trees aged 4.5 to 5.5 years, and contemporary and future (year 2030; six model-emission scenarios) climate variables were estimated. We found significant (P&lt;0.005) differences among populations in total elongation, final seedling height, basal diameter, rate of elongation, dry weight of needles, branches and stem, total dry weight and first principal component. We found a significant association between population performance, expressed as first principal component values, and their climate, where the best climatic predictor was the frost free period (r2=0.90, P&lt;0.0001). This result indicates that the patterning of genetic differentiation among populations is strongly associated with a climatic and altitudinal gradient. We propose a re-delineation of fixed climatic and altitudinal seed zoning for seed and seedling movement, based on intervals of 26 days of difference of frost free period: Zone 1, from 240 to 214 days of frost free period or 12 to 11°C or 3150 to 3350 masl; Zone 2, 214 to 188 days or 11 to 10°C or 3350 to 3550 masl; and Zone 3, 188 to 162 days or 10 to 9°C or 3550 a 3750 masl. Projecting at what altitude will occur the same frost free period values by year 2030, we suggested that populations should be shifted 400 m attitudinally upward, through a program of assisted migration, aiming to realign the populations to the climate for which they are adapted. Seedling deployment should use future (year 2030) fixed seed zones, with the same projected climatic interval values than contemporary climate, although at the following altitudinal limits: Zone 12030, from 3550 to 3750 masl; Zone 22030, 3750 to 3950 masl; and Zone 32030, 3950 to 4150 masl.

Slope displacement prediction based on morphological filtering

Combining mathematical morphology (MM), nonparametric and nonlinear model, a novel approach for predicting slope displacement was developed to improve the prediction accuracy. A parallel-composed morphological filter with multiple structure elements was designed to process measured displacement time series with adaptive multi-scale decoupling. Whereafter, functional-coefficient auto regressive (FAR) models were established for the random subsequences. Meanwhile, the trend subsequence was processed by least squares support vector machine (LSSVM) algorithm. Finally, extrapolation results obtained were superposed to get the ultimate prediction result. Case study and comparative analysis demonstrate that the presented method can optimize training samples and show a good nonlinear predicting performance with low risk of choosing wrong algorithms. Mean absolute percentage error (MAPE) and root mean square error (RMSE) of the MM-FAR&LSSVM predicting results are as low as 1.670% and 0.172 mm, respectively, which means that the prediction accuracy are improved significantly.

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

For the forced-circulation evaporation process of alumina production, the control objectives include maintaining the liquid level and fast tracking of the product density with respect to its setpoint. However, with the strong coupling between the level control and product density control loops and the process exhibits strong nonlinearities, conventional control strategies, such as proportional-integral-derivative and other linear control design, cannot achieve satisfactory control performance and meet production demands. By augmenting the forced-circulation evaporation system model with dynamics of its operating valves, a nonlinear adaptive decoupling switching control strategy is proposed. This control strategy includes a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller, and a switching mechanism. The linear adaptive decoupling controller is used to reduce the coupling between the two control loops. The neural-network-based nonlinear adaptive decoupling controller is employed to improve the transient performance and reduce the effects of the nonlinearities on the system, and the switching mechanism is introduced to guarantee the input-output stability of the closed-loop system. Simulation results show that the proposed method can decouple the loops effectively for the forced-circulation evaporation system and thus improve the evaporation efficiency.

Adaptive Decoupling Control of Pulp Levels in Flotation Cells

AbstractControl of the pulp levels in flotation cells directly affects the grade of the concentrate and the tailings in a concentration plant. Nevertheless, with strong coupling among cell levels and nonlinearities in the flotation process, conventional control strategies cannot achieve satisfactory control performance. In this paper, a nonlinear multi‐model adaptive decoupling control strategy based on adaptive‐network‐based fuzzy inference systems (ANFIS) is proposed for the flotation process, which includes a linear adaptive decoupling controller, an ANFIS‐based nonlinear adaptive decoupling controller, and a switching mechanism. The proposed method not only improves the transient performance and mitigates effects of the nonlinearities on the system, but also guarantees the input‐output stability of the closed‐loop system. Successful application to the flotation process has been made in a concentration plant in China, and the feasibility and efficiency of the proposed method have been validated.

An adaptive decoupling approach for reliability-based design optimization

Reliability-based design optimization (RBDO) is a powerful tool for design optimization when considering the probabilistic characteristics of the design variables. However, its use in practical applications is hindered by the huge computational cost during the evaluation of structure reliability. A number of algorithms have been proposed, such as reliability index approach (RIA), performance measure approach (PMA), decoupled approach and single-loop approach. In this paper, the adaptive decoupling approach (ADA) is developed. It adopts a new update angle strategy and a novel feasibility-checking method to improve the efficiency of probabilistic optimization. The update angle is utilized to reduce the number of performance function evaluations. And the probabilistic constraints are divided into feasible, active and violated categories, and only violated and active probabilistic constraints are evaluated precisely. The computation capability of ADA is demonstrated using five examples which are widely used to test RBDO methods. The comparison results show that ADA has the similar accuracy as existing methods, and it is also very efficient.

Adaptive decoupling switching control based on generalised predictive control

This study introduces a multivariable adaptive decoupling control strategy using multiple models and neural networks for a class of discrete-time nonlinear dynamic systems. The adaptive decoupling switching control strategy based on generalised predictive control is composed of a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller and a switching mechanism. First, the linear adaptive decoupling controller is designed to ensure the boundedness of the input and output signals of the closed-loop system. Second, the neural-network-based nonlinear adaptive decoupling controller is developed to improve the transient performance of the closed-loop system. Third, the stability and convergence of the closed-loop system are achieved simultaneously by using multiple-models-based switching mechanism. Simulation studies are provided for a numerical example and a forced-circulation evaporation process of an alumina production system so as to demonstrate the effectiveness of the proposed method.

Decoupling Control Approach for Neonate Incubator System

This paper presents an adaptive decoupling temperature and humidity control for neonatal incubator process by exploiting an active humidification system. The neonatal incubator is a Two-Input Two-Output process (TITO) with characteristics of strong coupling and time variation. The coupling problem is treated by the weight adjustment of the output error to reduce the effect of coupling and to enhance control performance. In addition, an Adaptive Decoupling strategy based on Generalized Predictive Control (ADGPC) with Multivariable Recursive Extended Least-Squares (MVRELS) parameters estimator is used. The simulation and real results demonstrate that the decoupling by error dependent tuning of the weighting factor can eliminate the coupling influence with better control performance and can be easily generalized to the Multiple-Input – Multiple-Output (MIMO) systems. General Terms Incubator process, Multivariable system, Decoupling Predictive Control.

FITNESS CONSEQUENCES OF LARVAL TRAITS PERSIST ACROSS THE METAMORPHIC BOUNDARY

Metamorphosis is thought to provide an adaptive decoupling between traits specialized for each life-history stage in species with complex life cycles. However, an increasing number of studies are finding that larval traits can carry-over to influence postmetamorphic performance, suggesting that these life-history stages may not be free to evolve independently of each other. We used a phenotypic selection framework to compare the relative and interactive effects of larval size, time to hatching, and time to settlement on postmetamorphic survival and growth in a marine invertebrate, Styela plicata. Time to hatching was the only larval trait found to be under directional selection, individuals that took more time to hatch into larvae survived better after metamorphosis but grew more slowly. Nonlinear selection was found to act on multivariate trait combinations, once again acting in opposite directions for selection acting via survival and growth. Individuals with above average values of larval traits were most likely to survive, but surviving individuals with intermediate larval traits grew to the largest size. These results demonstrate that larval traits can have multiple, complex fitness consequences that persist across the metamorphic boundary; and thus postmetamorphic selection pressures may constrain the evolution of larval traits.

Adaptive Decoupling Design of Constant Temperature and Humidity Control System Based on GPC and Multi-Model Control

In view of characteristics of large time delay, multi-interference and strong coupling in temperature and humidity control system, an adaptive decoupling strategy based on generalized predictive control (GPC) and multi-model control is proposed in this paper. The proposed strategy mainly contains muti-model control, GPC decoupling control and adaptive algorithm. In multi-model control, multi-model sets are established to prevent the model mismatch in different working conditions. Meanwhile, this paper designs adaptive dynamic decoupling algorithms based on the principle of GPC. In actual experiments, temperature and humidity achieve precision of ±0.2°C and ±0.5% respectively.

Modeling and Adaptive Decoupling of High-Frequency Resistance and Temperature Effects in Carrier-Based Sensorless Control of PM Synchronous Machines

This paper analyzes the effects of the high-frequency resistances in saliency tracking-based sensorless control methods of permanent-magnet synchronous machines (PMSMs). A high-frequency model of the PMSM, including stator high-frequency resistance, is presented. From this model, potential sources of error in the estimated position due to the high-frequency resistances are analyzed, and their compensation by means of an adaptive decoupling mechanism is proposed. This paper also addresses the influence and compensation of temperature effects in carrier-signal-injection-based sensorless techniques.

Intelligent Decoupling Control of Nonlinear Multivariable Systems and its Application to a Wind Tunnel System

In this paper, for a class of nonlinear multivariable discrete-time systems, an open-loop approximately dynamical decoupling control law is first presented. Then, by introducing a lambda o T difference operator, an intelligent decoupling control method using multiple models and neural networks (NNs) is developed. The intelligent decoupling control method includes a set of fixed decoupling controllers, a reinitialized NN adaptive decoupling controller, a free-running NN adaptive decoupling controller, and a switching mechanism. Theory analysis shows that the free-running NN adaptive decoupling controller can guarantee the bounded-input-bounded-output stability of the closed-loop system, while the multiple fixed decoupling controllers and the reinitialized NN adaptive decoupling controller are used to improve the system performance. To illustrate the method, the proposed design is applied to a 2.4 times 2.4-m injector-driven transonic wind tunnel system. Simulation and industrial experiment results show the effectiveness and practicality of the proposed method.

Multivariable direct adaptive decoupling controller using multiple models and a case study

In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system.

Measurement and Adaptive Decoupling of Cross-Saturation Effects and Secondary Saliencies in Sensorless Controlled IPM Synchronous Machines

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper analyzes the effects of magnetic saturation, including cross-saturation and secondary saliencies, on the saliency-based sensorless control of interior permanent magnet synchronous machines. These effects are mitigated by adaptively decoupling saturation-induced saliencies via a structured neural network. This paper includes the identification of the dominant saturation-induced components of the carrier-signal current interfering with the rotor-position-dependent component being tracked, characterization of these components, and implementation of a nonlinear adaptive saturation-induced-component structured neural network model to perform their decoupling. </para>

Multi-model direct adaptive decoupling control with application to the wind tunnel system

In this paper, a new multi-model direct adaptive decoupling controller is presented for multivariable processes, which includes multiple fixed optimal controllers, one free-running adaptive controller, and one re-initialized adaptive controller. The fixed controllers provide initial control to the process if its model lies in the corresponding region. For each controller selected, the re-initialized adaptive controller uses the values of this particular controller to improve the adaptation speed. This controller may replace the fixed controller at a later stage according to the switching criterion which is to select the best one among all controllers. A free-running adaptive controller is also added to guarantee the overall system stability. Different from the multiple models adaptive control structure proposed in Narendra, Balakrish-nan, and Ciliz [Adaptation and learning using multiple models, switching, and tuning. IEEE Control Syst. Mag. 15, 37–51 (1995)], the method not only is applicable to the multi-input multi-output processes but also identifies the decoupling controller parameters directly, which reduces both the computational burden and the chances of a singular matrix during the process of determining controller parameters. Several examples for a wind tunnel process are given to demonstrate the effectiveness and practicality of the proposed method.

Metamorphic duration: an under-studied variable in frog life histories

Over a narrow temperature range (25.5–28 °C), metamorphic duration in 14 taxonomically diverse frog species ranged from 2.0 to 7.3 days. For 12 species, duration was significantly related to tadpole body-size parameters, especially tail length. For the remainder, duration was longer than expected. Two patterns of tail regression were seen with either rapid or slow regression at the start. Most species lost about 30% of body wet weight during metamorphosis, but two were exceptional: X. laevis lost 58% and F. fitzgeraldi 13%. The results are discussed in the context of Wassersug & Sperry’s (1977) hypothesis that selection acts to minimize metamorphic duration because metamorphosis is a highly vulnerable stage. Several other factors are outlined as possible determinants of metamorphic duration: developmental constraints, functional trade-offs, phylogeny, predator abundance, adaptive de-coupling, body condition and metabolic and water costs. There is evidence from the data for the operation of several of these factors, especially in species utilizing specialized habitats, and a plea is made for further study of metamorphic duration as an ecologically and evolutionarily important variable in amphibian life histories. Finally, the effects of different temperatures on metamorphic duration are presented for several species, and discussed in terms of local adaptation and reaction norms. © 2004 The Linnean Society of London, Biological Journal of the Linnean Society, 2004, 83, 261–272.