Adapting to rates versus amounts of climate change: a case of adaptation to sea-level rise

Science.gov (United States)

Shayegh, Soheil; Moreno-Cruz, Juan; Caldeira, Ken

2016-10-01

Adaptation is the process of adjusting to climate change in order to moderate harm or exploit beneficial opportunities associated with it. Most adaptation strategies are designed to adjust to a new climate state. However, despite our best efforts to curtail greenhouse gas emissions, climate is likely to continue changing far into the future. Here, we show how considering rates of change affects the projected optimal adaptation strategy. We ground our discussion with an example of optimal investment in the face of continued sea-level rise, presenting a quantitative model that illustrates the interplay among physical and economic factors governing coastal development decisions such as rate of sea-level rise, land slope, discount rate, and depreciation rate. This model shows that the determination of optimal investment strategies depends on taking into account future rates of sea-level rise, as well as social and political constraints. This general approach also applies to the development of improved strategies to adapt to ongoing trends in temperature, precipitation, and other climate variables. Adaptation to some amount of change instead of adaptation to ongoing rates of change may produce inaccurate estimates of damages to the social systems and their ability to respond to external pressures.

Enhanced vaccine control of epidemics in adaptive networks

Science.gov (United States)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Adaptive Significance of Quorum Sensing-Dependent Regulation of Rhamnolipids by Integration of Growth Rate in Burkholderia glumae: A Trade-Off between Survival and Efficiency.

Science.gov (United States)

Nickzad, Arvin; Déziel, Eric

2016-01-01

Quorum sensing (QS) is a cell density-dependent mechanism which enables a population of bacteria to coordinate cooperative behaviors in response to the accumulation of self-produced autoinducer signals in their local environment. An emerging framework is that the adaptive significance of QS in the regulation of production of costly extracellular metabolites ("public goods") is to maintain the homeostasis of cooperation. We investigated this model using the phytopathogenic bacterium Burkholderia glumae, which we have previously demonstrated uses QS to regulate the production of rhamnolipids, extracellular surface-active glycolipids promoting the social behavior called "swarming motility." Using mass spectrometric quantification and chromosomal lux-based gene expression, we made the unexpected finding that when unrestricted nutrient resources are provided, production of rhamnolipids is carried out completely independently of QS regulation. This is a unique observation among known QS-controlled factors in bacteria. On the other hand, under nutrient-limited conditions, QS then becomes the main regulating mechanism, significantly enhancing the specific rhamnolipids yield. Accordingly, decreasing nutrient concentrations amplifies rhamnolipid biosynthesis gene expression, revealing a system where QS-dependent regulation is specifically triggered by the growth rate of the population, rather than by its cell density. Furthermore, a gradual increase in QS signal specific concentration upon decrease of specific growth rate suggests a reduction in quorum threshold, which reflects an increase in cellular demand for production of QS-dependent target gene product at low density populations. Integration of growth rate with QS as a decision-making mechanism for biosynthesis of costly metabolites, such as rhamnolipids, could serve to assess the demand and timing for expanding the carrying capacity of a population through spatial expansion mechanisms, such as swarming motility, thus

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

Energy Technology Data Exchange (ETDEWEB)

Chai, Tianyou; Jia, Yao; Wang, Hong; Su, Chun-Yi

2017-07-09

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperature are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

International Nuclear Information System (INIS)

Xue Guang-Yue; Ren Xue-Mei; Xia Yuan-Qing

2013-01-01

This paper proposes an adaptive discrete finite-time synergetic control (ADFTSC) scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter (EKF), the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach. (general)

An adaptive Cartesian control scheme for manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Variable mutation rates as an adaptive strategy in replicator populations.

Directory of Open Access Journals (Sweden)

Michael Stich

2010-06-01

Full Text Available For evolving populations of replicators, there is much evidence that the effect of mutations on fitness depends on the degree of adaptation to the selective pressures at play. In optimized populations, most mutations have deleterious effects, such that low mutation rates are favoured. In contrast to this, in populations thriving in changing environments a larger fraction of mutations have beneficial effects, providing the diversity necessary to adapt to new conditions. What is more, non-adapted populations occasionally benefit from an increase in the mutation rate. Therefore, there is no optimal universal value of the mutation rate and species attempt to adjust it to their momentary adaptive needs. In this work we have used stationary populations of RNA molecules evolving in silico to investigate the relationship between the degree of adaptation of an optimized population and the value of the mutation rate promoting maximal adaptation in a short time to a new selective pressure. Our results show that this value can significantly differ from the optimal value at mutation-selection equilibrium, being strongly influenced by the structure of the population when the adaptive process begins. In the short-term, highly optimized populations containing little variability respond better to environmental changes upon an increase of the mutation rate, whereas populations with a lower degree of optimization but higher variability benefit from reducing the mutation rate to adapt rapidly. These findings show a good agreement with the behaviour exhibited by actual organisms that replicate their genomes under broadly different mutation rates.

Adaptive Torque Control of Variable Speed Wind Turbines

Energy Technology Data Exchange (ETDEWEB)

Johnson, K. E.

2004-08-01

The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry for variable speed wind turbines below rated power. This adaptive controller uses a simple, highly intuitive gain adaptation law designed to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds.

Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

International Nuclear Information System (INIS)

Sun, Z.; Sen, A.K.; Longman, R.W.

2006-01-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used

Diffusion-controlled reaction. V. Effect of concentration-dependent diffusion coefficient on reaction rate in graft polymerization

International Nuclear Information System (INIS)

Imre, K.; Odian, G.

1979-01-01

The effect of diffusion on radiation-initiated graft polymerization has been studied with emphasis on the single- and two-penetrant cases. When the physical properties of the penetrants are similar, the two-penetrant problems can be reduced to the single-penetrant problem by redefining the characteristic parameters of the system. The diffusion-free graft polymerization rate is assumed to be proportional to the upsilon power of the monomer concentration respectively, and, in which the proportionality constant a = k/sub p/R/sub i//sup w//k/sub t//sup z/, where k/sub p/ and k/sub t/ are the propagation and termination rate constants, respectively, and R/sub i/ is the initiation rate. The values of upsilon, w, and z depend on the particular reaction system. The results of earlier work were generalized by allowing a non-Fickian diffusion rate which predicts an essentially exponential dependence on the monomer concentration of the diffusion coefficient, D = D 0 [exp(deltaC/M)], where M is the saturation concentration. A reaction system is characterized by the three dimensionless parameters, upsilon, delta, and A = (L/2)[aM/sup (upsilon--1)//D 0 ]/sup 1/2/, where L is the polymer film thickness. Graft polymerization tends to become diffusion controlled as A increases. Larger values of delta and ν cause a reaction system to behave closer to the diffusion-free regime. Transition from diffusion-free to diffusion-controlled reaction involves changes in the dependence of the reaction rate on film thickness, initiation rate, and monomer concentration. Although the diffusion-free rate is w order in initiation rate, upsilon order in monomer, and independent of film thickness, the diffusion-controlled rate is w/2 order in initiator rate and inverse first-order in film thickness. Dependence of the diffusion-controlled rate on monomer is dependent in a complex manner on the diffusional characteristics of the reaction system. 11 figures, 4 tables

Exponential Antisynchronization Control of Stochastic Memristive Neural Networks with Mixed Time-Varying Delays Based on Novel Delay-Dependent or Delay-Independent Adaptive Controller

Directory of Open Access Journals (Sweden)

Minghui Yu

2017-01-01

Full Text Available The global exponential antisynchronization in mean square of memristive neural networks with stochastic perturbation and mixed time-varying delays is studied in this paper. Then, two kinds of novel delay-dependent and delay-independent adaptive controllers are designed. With the ability of adapting to environment changes, the proposed controllers can modify their behaviors to achieve the best performance. In particular, on the basis of the differential inclusions theory, inequality theory, and stochastic analysis techniques, several sufficient conditions are obtained to guarantee the exponential antisynchronization between the drive system and response system. Furthermore, two numerical simulation examples are provided to the validity of the derived criteria.

Controllable deterioration rate for time-dependent demand and time-varying holding cost

Directory of Open Access Journals (Sweden)

Mishra Vinod Kumar

2014-01-01

Full Text Available In this paper, we develop an inventory model for non-instantaneous deteriorating items under the consideration of the facts: deterioration rate can be controlled by using the preservation technology (PT during deteriorating period, and holding cost and demand rate both are linear function of time, which was treated as constant in most of the deteriorating inventory models. So in this paper, we developed a deterministic inventory model for non-instantaneous deteriorating items in which both demand rate and holding cost are a linear function of time, deterioration rate is constant, backlogging rate is variable and depend on the length of the next replenishment, shortages are allowed and partially backlogged. The model is solved analytically by minimizing the total cost of the inventory system. The model can be applied to optimizing the total inventory cost of non-instantaneous deteriorating items inventory for the business enterprises, where the preservation technology is used to control the deterioration rate, and demand & holding cost both are a linear function of time.

Direct adaptive control of manipulators in Cartesian space

Science.gov (United States)

Seraji, H.

1987-01-01

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Pilot-Induced Oscillation Suppression by Using 1 Adaptive Control

Directory of Open Access Journals (Sweden)

Chuan Wang

2012-01-01

research activities that aim to alleviate this problem. In this paper, the L1 adaptive controller has been introduced to suppress the PIO, which is caused by rate limiting and pure time delay. Due to its architecture, the L1 adaptive controller will achieve a desired response with fast adaptation. The analysis of PIO and its suppression by L1 adaptive controller are presented in detail in the paper. The simulation results indicate that the L1 adaptive control is efficient in solving this kind of problem.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

Science.gov (United States)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Differential flatness properties and adaptive control of the hypothalamic-pituitary-adrenal axis model

Science.gov (United States)

Rigatos, Gerasimos

2016-12-01

It is shown that the model of the hypothalamic-pituitary-adrenal gland axis is a differentially flat one and this permits to transform it to the so-called linear canonical form. For the new description of the system's dynamics the transformed control inputs contain unknown terms which depend on the system's parameters. To identify these terms an adaptive fuzzy approximator is used in the control loop. Thus an adaptive fuzzy control scheme is implemented in which the unknown or unmodeled system dynamics is approximated by neurofuzzy networks and next this information is used by a feedback controller that makes the state variables (CRH - corticotropin releasing hormone, adenocortocotropic hormone - ACTH, cortisol) of the hypothalamic-pituitary-adrenal gland axis model converge to the desirable levels (setpoints). This adaptive control scheme is exclusively implemented with the use of output feedback, while the state vector elements which are not directly measured are estimated with the use of a state observer that operates in the control loop. The learning rate of the adaptive fuzzy system is suitably computed from Lyapunov analysis, so as to assure that both the learning procedure for the unknown system's parameters, the dynamics of the observer and the dynamics of the control loop will remain stable. The performed Lyapunov stability analysis depends on two Riccati equations, one associated with the feedback controller and one associated with the state observer. Finally, it is proven that for the control scheme that comprises the feedback controller, the state observer and the neurofuzzy approximator, an H-infinity tracking performance can be succeeded.

Translation elicits a growth rate-dependent, genome-wide, differential protein production in Bacillus subtilis.

Science.gov (United States)

Borkowski, Olivier; Goelzer, Anne; Schaffer, Marc; Calabre, Magali; Mäder, Ulrike; Aymerich, Stéphane; Jules, Matthieu; Fromion, Vincent

2016-05-17

Complex regulatory programs control cell adaptation to environmental changes by setting condition-specific proteomes. In balanced growth, bacterial protein abundances depend on the dilution rate, transcript abundances and transcript-specific translation efficiencies. We revisited the current theory claiming the invariance of bacterial translation efficiency. By integrating genome-wide transcriptome datasets and datasets from a library of synthetic gfp-reporter fusions, we demonstrated that translation efficiencies in Bacillus subtilis decreased up to fourfold from slow to fast growth. The translation initiation regions elicited a growth rate-dependent, differential production of proteins without regulators, hence revealing a unique, hard-coded, growth rate-dependent mode of regulation. We combined model-based data analyses of transcript and protein abundances genome-wide and revealed that this global regulation is extensively used in B. subtilis We eventually developed a knowledge-based, three-step translation initiation model, experimentally challenged the model predictions and proposed that a growth rate-dependent drop in free ribosome abundance accounted for the differential protein production. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

The adaptation rate of a quantitative trait in an environmental gradient

Science.gov (United States)

Hermsen, R.

2016-12-01

The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

The adaptation rate of a quantitative trait in an environmental gradient.

Science.gov (United States)

Hermsen, R

2016-11-30

The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

Multiple model adaptive control with mixing

Science.gov (United States)

Kuipers, Matthew

Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

Context-dependent adaptation of visually-guided arm movements and vestibular eye movements: role of the cerebellum

Science.gov (United States)

Lewis, Richard F.

2003-01-01

Accurate motor control requires adaptive processes that correct for gradual and rapid perturbations in the properties of the controlled object. The ability to quickly switch between different movement synergies using sensory cues, referred to as context-dependent adaptation, is a subject of considerable interest at present. The potential function of the cerebellum in context-dependent adaptation remains uncertain, but the data reviewed below suggest that it may play a fundamental role in this process.

Time-dependent postural control adaptations following a neuromuscular warm-up in female handball players: a randomized controlled trial.

Science.gov (United States)

Steib, Simon; Zahn, Peter; Zu Eulenburg, Christine; Pfeifer, Klaus; Zech, Astrid

2016-01-01

Female handball athletes are at a particular risk of sustaining lower extremity injuries. The study examines time-dependent adaptations of static and dynamic balance as potential injury risk factors to a specific warm-up program focusing on neuromuscular control. Fourty one (24.0 ± 5.9 years) female handball athletes were randomized to an intervention or control group. The intervention group implemented a 15-min specific neuromuscular warm-up program, three times per week for eleven weeks, whereas the control group continued with their regular warm-up. Balance was assessed at five time points. Measures included the star excursion balance test (SEBT), and center of pressure (COP) sway velocity during single-leg standing. No baseline differences existed between groups in demographic data. Adherence to neuromuscular warm-up was 88.7 %. Mean COP sway velocity decreased significantly over time in the intervention group (-14.4 %; p  control group (-6.2 %; p  = 0.056). However, these effects did not differ significantly between groups ( p  = .098). Mean changes over time in the SEBT score were significantly greater ( p  = .014) in the intervention group (+5.48) compared to the control group (+3.45). Paired t-tests revealed that the first significant balance improvements were observed after 6 weeks of training. A neuromuscular warm-up positively influences balance variables associated with an increased risk of lower extremity injuries in female handball athletes. The course of adaptations suggests that a training volume of 15 min, three times weekly over at least six weeks produces measurable changes. Retrospectively registered on 4th October 2016. Registry: clinicaltrials.gov. Trial number: NCT02925377.

An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

Science.gov (United States)

Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

2008-01-01

This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

Controlling smart grid adaptivity

OpenAIRE

Toersche, Hermen; Nykamp, Stefan; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria

2012-01-01

Methods are discussed for planning oriented smart grid control to cope with scenarios with limited predictability, supporting an increasing penetration of stochastic renewable resources. The performance of these methods is evaluated with simulations using measured wind generation and consumption data. Forecast errors are shown to affect worst case behavior in particular, the severity of which depends on the chosen adaptivity strategy and error model.

Spectrum of Slip Processes on the Subduction Interface in a Continuum Framework Resolved by Rate-and State Dependent Friction and Adaptive Time Stepping

Science.gov (United States)

Herrendoerfer, R.; van Dinther, Y.; Gerya, T.

2015-12-01

To explore the relationships between subduction dynamics and the megathrust earthquake potential, we have recently developed a numerical model that bridges the gap between processes on geodynamic and earthquake cycle time scales. In a self-consistent, continuum-based framework including a visco-elasto-plastic constitutive relationship, cycles of megathrust earthquake-like ruptures were simulated through a purely slip rate-dependent friction, albeit with very low slip rates (van Dinther et al., JGR, 2013). In addition to much faster earthquakes, a range of aseismic slip processes operate at different time scales in nature. These aseismic processes likely accommodate a considerable amount of the plate convergence and are thus relevant in order to estimate the long-term seismic coupling and related hazard in subduction zones. To simulate and resolve this wide spectrum of slip processes, we innovatively implemented rate-and state dependent friction (RSF) and an adaptive time-stepping into our continuum framework. The RSF formulation, in contrast to our previous friction formulation, takes the dependency of frictional strength on a state variable into account. It thereby allows for continuous plastic yielding inside rate-weakening regions, which leads to aseismic slip. In contrast to the conventional RSF formulation, we relate slip velocities to strain rates and use an invariant formulation. Thus we do not require the a priori definition of infinitely thin, planar faults in a homogeneous elastic medium. With this new implementation of RSF, we succeed to produce consistent cycles of frictional instabilities. By changing the frictional parameter a, b, and the characteristic slip distance, we observe a transition from stable sliding to stick-slip behaviour. This transition is in general agreement with predictions from theoretical estimates of the nucleation size, thereby to first order validating our implementation. By incorporating adaptive time-stepping based on a

Controlling the local false discovery rate in the adaptive Lasso

KAUST Repository

Sampson, J. N.

2013-04-09

The Lasso shrinkage procedure achieved its popularity, in part, by its tendency to shrink estimated coefficients to zero, and its ability to serve as a variable selection procedure. Using data-adaptive weights, the adaptive Lasso modified the original procedure to increase the penalty terms for those variables estimated to be less important by ordinary least squares. Although this modified procedure attained the oracle properties, the resulting models tend to include a large number of "false positives" in practice. Here, we adapt the concept of local false discovery rates (lFDRs) so that it applies to the sequence, λn, of smoothing parameters for the adaptive Lasso. We define the lFDR for a given λn to be the probability that the variable added to the model by decreasing λn to λn-δ is not associated with the outcome, where δ is a small value. We derive the relationship between the lFDR and λn, show lFDR =1 for traditional smoothing parameters, and show how to select λn so as to achieve a desired lFDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate specific antigen.

Adaptive self-correcting control system

International Nuclear Information System (INIS)

Ellis, S.H.

1984-01-01

A control system for regulating a controlled device or process, such as a turbofan engine, produces independent multiple estimates of one or more controlled variables of the device or process by combining the signals from a plurality of feedback sensors, which provide information related to the controlled variables, in weighted nonordered pairs. The independent multiple estimates of each controlled variable are combined into a weighted average, and individual estimates which differ by more than a specified amount from the weighted average are edited and temporarily removed from consideration. A revised weighted average value of each controlled variable is then produced, and this value is used to limit or control operation of the device or process. Adaptive trim is provided to compensate for changes in the device or process being controlled, such as engine deterioration, by slowly trimming each individual estimate toward the mean, and includes error compensation which constrains the weighted sum of the adaptive trims to equal zero, thereby preventing the adaptive trim from changing the operating level of the device or process. A secondary editing circuit based on a majority rule principle identifies a failed feedback sensor and permanently excludes all individual estimates of the controlled variable based on the failed sensor. Editing boundaries are increased and adaptive trim rate is varied when a transient occurs in the operation of the device or process. Further transient compensation may be required for a system with more severe transient requirements, and this invention includes compensation to selected feedback parameters such as turbine temperature to account for differences between steady state and transient values

Adaptive control of solar energy collector systems

CERN Document Server

Lemos, João M; Igreja, José M

2014-01-01

This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts

Walking Flexibility after Hemispherectomy: Split-Belt Treadmill Adaptation and Feedback Control

Science.gov (United States)

Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.

2009-01-01

Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…

Robust Optimal Adaptive Control Method with Large Adaptive Gain

Science.gov (United States)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Coordinating IMC-PID and adaptive SMC controllers for a PEMFC.

Science.gov (United States)

Wang, Guo-Liang; Wang, Yong; Shi, Jun-Hai; Shao, Hui-He

2010-01-01

For a Proton Exchange Membrane Fuel Cell (PEMFC) power plant with a methanol reformer, the process parameters and power output are considered simultaneously to avoid violation of the constraints and to keep the fuel cell power plant safe and effective. In this paper, a novel coordinating scheme is proposed by combining an Internal Model Control (IMC) based PID Control and adaptive Sliding Mode Control (SMC). The IMC-PID controller is designed for the reformer of the fuel flow rate according to the expected first-order dynamic properties. The adaptive SMC controller of the fuel cell current has been designed using the constant plus proportional rate reaching law. The parameters of the SMC controller are adaptively tuned according to the response of the fuel flow rate control system. When the power output controller feeds back the current references to these two controllers, the coordinating controllers system works in a system-wide way. The simulation results of the PEMFC power plant demonstrate the effectiveness of the proposed method. 2009 ISA. Published by Elsevier Ltd. All rights reserved.

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Science.gov (United States)

Nguyen, Nhan T.

2018-01-01

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Neural network based adaptive control for nonlinear dynamic regimes

Science.gov (United States)

Shin, Yoonghyun

Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

Locomotor adaptation to a powered ankle-foot orthosis depends on control method

Directory of Open Access Journals (Sweden)

Gordon Keith E

2007-12-01

Full Text Available Abstract Background We studied human locomotor adaptation to powered ankle-foot orthoses with the intent of identifying differences between two different orthosis control methods. The first orthosis control method used a footswitch to provide bang-bang control (a kinematic control and the second orthosis control method used a proportional myoelectric signal from the soleus (a physiological control. Both controllers activated an artificial pneumatic muscle providing plantar flexion torque. Methods Subjects walked on a treadmill for two thirty-minute sessions spaced three days apart under either footswitch control (n = 6 or myoelectric control (n = 6. We recorded lower limb electromyography (EMG, joint kinematics, and orthosis kinetics. We compared stance phase EMG amplitudes, correlation of joint angle patterns, and mechanical work performed by the powered orthosis between the two controllers over time. Results During steady state at the end of the second session, subjects using proportional myoelectric control had much lower soleus and gastrocnemius activation than the subjects using footswitch control. The substantial decrease in triceps surae recruitment allowed the proportional myoelectric control subjects to walk with ankle kinematics close to normal and reduce negative work performed by the orthosis. The footswitch control subjects walked with substantially perturbed ankle kinematics and performed more negative work with the orthosis. Conclusion These results provide evidence that the choice of orthosis control method can greatly alter how humans adapt to powered orthosis assistance during walking. Specifically, proportional myoelectric control results in larger reductions in muscle activation and gait kinematics more similar to normal compared to footswitch control.

Adaptive Command Filtered Integrated Guidance and Control for Hypersonic Vehicle with Magnitude, Rate and Bandwidth Constraints

Directory of Open Access Journals (Sweden)

Wang Liang

2018-01-01

Full Text Available This paper proposes a novel integrated guidance and control (IGC method for hypersonic vehicle in terminal phase. Firstly, the system model is developed with a second order actuator dynamics. Then the back-stepping controller is designed hierarchically with command filters, where the first order command filters are implemented to construct the virtual control input with ideal states predicted by an adaptive estimator, and the nonlinear command filter is designed to produce magnitude, rate and bandwidth limited control surface deflection finally tracked by a terminal sliding mode controller with finite convergence time. Through a series of 6-DOF numerical simulations, it’s indicated that the proposed method successfully cancels out the large aerodynamics coefficient uncertainties and disturbances in hypersonic flight under limited control surface deflection. The contribution of this paper lies in the application and determination of nonlinear integrated design of guidance and control system for hypersonic vehicle.

Effects of glycemic control on saliva flow rates and protein composition in non-insulin-dependent diabetes mellitus.

Science.gov (United States)

Dodds, M W; Dodds, A P

1997-04-01

The objective of this study was to determine whether improvements in the level of diabetic control in a group of subjects with poorly controlled non-insulin-dependent diabetes mellitus influence salivary output and composition. Repeated whole unstimulated and stimulated parotid saliva samples were collected from diabetic patients attending an outpatient diabetes education program and a matched nondiabetic control group. Saliva was analyzed for flow rates, parotid protein concentration and composition, and amylase activity. Subjective responses to questions about salivary hypofunction were tested. There were no significant differences in whole unstimulated and stimulated parotid flow rates or stimulated parotid protein concentration and composition between diabetics and the control group. Amylase activity was higher in diabetics and decreased with improved glycemic control. Subjects reporting taste alterations had higher mean blood glucose levels than subjects with normal taste sensation. Poorly controlled non-insulin-dependent diabetes mellitus has no influence on saliva output, although amylase activity may be elevated, and there may be taste alterations.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

Energy Technology Data Exchange (ETDEWEB)

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune; Andrea Francini; Lisa Zhang

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet. The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks

Designing adaptive integral sliding mode control for heart rate regulation during cycle-ergometer exercise using bio-feedback.

Science.gov (United States)

Argha, Ahmadreza; Su, Steven W; Nguyen, Hung; Celler, Branko G

2015-01-01

This paper considers our developed control system which aims to regulate the exercising subjects' heart rate (HR) to a predefined profile. The controller would be an adaptive integral sliding mode controller. Here it is assumed that the controller commands are interpreted as biofeedback auditory commands. These commands can be heard and implemented by the exercising subject as a part of the control-loop. However, transmitting a feedback signal while the pedals are not in the appropriate position to efficiently exert force may lead to a cognitive disengagement of the user from the feedback controller. To address this problem this paper will employ a different form of control system regarding as "actuator-based event-driven control system". This paper will claim that the developed event-driven controller makes it possible to effectively regulate HR to a predetermined HR profile.

Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

Science.gov (United States)

Eshak, Peter B.

the explored derivatives. Biases were considered in the range -500% to 500% and delays in the range 0.5 to 40 seconds. The stability and control derivatives considered in this research effort are a combination of decoupled derivatives in the three channels, longitudinal, lateral, and directional. Numerous simulation scenarios and flight conditions are considered to provide more credibility to the obtained results. In addition, a statistical analysis has been conducted to assess the results. The performance of the control laws has been evaluated in terms of the integral of the error in tracking the three desired angular rates, pitch, roll, and yaw. In addition, the effort of the neural networks exerted to compensate for tracking errors is considered in the analysis as well. The results show that in order to obtain reliable estimates for the investigated derivatives, the estimator needs to generate values with less than five seconds delay. In addition, derivatives estimates are within 50% or -15% off the exact values. Moreover, the importance of updating derivatives depends on the maneuver scenario and the flight condition. The estimation process at quasi-steady state conditions provides reliable estimates as opposed to estimation during fast dynamic changes; also, the estimation process has better performance at large rate of change of derivatives values.

Adaptive Control Algorithm of the Synchronous Generator

Directory of Open Access Journals (Sweden)

Shevchenko Victor

2017-01-01

Full Text Available The article discusses the the problem of controlling a synchronous generator, namely, maintaining the stability of the control object in the conditions of occurrence of noise and disturbances in the regulatory process. The model of a synchronous generator is represented by a system of differential equations of Park-Gorev, where state variables are computed relative to synchronously rotating d, q-axis. Management of synchronous generator is proposed to organize on the basis of the position-path control using algorithms to adapt with the reference model. Basic control law directed on the stabilizing indicators the frequency generated by the current and the required power level, which is achieved by controlling the mechanical torque on the shaft of the turbine and the value of the excitation voltage of the synchronous generator. Modification of the classic adaptation algorithm using the reference model, allowing to minimize the error of the reference regulation and the model under investigation within the prescribed limits, produced by means of the introduction of additional variables controller adaptation in the model. Сarried out the mathematical modeling of control provided influence on the studied model of continuous nonlinear and unmeasured the disturbance. Simulation results confirm the high level accuracy of tracking and adaptation investigated model with respect to the reference, and the present value of the loop error depends on parameters performance of regulator.

View-Dependent Adaptive Cloth Simulation with Buckling Compensation.

Science.gov (United States)

Koh, Woojong; Narain, Rahul; O'Brien, James F

2015-10-01

This paper describes a method for view-dependent cloth simulation using dynamically adaptive mesh refinement and coarsening. Given a prescribed camera motion, the method adjusts the criteria controlling refinement to account for visibility and apparent size in the camera's view. Objectionable dynamic artifacts are avoided by anticipative refinement and smoothed coarsening, while locking in extremely coarsened regions is inhibited by modifying the material model to compensate for unresolved sub-element buckling. This approach preserves the appearance of detailed cloth throughout the animation while avoiding the wasted effort of simulating details that would not be discernible to the viewer. The computational savings realized by this method increase as scene complexity grows. The approach produces a 2× speed-up for a single character and more than 4× for a small group as compared to view-independent adaptive simulations, and respectively 5× and 9× speed-ups as compared to non-adaptive simulations.

High rate of adaptation of mammalian proteins that interact with Plasmodium and related parasites

Science.gov (United States)

Telis, Natalie; Petrov, Dmitri A.

2017-01-01

Plasmodium parasites, along with their Piroplasm relatives, have caused malaria-like illnesses in terrestrial mammals for millions of years. Several Plasmodium-protective alleles have recently evolved in human populations, but little is known about host adaptation to blood parasites over deeper evolutionary timescales. In this work, we analyze mammalian adaptation in ~500 Plasmodium- or Piroplasm- interacting proteins (PPIPs) manually curated from the scientific literature. We show that (i) PPIPs are enriched for both immune functions and pleiotropy with other pathogens, and (ii) the rate of adaptation across mammals is significantly elevated in PPIPs, compared to carefully matched control proteins. PPIPs with high pathogen pleiotropy show the strongest signatures of adaptation, but this pattern is fully explained by their immune enrichment. Several pieces of evidence suggest that blood parasites specifically have imposed selection on PPIPs. First, even non-immune PPIPs that lack interactions with other pathogens have adapted at twice the rate of matched controls. Second, PPIP adaptation is linked to high expression in the liver, a critical organ in the parasite life cycle. Finally, our detailed investigation of alpha-spectrin, a major red blood cell membrane protein, shows that domains with particularly high rates of adaptation are those known to interact specifically with P. falciparum. Overall, we show that host proteins that interact with Plasmodium and Piroplasm parasites have experienced elevated rates of adaptation across mammals, and provide evidence that some of this adaptation has likely been driven by blood parasites. PMID:28957326

Developed adaptive neuro-fuzzy algorithm to control air conditioning ...

African Journals Online (AJOL)

The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy inference system was implemented and utilized for modeling and controller design. In addition, the estimation of the heat transfer rate and water mass flow rate ...

Multivariable adaptive control of bio process

Energy Technology Data Exchange (ETDEWEB)

Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique

1995-12-31

This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.

Reinforcer magnitude and rate dependency: evaluation of resistance-to-change mechanisms.

Science.gov (United States)

Pinkston, Jonathan W; Ginsburg, Brett C; Lamb, Richard J

2014-10-01

Under many circumstances, reinforcer magnitude appears to modulate the rate-dependent effects of drugs such that when schedules arrange for relatively larger reinforcer magnitudes rate dependency is attenuated compared with behavior maintained by smaller magnitudes. The current literature on resistance to change suggests that increased reinforcer density strengthens operant behavior, and such strengthening effects appear to extend to the temporal control of behavior. As rate dependency may be understood as a loss of temporal control, the effects of reinforcer magnitude on rate dependency may be due to increased resistance to disruption of temporally controlled behavior. In the present experiments, pigeons earned different magnitudes of grain during signaled components of a multiple FI schedule. Three drugs, clonidine, haloperidol, and morphine, were examined. All three decreased overall rates of key pecking; however, only the effects of clonidine were attenuated as reinforcer magnitude increased. An analysis of within-interval performance found rate-dependent effects for clonidine and morphine; however, these effects were not modulated by reinforcer magnitude. In addition, we included prefeeding and extinction conditions, standard tests used to measure resistance to change. In general, rate-decreasing effects of prefeeding and extinction were attenuated by increasing reinforcer magnitudes. Rate-dependent analyses of prefeeding showed rate-dependency following those tests, but in no case were these effects modulated by reinforcer magnitude. The results suggest that a resistance-to-change interpretation of the effects of reinforcer magnitude on rate dependency is not viable.

Towards Self-adaptation for Dependable Service-Oriented Systems

Science.gov (United States)

Cardellini, Valeria; Casalicchio, Emiliano; Grassi, Vincenzo; Lo Presti, Francesco; Mirandola, Raffaela

Increasingly complex information systems operating in dynamic environments ask for management policies able to deal intelligently and autonomously with problems and tasks. An attempt to deal with these aspects can be found in the Service-Oriented Architecture (SOA) paradigm that foresees the creation of business applications from independently developed services, where services and applications build up complex dependencies. Therefore the dependability of SOA systems strongly depends on their ability to self-manage and adapt themselves to cope with changes in the operating conditions and to meet the required dependability with a minimum of resources. In this paper we propose a model-based approach to the realization of self-adaptable SOA systems, aimed at the fulfillment of dependability requirements. Specifically, we provide a methodology driving the system adaptation and we discuss the architectural issues related to its implementation. To bring this approach to fruition, we developed a prototype tool and we show the results that can be achieved with a simple example.

Adaptive Controller Effects on Pilot Behavior

Science.gov (United States)

Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

2014-01-01

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

The adaptation rate of terrestrial ecosystems as a critical factor in global climate dynamics

Energy Technology Data Exchange (ETDEWEB)

Fuessler, J S; Gassmann, F [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1999-08-01

A conceptual climate model describing regional two-way atmosphere-vegetation interaction has been extended by a simple qualitative scheme of ecosystem adaptation to drought stress. The results of this explorative study indicate that the role of terrestrial vegetation under different forcing scenarios depends crucially on the rate of the ecosystems adaptation to drought stress. The faster the adaptation of important ecosystems such as forests the better global climate is protected from abrupt climate changes. (author) 1 fig., 3 refs.

A self-driven temperature and flow rate co-adjustment mechanism based on Shape-Memory-Alloy (SMA) assembly for an adaptive thermal control coldplate module with on-orbit service characteristics

International Nuclear Information System (INIS)

Guo, Wei; Li, Yunhua; Li, Yun-Ze; Zhong, Ming-Liang; Wang, Sheng-Nan; Wang, Ji-Xiang; Zhang, Jia-Xun

2017-01-01

Highlights: • A self-driven temperature and flow rate co-adjustment mechanism based on SMA assembly is proposed. • An adaptive thermal control coldplate module (TCCM) is introduced. • A testbed is set up to investigate the TCCM adaptive thermal management performances. • The TCCM has the potential for spacecrafts on-orbit services. - Abstract: An adaptive thermal control coldplate module (TCCM) was proposed in this paper to fulfill the requirements of modular thermal control systems for spacecrafts on-orbit services. The TCCM could provide flow rate and temperature co-adjustment by using Shape-Memory-Alloy (SMA) assembly which possesses self-driven abilities. In this paper, the adaptive thermal management mechanism of the TCCM integrated with a single phase mechanically pumped fluid loop (SPMPFL) is described in detail, a verification testbed was established to examine the TCCM dynamic characteristics. Various working conditions such as inlet temperature, flow rate and thermal load disturbances were imposed on the TCCM to inspect its startup and transient performance. It was observed that the TCCM may present robust temperature control results with low overshoot (maximum 16.8%) and small temperature control error (minimum 0.18%), fast time response (minimum 600 s) was also revealed. The results demonstrated that the well-designed TCCM provided effective autonomous flow-rate and temperature co-adjustment operations, which may be a promising candidate for realizing modular level adaptive thermal management for spacecrafts on-orbit services.

An M/M/c/K State-Dependent Model for Pedestrian Flow Control and Design of Facilities.

Directory of Open Access Journals (Sweden)

Khalidur Rahman

Full Text Available Pedestrian overflow causes queuing delay and in turn, is controlled by the capacity of a facility. Flow control or blocking control takes action to avoid queues from building up to extreme values. Thus, in this paper, the problem of pedestrian flow control in open outdoor walking facilities in equilibrium condition is investigated using M/M/c/K queuing models. State dependent service rate based on speed and density relationship is utilized. The effective rate of the Poisson arrival process to the facility is determined so as there is no overflow of pedestrians. In addition, the use of the state dependent queuing models to the design of the facilities and the effect of pedestrian personal capacity on the design and the traffic congestion are discussed. The study does not validate the sustainability of adaptation of Western design codes for the pedestrian facilities in the countries like Bangladesh.

On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

Directory of Open Access Journals (Sweden)

Saikat Kumar Shome

2015-01-01

Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

Adaptive filtering prediction and control

CERN Document Server

Goodwin, Graham C

2009-01-01

Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

Time-adaptive and history-adaptive multicriterion routing in stochastic, time-dependent networks

DEFF Research Database (Denmark)

Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan

2009-01-01

We compare two different models for multicriterion routing in stochastic time-dependent networks: the classic "time-adaptive'' model and the more flexible "history-adaptive'' one. We point out several properties of the sets of efficient solutions found under the two models. We also devise a method...

Adaptive Wavelet Coding Applied in a Wireless Control System.

Science.gov (United States)

Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O

2017-12-13

Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

Adaptive Wavelet Coding Applied in a Wireless Control System

Directory of Open Access Journals (Sweden)

Felipe O. S. Gama

2017-12-01

Full Text Available Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

Basal ganglia-dependent processes in recalling learned visual-motor adaptations.

Science.gov (United States)

Bédard, Patrick; Sanes, Jerome N

2011-03-01

Humans learn and remember motor skills to permit adaptation to a changing environment. During adaptation, the brain develops new sensory-motor relationships that become stored in an internal model (IM) that may be retained for extended periods. How the brain learns new IMs and transforms them into long-term memory remains incompletely understood since prior work has mostly focused on the learning process. A current model suggests that basal ganglia, cerebellum, and their neocortical targets actively participate in forming new IMs but that a cerebellar cortical network would mediate automatization. However, a recent study (Marinelli et al. 2009) reported that patients with Parkinson's disease (PD), who have basal ganglia dysfunction, had similar adaptation rates as controls but demonstrated no savings at recall tests (24 and 48 h). Here, we assessed whether a longer training session, a feature known to increase long-term retention of IM in healthy individuals, could allow PD patients to demonstrate savings. We recruited PD patients and age-matched healthy adults and used a visual-motor adaptation paradigm similar to the study by Marinelli et al. (2009), doubling the number of training trials and assessed recall after a short and a 24-h delay. We hypothesized that a longer training session would allow PD patients to develop an enhanced representation of the IM as demonstrated by savings at the recall tests. Our results showed that PD patients had similar adaptation rates as controls but did not demonstrate savings at both recall tests. We interpret these results as evidence that fronto-striatal networks have involvement in the early to late phase of motor memory formation, but not during initial learning.

Indirect Adaptive Attitude Control for a Ducted Fan Vertical Takeoff and Landing Microaerial Vehicle

Directory of Open Access Journals (Sweden)

Shouzhao Sheng

2015-01-01

Full Text Available The present paper addresses an attitude tracking control problem of a ducted fan microaerial vehicle. The proposed indirect adaptive controller can greatly reduce tracking error in the initial stage of the adaptive learning process by using an error compensation strategy and can achieve good capability to eliminate the adverse effect of measurement noises on the convergence of adjustable parameters. Moreover, the learning rate adaptation strategy is proposed to further minimize the adverse effect of large learning rates on the convergence of adjustable parameters. The experimental tests have illustrated the effectiveness of the proposed adaptive controller.

Layer-based buffer aware rate adaptation design for SHVC video streaming

Science.gov (United States)

Gudumasu, Srinivas; Hamza, Ahmed; Asbun, Eduardo; He, Yong; Ye, Yan

2016-09-01

This paper proposes a layer based buffer aware rate adaptation design which is able to avoid abrupt video quality fluctuation, reduce re-buffering latency and improve bandwidth utilization when compared to a conventional simulcast based adaptive streaming system. The proposed adaptation design schedules DASH segment requests based on the estimated bandwidth, dependencies among video layers and layer buffer fullness. Scalable HEVC video coding is the latest state-of-art video coding technique that can alleviate various issues caused by simulcast based adaptive video streaming. With scalable coded video streams, the video is encoded once into a number of layers representing different qualities and/or resolutions: a base layer (BL) and one or more enhancement layers (EL), each incrementally enhancing the quality of the lower layers. Such layer based coding structure allows fine granularity rate adaptation for the video streaming applications. Two video streaming use cases are presented in this paper. The first use case is to stream HD SHVC video over a wireless network where available bandwidth varies, and the performance comparison between proposed layer-based streaming approach and conventional simulcast streaming approach is provided. The second use case is to stream 4K/UHD SHVC video over a hybrid access network that consists of a 5G millimeter wave high-speed wireless link and a conventional wired or WiFi network. The simulation results verify that the proposed layer based rate adaptation approach is able to utilize the bandwidth more efficiently. As a result, a more consistent viewing experience with higher quality video content and minimal video quality fluctuations can be presented to the user.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

Science.gov (United States)

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Neural network-based model reference adaptive control system.

Science.gov (United States)

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

Directory of Open Access Journals (Sweden)

Xin Zuo

2017-01-01

Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

Adaptive Control with Reference Model Modification

Science.gov (United States)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

Poststroke Hemiparesis Impairs the Rate but not Magnitude of Adaptation of Spatial and Temporal Locomotor Features

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Savin, Douglas N.; Tseng, Shih-Chiao; Whitall, Jill; Morton, Susanne M.

2015-01-01

Background Persons with stroke and hemiparesis walk with a characteristic pattern of spatial and temporal asymmetry that is resistant to most traditional interventions. It was recently shown in nondisabled persons that the degree of walking symmetry can be readily altered via locomotor adaptation. However, it is unclear whether stroke-related brain damage affects the ability to adapt spatial or temporal gait symmetry. Objective Determine whether locomotor adaptation to a novel swing phase perturbation is impaired in persons with chronic stroke and hemiparesis. Methods Participants with ischemic stroke (14) and nondisabled controls (12) walked on a treadmill before, during, and after adaptation to a unilateral perturbing weight that resisted forward leg movement. Leg kinematics were measured bilaterally, including step length and single-limb support (SLS) time symmetry, limb angle center of oscillation, and interlimb phasing, and magnitude of “initial” and “late” locomotor adaptation rates were determined. Results All participants had similar magnitudes of adaptation and similar initial adaptation rates both spatially and temporally. All 14 participants with stroke and baseline asymmetry temporarily walked with improved SLS time symmetry after adaptation. However, late adaptation rates poststroke were decreased (took more strides to achieve adaptation) compared with controls. Conclusions Mild to moderate hemiparesis does not interfere with the initial acquisition of novel symmetrical gait patterns in both the spatial and temporal domains, though it does disrupt the rate at which “late” adaptive changes are produced. Impairment of the late, slow phase of learning may be an important rehabilitation consideration in this patient population. PMID:22367915

Mechanosensation and Adaptive Motor Control in Insects.

Science.gov (United States)

Tuthill, John C; Wilson, Rachel I

2016-10-24

The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive control of robotic manipulators

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Seraji, H.

1987-01-01

The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

Hybrid adaptive ascent flight control for a flexible launch vehicle

Science.gov (United States)

Lefevre, Brian D.

For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

Neural predictors of sensorimotor adaptation rate and savings.

Science.gov (United States)

Cassady, Kaitlin; Ruitenberg, Marit; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos Castenada, Roy; Kofman, Igor; Bloomberg, Jacob; Mulavara, Ajitkumar; Seidler, Rachael

2018-04-01

In this study, we investigate whether individual variability in the rate of visuomotor adaptation and multiday savings is associated with differences in regional gray matter volume and resting-state functional connectivity. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. Functional connectivity strength between sensorimotor, dorsal cingulate, and temporoparietal regions of the brain was found to predict the rate of learning during the early phase of the adaptation task. In contrast, default mode network connectivity strength was found to predict both the rate of learning during the late adaptation phase and savings. As for structural predictors, greater gray matter volume in temporoparietal and occipital regions predicted faster early learning, whereas greater gray matter volume in superior posterior regions of the cerebellum predicted faster late learning. These findings suggest that the offline neural predictors of early adaptation may facilitate the cognitive aspects of sensorimotor adaptation, supported by the involvement of temporoparietal and cingulate networks. The offline neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. © 2017 Wiley Periodicals, Inc.

Adaptive model predictive process control using neural networks

Science.gov (United States)

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

How much do genetic covariances alter the rate of adaptation?

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Agrawal, Aneil F; Stinchcombe, John R

2009-03-22

Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.

How adaptation shapes spike rate oscillations in recurrent neuronal networks

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Moritz eAugustin

2013-02-01

Full Text Available Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 Hz to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.

Wavelet Adaptive Algorithm and Its Application to MRE Noise Control System

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Zhang Yulin

2015-01-01

Full Text Available To address the limitation of conventional adaptive algorithm used for active noise control (ANC system, this paper proposed and studied two adaptive algorithms based on Wavelet. The twos are applied to a noise control system including magnetorheological elastomers (MRE, which is a smart viscoelastic material characterized by a complex modulus dependent on vibration frequency and controllable by external magnetic fields. Simulation results reveal that the Decomposition LMS algorithm (D-LMS and Decomposition and Reconstruction LMS algorithm (DR-LMS based on Wavelet can significantly improve the noise reduction performance of MRE control system compared with traditional LMS algorithm.

Effects of Yoga on Stress, Stress Adaption, and Heart Rate Variability Among Mental Health Professionals--A Randomized Controlled Trial.

Science.gov (United States)

Lin, Shu-Ling; Huang, Ching-Ya; Shiu, Shau-Ping; Yeh, Shu-Hui

2015-08-01

Mental health professionals experiencing work-related stress may experience burn out, leading to a negative impact on their organization and patients. The aim of this study was to examine the effects of yoga classes on work-related stress, stress adaptation, and autonomic nerve activity among mental health professionals. A randomized controlled trial was used, which compared the outcomes between the experimental (e.g., yoga program) and the control groups (e.g., no yoga exercise) for 12 weeks. Work-related stress and stress adaptation were assessed before and after the program. Heart rate variability (HRV) was measured at baseline, midpoint through the weekly yoga classes (6 weeks), and postintervention (after 12 weeks of yoga classes). The results showed that the mental health professionals in the yoga group experienced a significant reduction in work-related stress (t = -6.225, p control group revealed no significant changes. Comparing the mean differences in pre- and posttest scores between yoga and control groups, we found the yoga group significantly decreased work-related stress (t = -3.216, p = .002), but there was no significant change in stress adaptation (p = .084). While controlling for the pretest scores of work-related stress, participants in yoga, but not the control group, revealed a significant increase in autonomic nerve activity at midpoint (6 weeks) test (t = -2.799, p = .007), and at posttest (12 weeks; t = -2.099, p = .040). Because mental health professionals experienced a reduction in work-related stress and an increase in autonomic nerve activity in a weekly yoga program for 12 weeks, clinicians, administrators, and educators should offer yoga classes as a strategy to help health professionals reduce their work-related stress and balance autonomic nerve activities. © 2015 The Authors. Worldviews on Evidence-Based Nursing published by Wiley Periodicals, Inc. on behalf of Society for Worldviews on Evidence-Based Nursing.

Engineering of Fast and Robust Adaptive Control for Fixed-Wing Unmanned Aircraft

Science.gov (United States)

2017-06-01

evaluate the use of adaptive control on fixed-wing unmanned aircraft . The growing demand for unmanned systems will inherit the costs associated with...aerospace environment . 2.2 Classical Feedback vs Adaptive Control Control of a system can be categorized into two required elements; the requirement to...stabilize the system in the presence of: 1. disturbances that affect the controlled states and outputs (pitch rate perturbation caused by environmental

Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan

2013-01-01

This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

Rate-adaptive BCH codes for distributed source coding

DEFF Research Database (Denmark)

Salmistraro, Matteo; Larsen, Knud J.; Forchhammer, Søren

2013-01-01

This paper considers Bose-Chaudhuri-Hocquenghem (BCH) codes for distributed source coding. A feedback channel is employed to adapt the rate of the code during the decoding process. The focus is on codes with short block lengths for independently coding a binary source X and decoding it given its...... strategies for improving the reliability of the decoded result are analyzed, and methods for estimating the performance are proposed. In the analysis, noiseless feedback and noiseless communication are assumed. Simulation results show that rate-adaptive BCH codes achieve better performance than low...... correlated side information Y. The proposed codes have been analyzed in a high-correlation scenario, where the marginal probability of each symbol, Xi in X, given Y is highly skewed (unbalanced). Rate-adaptive BCH codes are presented and applied to distributed source coding. Adaptive and fixed checking...

Adaptive control of port-Hamiltonian systems

NARCIS (Netherlands)

Dirksz, D.A.; Scherpen, J.M.A.; Edelmayer, András

2010-01-01

In this paper an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation theory for

Video flow active control by means of adaptive shifted foveal geometries

Science.gov (United States)

Urdiales, Cristina; Rodriguez, Juan A.; Bandera, Antonio J.; Sandoval, Francisco

2000-10-01

This paper presents a control mechanism for video transmission that relies on transmitting non-uniform resolution images depending on the delay of the communication channel. These images are built in an active way to keep the areas of interest of the image at the highest resolution available. In order to shift the area of high resolution over the image and to achieve a data structure easy to process by using conventional algorithms, a shifted fovea multi resolution geometry of adaptive size is used. Besides, if delays are nevertheless too high, the different areas of resolution of the image can be transmitted at different rates. A functional system has been developed for corridor surveillance with static cameras. Tests with real video images have proven that the method allows an almost constant rate of images per second as long as the channel is not collapsed.

Extreme-value dependence: An application to exchange rate markets

Science.gov (United States)

Fernandez, Viviana

2007-04-01

Extreme value theory (EVT) focuses on modeling the tail behavior of a loss distribution using only extreme values rather than the whole data set. For a sample of 10 countries with dirty/free float regimes, we investigate whether paired currencies exhibit a pattern of asymptotic dependence. That is, whether an extremely large appreciation or depreciation in the nominal exchange rate of one country might transmit to another. In general, after controlling for volatility clustering and inertia in returns, we do not find evidence of extreme-value dependence between paired exchange rates. However, for asymptotic-independent paired returns, we find that tail dependency of exchange rates is stronger under large appreciations than under large depreciations.

A globally convergent MC algorithm with an adaptive learning rate.

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Peng, Dezhong; Yi, Zhang; Xiang, Yong; Zhang, Haixian

2012-02-01

This brief deals with the problem of minor component analysis (MCA). Artificial neural networks can be exploited to achieve the task of MCA. Recent research works show that convergence of neural networks based MCA algorithms can be guaranteed if the learning rates are less than certain thresholds. However, the computation of these thresholds needs information about the eigenvalues of the autocorrelation matrix of data set, which is unavailable in online extraction of minor component from input data stream. In this correspondence, we introduce an adaptive learning rate into the OJAn MCA algorithm, such that its convergence condition does not depend on any unobtainable information, and can be easily satisfied in practical applications.

Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

Directory of Open Access Journals (Sweden)

Guofeng Tong

2014-04-01

Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

An implicit adaptation algorithm for a linear model reference control system

Science.gov (United States)

Mabius, L.; Kaufman, H.

1975-01-01

This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.

Direct adaptive control of a PUMA 560 industrial robot

Science.gov (United States)

Seraji, Homayoun; Lee, Thomas; Delpech, Michel

1989-01-01

The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

Limited interlimb transfer of locomotor adaptations to a velocity-dependent force field during unipedal walking.

Science.gov (United States)

Houldin, Adina; Chua, Romeo; Carpenter, Mark G; Lam, Tania

2012-08-01

Several studies have demonstrated that motor adaptations to a novel task environment can be transferred between limbs. Such interlimb transfer of motor commands is consistent with the notion of centrally driven strategies that can be generalized across different frames of reference. So far, studies of interlimb transfer of locomotor adaptations have yielded disparate results. Here we sought to determine whether locomotor adaptations in one (trained) leg show transfer to the other (test) leg during a unipedal walking task. We hypothesized that adaptation in the test leg to a velocity-dependent force field previously experienced by the trained leg will be faster, as revealed by faster recovery of kinematic errors and earlier onset of aftereffects. Twenty able-bodied adults walked unipedally in the Lokomat robotic gait orthosis, which applied velocity-dependent resistance to the legs. The amount of resistance was scaled to 10% of each individual's maximum voluntary contraction of the hip flexors. Electromyography and kinematics of the lower limb were recorded. All subjects were right-leg dominant and were tested for transfer of motor adaptations from the right leg to the left leg. Catch trials, consisting of unexpected removal of resistance, were presented after the first step with resistance and after a period of adaptation to test for aftereffects. We found no significant differences in the sizes of the aftereffects between the two legs, except for peak hip flexion during swing, or in the rate at which peak hip flexion adapted during steps against resistance between the two legs. Our results indicate that interlimb transfer of these types of locomotor adaptation is not a robust phenomenon. These findings add to our current understanding of motor adaptations and provide further evidence that generalization of adaptations may be dependent on the movement task.

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

Science.gov (United States)

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Adaptation of feedforward movement control is abnormal in patients with cervical dystonia and tremor.

Science.gov (United States)

Avanzino, Laura; Ravaschio, Andrea; Lagravinese, Giovanna; Bonassi, Gaia; Abbruzzese, Giovanni; Pelosin, Elisa

2018-01-01

It is under debate whether the cerebellum plays a role in dystonia pathophysiology and in the expression of clinical phenotypes. We investigated a typical cerebellar function (anticipatory movement control) in patients with cervical dystonia (CD) with and without tremor. Twenty patients with CD, with and without tremor, and 17 healthy controls were required to catch balls of different load: 15 trials with a light ball, 25 trials with a heavy ball (adaptation) and 15 trials with a light ball (post-adaptation). Arm movements were recorded using a motion capture system. We evaluated: (i) the anticipatory adjustment (just before the impact); (ii) the extent and rate of the adaptation (at the impact) and (iii) the aftereffect in the post-adaptation phase. The anticipatory adjustment was reduced during adaptation in CD patients with tremor respect to CD patients without tremor and controls. The extent and rate of adaptation and the aftereffect in the post-adaptation phase were smaller in CD with tremor than in controls and CD without tremor. Patients with cervical dystonia and tremor display an abnormal predictive movement control. Our findings point to a possible role of cerebellum in the expression of a clinical phenotype in dystonia. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Adaptive sequential controller

Energy Technology Data Exchange (ETDEWEB)

El-Sharkawi, Mohamed A. (Renton, WA); Xing, Jian (Seattle, WA); Butler, Nicholas G. (Newberg, OR); Rodriguez, Alonso (Pasadena, CA)

1994-01-01

An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

Adaptive sequential controller

Science.gov (United States)

El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

1994-01-01

An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

Activity and heart rate in semi-domesticated reindeer during adaptation to emergency feeding.

Science.gov (United States)

Nilsson, A; Ahman, B; Norberg, H; Redbo, I; Eloranta, E; Olsson, K

2006-06-15

Although reindeer are well adapted to limited food resources during winter, semi-domesticated reindeer are regularly fed when snow conditions are bad in order to prevent starvation. Feeding sometimes results in health problems and loss of animals. This study was made to assess if activity pattern in reindeer could be used as a tool for the reindeer herder in early detection of animals that are not adapting to feeding. The frequency of 10 behavioural categories was recorded in five groups of penned, eight-month-old, female semi-domesticated reindeer. Three reindeer per group were fitted with heart rate monitors. Lying was the most frequent behaviour, whilst there were few cases of agonistic behaviour. Heart rate varied during the day, with peaks during feeding and low heart rates in the early morning. Restricted feed intake resulted in more locomotion and seeking but less ruminating compared to feeding ad libitum. This was followed by a generally lower heart rate in reindeer in the restricted groups compared to controls. Subsequent feeding with different combinations of lichens, silage and pellets ad libitum resulted initially in significantly more of the animals lying curled up, compared to controls, combined with increased heart rates. As the experiment continued the general activity pattern, as well as the heart rate, gradually became more similar in all groups. Lying curled was the behavioural indicator most consistently affected by feed deprivation and adaptation to feeding and may thus be a useful indicator to distinguish individual reindeer that are not adjusting to feeding.

A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

Science.gov (United States)

Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

Adaptive Extremum Control and Wind Turbine Control

DEFF Research Database (Denmark)

Ma, Xin

1997-01-01

This thesis is divided into two parts, i.e., adaptive extremum control and modelling and control of a wind turbine. The rst part of the thesis deals with the design of adaptive extremum controllers for some processes which have the behaviour that process should have as high e ciency as possible...... in parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important....... Firstly, it is assumed that the nonlinear processes can be divided into a dynamic linear part and static nonlinear part. Consequently the processes with input nonlinearity and output nonlinearity are treated separately. With the nonlinearity at the input it is easy to set up a model which is linear...

Controlling the Rate of GWAS False Discoveries.

Science.gov (United States)

Brzyski, Damian; Peterson, Christine B; Sobczyk, Piotr; Candès, Emmanuel J; Bogdan, Malgorzata; Sabatti, Chiara

2017-01-01

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study. Copyright © 2017 by the Genetics Society of America.

Predictor-Based Model Reference Adaptive Control

Science.gov (United States)

Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

A new rate-dependent model for high-frequency tracking performance enhancement of piezoactuator system

Science.gov (United States)

Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

2017-05-01

Feedforward-feedback control is widely used in motion control of piezoactuator systems. Due to the phase lag caused by incomplete dynamics compensation, the performance of the composite controller is greatly limited at high frequency. This paper proposes a new rate-dependent model to improve the high-frequency tracking performance by reducing dynamics compensation error. The rate-dependent model is designed as a function of the input and input variation rate to describe the input-output relationship of the residual system dynamics which mainly performs as phase lag in a wide frequency band. Then the direct inversion of the proposed rate-dependent model is used to compensate the residual system dynamics. Using the proposed rate-dependent model as feedforward term, the open loop performance can be improved significantly at medium-high frequency. Then, combining the with feedback controller, the composite controller can provide enhanced close loop performance from low frequency to high frequency. At the frequency of 1 Hz, the proposed controller presents the same performance as previous methods. However, at the frequency of 900 Hz, the tracking error is reduced to be 30.7% of the decoupled approach.

Robustness of non-interdependent and interdependent networks against dependent and adaptive attacks

Science.gov (United States)

Tyra, Adam; Li, Jingtao; Shang, Yilun; Jiang, Shuo; Zhao, Yanjun; Xu, Shouhuai

2017-09-01

Robustness of complex networks has been extensively studied via the notion of site percolation, which typically models independent and non-adaptive attacks (or disruptions). However, real-life attacks are often dependent and/or adaptive. This motivates us to characterize the robustness of complex networks, including non-interdependent and interdependent ones, against dependent and adaptive attacks. For this purpose, dependent attacks are accommodated by L-hop percolation where the nodes within some L-hop (L ≥ 0) distance of a chosen node are all deleted during one attack (with L = 0 degenerating to site percolation). Whereas, adaptive attacks are launched by attackers who can make node-selection decisions based on the network state in the beginning of each attack. The resulting characterization enriches the body of knowledge with new insights, such as: (i) the Achilles' Heel phenomenon is only valid for independent attacks, but not for dependent attacks; (ii) powerful attack strategies (e.g., targeted attacks and dependent attacks, dependent attacks and adaptive attacks) are not compatible and cannot help the attacker when used collectively. Our results shed some light on the design of robust complex networks.

Engaging a moving target: Adapting to rates of climate change

Science.gov (United States)

Shayegh, S.; Caldeira, K.; Moreno-Cruz, J.

2015-12-01

Climate change is affecting the planet and its human and natural systems at an increasing rate. As temperatures continue to rise, the international community has increasingly been considering adaptation measures to prepare for future climate change. However, most discussion around adaptation strategies has focused on preparedness for some expected amount of climate change impacts, e.g. 2 meters sea level rise. In this study, we discuss adaptation to rates of change as an alternative conceptual framework for thinking about adaptation. Adaptation is not only about adapting to amounts of change, but the rate at which these changes occur is also critically important. We ground our discussion with an example of optimal coastal investment in the face of ongoing sea level rise. Sea level rise threatens coastal assets. Finite resources could be devoted to building infrastructure further inland or to building coastal defense systems. A possible policy response could be to create a "no-build" coastal buffer zone that anticipates a future higher sea level. We present a quantitative model that illustrates the interplay among various important factors (rate of sea level rise, discount rate, capital depreciation rate, attractiveness of coastal land, etc). For some cases, strategies that combine periodic defensive investments (e.g. dikes) with planned retreat can maximize welfare when adapting to rates of climate change. In other cases, planned retreat may be optimal. It is important to prepare for ongoing increasing amounts of climate change. Preparing for a fixed amount of climate change can lead to a suboptimal solution. Climate is likely to continue changing throughout this century and beyond. To reduce adverse climate impacts, ecosystems and human systems will need to continuously adapt to a moving target.

Sample size reassessment for a two-stage design controlling the false discovery rate.

Science.gov (United States)

Zehetmayer, Sonja; Graf, Alexandra C; Posch, Martin

2015-11-01

Sample size calculations for gene expression microarray and NGS-RNA-Seq experiments are challenging because the overall power depends on unknown quantities as the proportion of true null hypotheses and the distribution of the effect sizes under the alternative. We propose a two-stage design with an adaptive interim analysis where these quantities are estimated from the interim data. The second stage sample size is chosen based on these estimates to achieve a specific overall power. The proposed procedure controls the power in all considered scenarios except for very low first stage sample sizes. The false discovery rate (FDR) is controlled despite of the data dependent choice of sample size. The two-stage design can be a useful tool to determine the sample size of high-dimensional studies if in the planning phase there is high uncertainty regarding the expected effect sizes and variability.

Adaptive control of discrete-time chaotic systems: a fuzzy control approach

International Nuclear Information System (INIS)

Feng Gang; Chen Guanrong

2005-01-01

This paper discusses adaptive control of a class of discrete-time chaotic systems from a fuzzy control approach. Using the T-S model of discrete-time chaotic systems, an adaptive control algorithm is developed based on some conventional adaptive control techniques. The resulting adaptively controlled chaotic system is shown to be globally stable, and its robustness is discussed. A simulation example of the chaotic Henon map control is finally presented, to illustrate an application and the performance of the proposed control algorithm

Adaptive piezoelectric sensoriactuators for active structural acoustic control

Science.gov (United States)

Vipperman, Jeffrey Stuart

1997-09-01

piezostructures were used to demonstrate and verify the adaptive piezoelectric sensoriactuator, a cantilevered beam and a simply-supported plate. The experimental open- loop results compare well with theory. A preliminary closed-loop rate controller applied to the cantilevered beam demonstrates simultaneous control and adaptation of the piezoelectric sensoriactuator. Lastly, [/cal H]2 optimal feedback Active Structural Acoustic Control (ASAC) is demonstrated using the adaptive piezoelectric sensoriactuators and the simply- supported plate test bed. A cost function is formulated based upon control effort and predicted radiated acoustic power. Radiation filters are created to predict acoustic power based on the self and mutual radiation efficiencies of the plate modes to be controlled. Both static output feedback and state-feedback compensation as well as dynamic (Linear Quadratic Gaussian) compensation are investigated and compared analytically. The importance of choosing an appropriate spatial aperture for the piezoceramic transducer for static compensation is discussed. Finally, multivariable Active Vibration Control (AVC) and ASAC are implemented experimentally on a simply-supported plate test bed using an array of four Adaptive Piezoelectric Sensoriactuators as the control sensors and actuators. Unfavorable high-frequency response from the given piezoceramic transducers required that dynamic, Linear Quadratic Gaussian (LQG) compensation be used to achieve good control performance.

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations of Adverse Interactions Using a Piloted Aircraft

Science.gov (United States)

Hanson, Curt; Miller, Chris; Wall, John H.; Vanzwieten, Tannen S.; Gilligan, Eric; Orr, Jeb S.

2015-01-01

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority. Two NASA research pilots flew a total of twenty five constant pitch-rate trajectories using a prototype manual steering mode with and without adaptive control.

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

Substance P Differentially Modulates Firing Rate of Solitary Complex (SC) Neurons from Control and Chronic Hypoxia-Adapted Adult Rats

Science.gov (United States)

Nichols, Nicole L.; Powell, Frank L.; Dean, Jay B.; Putnam, Robert W.

2014-01-01

NK1 receptors, which bind substance P, are present in the majority of brainstem regions that contain CO2/H+-sensitive neurons that play a role in central chemosensitivity. However, the effect of substance P on the chemosensitive response of neurons from these regions has not been studied. Hypoxia increases substance P release from peripheral afferents that terminate in the caudal nucleus tractus solitarius (NTS). Here we studied the effect of substance P on the chemosensitive responses of solitary complex (SC: NTS and dorsal motor nucleus) neurons from control and chronic hypoxia-adapted (CHx) adult rats. We simultaneously measured intracellular pH and electrical responses to hypercapnic acidosis in SC neurons from control and CHx adult rats using the blind whole cell patch clamp technique and fluorescence imaging microscopy. Substance P significantly increased the basal firing rate in SC neurons from control and CHx rats, although the increase was smaller in CHx rats. However, substance P did not affect the chemosensitive response of SC neurons from either group of rats. In conclusion, we found that substance P plays a role in modulating the basal firing rate of SC neurons but the magnitude of the effect is smaller for SC neurons from CHx adult rats, implying that NK1 receptors may be down regulated in CHx adult rats. Substance P does not appear to play a role in modulating the firing rate response to hypercapnic acidosis of SC neurons from either control or CHx adult rats. PMID:24516602

An adaptive robust controller for time delay maglev transportation systems

Science.gov (United States)

Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

2012-12-01

For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

Adaptive Augmenting Control and Launch Vehicle Adaptive Control Flight Experiments

Data.gov (United States)

National Aeronautics and Space Administration — Researchers at NASA Armstrong are working to further the development of an adaptive augmenting control algorithm (AAC). The AAC was developed to improve the...

Launch Vehicle Manual Steering with Adaptive Augmenting Control:In-Flight Evaluations of Adverse Interactions Using a Piloted Aircraft

Science.gov (United States)

Hanson, Curt; Miller, Chris; Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Orr, Jeb S.

2015-01-01

An Adaptive Augmenting Control (AAC) algorithm for the Space Launch System (SLS) has been developed at the Marshall Space Flight Center (MSFC) as part of the launch vehicle's baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a potential manual steering mode were also investigated by giving the pilot trajectory deviation cues and pitch rate command authority, which is the subject of this paper. Two NASA research pilots flew a total of 25 constant pitch rate trajectories using a prototype manual steering mode with and without adaptive control, evaluating six different nominal and off-nominal test case scenarios. Pilot comments and PIO ratings were given following each trajectory and correlated with aircraft state data and internal controller signals post-flight.

Anti-hebbian spike-timing-dependent plasticity and adaptive sensory processing.

Science.gov (United States)

Roberts, Patrick D; Leen, Todd K

2010-01-01

Adaptive sensory processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptive sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important novel information needed to improve performance of specific tasks. The mechanism of spike-timing-dependent plasticity (STDP) has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of weakly electric fish. Plasticity in these systems is anti-Hebbian, so that presynaptic inputs that repeatedly precede, and possibly could contribute to, a postsynaptic neuron's firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancelation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

Anti-Hebbian Spike Timing Dependent Plasticity and Adaptive Sensory Processing

Directory of Open Access Journals (Sweden)

Patrick D Roberts

2010-12-01

Full Text Available Adaptive processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptative sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important new information needed to improve performance of specific tasks. The mechanism of spike timing-dependent plasticity (STDP has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of fish. Plasticity in such systems is anti-Hebbian, i.e. presynaptic inputs that repeatedly precede and hence could contribute to a postsynaptic neuron’s firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancellation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

OpenAIRE

Hou, Chuanjing; Hu, Lisheng; Zhang, Yingwei

2015-01-01

An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

Dynamic optimization and adaptive controller design

Science.gov (United States)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations Using a Piloted Aircraft

Science.gov (United States)

Hanson, Curt

2014-01-01

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority.

Adaptive Flight Control Research at NASA

Science.gov (United States)

Motter, Mark A.

2008-01-01

A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

Science.gov (United States)

Herzallah, Randa

2015-03-01

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rail Vehicle Vibrations Control Using Parameters Adaptive PID Controller

Directory of Open Access Journals (Sweden)

Muzaffer Metin

2014-01-01

Full Text Available In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5-DOF quarter-rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.

Adaptive control of a Stewart platform-based manipulator

Science.gov (United States)

Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.

1993-01-01

A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

Linezolid-Dependent Function and Structure Adaptation of Ribosomes in a Staphylococcus epidermidis Strain Exhibiting Linezolid Dependence

Science.gov (United States)

Kokkori, Sofia; Apostolidi, Maria; Tsakris, Athanassios; Pournaras, Spyros

2014-01-01

Linezolid-dependent growth was recently reported in Staphylococcus epidermidis clinical strains carrying mutations associated with linezolid resistance. To investigate this unexpected behavior at the molecular level, we isolated active ribosomes from one of the linezolid-dependent strains and we compared them with ribosomes isolated from a wild-type strain. Both strains were grown in the absence and presence of linezolid. Detailed biochemical and structural analyses revealed essential differences in the function and structure of isolated ribosomes which were assembled in the presence of linezolid. The catalytic activity of peptidyltransferase was found to be significantly higher in the ribosomes derived from the linezolid-dependent strain. Interestingly, the same ribosomes exhibited an abnormal ribosomal subunit dissociation profile on a sucrose gradient in the absence of linezolid, but the profile was restored after treatment of the ribosomes with an excess of the antibiotic. Our study suggests that linezolid most likely modified the ribosomal assembly procedure, leading to a new functional ribosomal population active only in the presence of linezolid. Therefore, the higher growth rate of the partially linezolid-dependent strains could be attributed to the functional and structural adaptations of ribosomes to linezolid. PMID:24890589

Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

Science.gov (United States)

Chen, Syuan-Yi; Gong, Sheng-Sian

2017-09-01

This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

Science.gov (United States)

Xia, Feng; Ma, Longhua; Peng, Chen; Sun, Youxian; Dong, Jinxiang

2008-01-01

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN. PMID:27879934

Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

Directory of Open Access Journals (Sweden)

Jinxiang Dong

2008-07-01

Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.

Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

Science.gov (United States)

Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

2017-03-01

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

Evolutionary rescue and local adaptation under different rates of temperature increase: a combined analysis of changes in phenotype expression and genotype frequency in Paramecium microcosms.

Science.gov (United States)

Killeen, Joshua; Gougat-Barbera, Claire; Krenek, Sascha; Kaltz, Oliver

2017-04-01

Evolutionary rescue (ER) occurs when populations, which have declined due to rapid environmental change, recover through genetic adaptation. The success of this process and the evolutionary trajectory of the population strongly depend on the rate of environmental change. Here we investigated how different rates of temperature increase (from 23 to 32 °C) affect population persistence and evolutionary change in experimental microcosms of the protozoan Paramecium caudatum. Consistent with theory on ER, we found that those populations experiencing the slowest rate of temperature increase were the least likely to become extinct and tended to be the best adapted to the new temperature environment. All high-temperature populations were more tolerant to severe heat stress (35, 37 °C), indicating a common mechanism of heat protection. High-temperature populations also had superior growth rates at optimum temperatures, leading to the absence of a pattern of local adaptation to control (23 °C) and high-temperature (32 °C) environments. However, high-temperature populations had reduced growth at low temperatures (5-9 °C), causing a shift in the temperature niche. In part, the observed evolutionary change can be explained by selection from standing variation. Using mitochondrial markers, we found complete divergence between control and high-temperature populations in the frequencies of six initial founder genotypes. Our results confirm basic predictions of ER and illustrate how adaptation to an extreme local environment can produce positive as well as negative correlated responses to selection over the entire range of the ecological niche. © 2017 John Wiley & Sons Ltd.

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

Directory of Open Access Journals (Sweden)

Chuanjing Hou

2015-01-01

Full Text Available An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

Substance P differentially modulates firing rate of solitary complex (SC neurons from control and chronic hypoxia-adapted adult rats.

Directory of Open Access Journals (Sweden)

Nicole L Nichols

Full Text Available NK1 receptors, which bind substance P, are present in the majority of brainstem regions that contain CO2/H(+-sensitive neurons that play a role in central chemosensitivity. However, the effect of substance P on the chemosensitive response of neurons from these regions has not been studied. Hypoxia increases substance P release from peripheral afferents that terminate in the caudal nucleus tractus solitarius (NTS. Here we studied the effect of substance P on the chemosensitive responses of solitary complex (SC: NTS and dorsal motor nucleus neurons from control and chronic hypoxia-adapted (CHx adult rats. We simultaneously measured intracellular pH and electrical responses to hypercapnic acidosis in SC neurons from control and CHx adult rats using the blind whole cell patch clamp technique and fluorescence imaging microscopy. Substance P significantly increased the basal firing rate in SC neurons from control and CHx rats, although the increase was smaller in CHx rats. However, substance P did not affect the chemosensitive response of SC neurons from either group of rats. In conclusion, we found that substance P plays a role in modulating the basal firing rate of SC neurons but the magnitude of the effect is smaller for SC neurons from CHx adult rats, implying that NK1 receptors may be down regulated in CHx adult rats. Substance P does not appear to play a role in modulating the firing rate response to hypercapnic acidosis of SC neurons from either control or CHx adult rats.

A Rate Adaptation Scheme According to Channel Conditions in Wireless LANs

Science.gov (United States)

Numoto, Daisuke; Inai, Hiroshi

Rate adaptation in wireless LANs is to select the most suitable transmission rate automatically according to channel condition. If the channel condition is good, a station can choose a higher transmission rate, otherwise, it should choose a lower but noise-resistant transmission rate. Since IEEE 802.11 does not specify any rate adaptation scheme, several schemes have been proposed. However those schemes provide low throughput or unfair transmission opportunities among stations especially when the number of stations increases. In this paper, we propose a rate adaptation scheme under which the transmission rate quickly closes and then stays around an optimum rate even in the presence of a large number of stations. Via simulation, our scheme provides higher throughput than existing ones and almost equal fairness.

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

Science.gov (United States)

Volyanskyy, Kostyantyn Y.

maintaining a desired constant level of depth of anesthesia for noncardiac surgery in the face of infusion rate constraints and a drug dosing constraint over a specified period. In addition, the aforementioned control architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework. Finally, a neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.

Flatness-based adaptive fuzzy control of chaotic finance dynamics

Science.gov (United States)

Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

2017-11-01

A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

Adaptive powertrain control for plugin hybrid electric vehicles

Science.gov (United States)

Kedar-Dongarkar, Gurunath; Weslati, Feisel

2013-10-15

A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Transcriptional dynamics with time-dependent reaction rates

Science.gov (United States)

Nandi, Shubhendu; Ghosh, Anandamohan

2015-02-01

Transcription is the first step in the process of gene regulation that controls cell response to varying environmental conditions. Transcription is a stochastic process, involving synthesis and degradation of mRNAs, that can be modeled as a birth-death process. We consider a generic stochastic model, where the fluctuating environment is encoded in the time-dependent reaction rates. We obtain an exact analytical expression for the mRNA probability distribution and are able to analyze the response for arbitrary time-dependent protocols. Our analytical results and stochastic simulations confirm that the transcriptional machinery primarily act as a low-pass filter. We also show that depending on the system parameters, the mRNA levels in a cell population can show synchronous/asynchronous fluctuations and can deviate from Poisson statistics.

Transcriptional dynamics with time-dependent reaction rates

International Nuclear Information System (INIS)

Nandi, Shubhendu; Ghosh, Anandamohan

2015-01-01

Transcription is the first step in the process of gene regulation that controls cell response to varying environmental conditions. Transcription is a stochastic process, involving synthesis and degradation of mRNAs, that can be modeled as a birth–death process. We consider a generic stochastic model, where the fluctuating environment is encoded in the time-dependent reaction rates. We obtain an exact analytical expression for the mRNA probability distribution and are able to analyze the response for arbitrary time-dependent protocols. Our analytical results and stochastic simulations confirm that the transcriptional machinery primarily act as a low-pass filter. We also show that depending on the system parameters, the mRNA levels in a cell population can show synchronous/asynchronous fluctuations and can deviate from Poisson statistics. (paper)

Where you stand depends on where you sit: Qualitative inquiry into notions of fire adaptation

Science.gov (United States)

Brenkert-Smith, Hannah; Meldrum, James; Champ, Patricia A.; Barth, Christopher

2017-01-01

Wildfire and the threat it poses to society represents an example of the complex, dynamic relationship between social and ecological systems. Increasingly, wildfire adaptation is posited as a pathway to shift the approach to fire from a suppression paradigm that seeks to control fire to a paradigm that focuses on “living with” and “adapting to” wildfire. In this study, we seek insights into what it means to adapt to wildfire from a range of stakeholders whose efforts contribute to the management of wildfire. Study participants provided insights into the meaning, relevance, and use of the concept of fire adaptation as it relates to their wildfire-related activities. A key finding of this investigation suggests that social scale is of key importance in the conceptualization and understanding of adaptation for participating stakeholders. Indeed, where you stand in terms of understandings of fire adaptation depends in large part on where you sit.

Flight Test Approach to Adaptive Control Research

Science.gov (United States)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

Directory of Open Access Journals (Sweden)

Poramate eManoonpong

2013-02-01

Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

Shear-Rate-Dependent Behavior of Clayey Bimaterial Interfaces at Landslide Stress Levels

Science.gov (United States)

Scaringi, Gianvito; Hu, Wei; Xu, Qiang; Huang, Runqiu

2018-01-01

The behavior of reactivated and first-failure landslides after large displacements is controlled by the available shear resistance in a shear zone and/or along slip surfaces, such as a soil-bedrock interface. Among the factors influencing the resistance parameter, the dependence on the shear rate can trigger catastrophic evolution (rate-weakening) or exert a slow-down feedback (rate-strengthening) upon stress perturbation. We present ring-shear test results, performed under various normal stresses and shear rates, on clayey soils from a landslide shear zone, on its parent lithology and other lithologies, and on clay-rock interface samples. We find that depending on the materials in contact, the normal stress, and the stress history, the shear-rate-dependent behaviors differ. We discuss possible models and underlying mechanisms for the time-dependent behavior of landslides in clay soils.

Simulation and Rapid Prototyping of Adaptive Control Systems using the Adaptive Blockset for Simulink

DEFF Research Database (Denmark)

Ravn, Ole

1998-01-01

The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller implement...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown.......The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...

Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

Science.gov (United States)

Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

2018-04-01

To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional

Model and experiments to optimize co-adaptation in a simplified myoelectric control system

Science.gov (United States)

Couraud, M.; Cattaert, D.; Paclet, F.; Oudeyer, P. Y.; de Rugy, A.

2018-04-01

Objective. To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. Approach. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. Results. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. Significance. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

Science.gov (United States)

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

Dynamic Self-Adaptive Reliability Control for Electric-Hydraulic Systems

Directory of Open Access Journals (Sweden)

Yi Wan

2015-02-01

Full Text Available The high-speed electric-hydraulic proportional control is a new development of the hydraulic control technique with high reliability, low cost, efficient energy, and easy maintenance; it is widely used in industrial manufacturing and production. However, there are still some unresolved challenges, the most notable being the requirements of high stability and real-time by the classical control algorithm due to its high nonlinear characteristics. We propose a dynamic self-adaptive mixed control method based on the least squares support vector machine (LSSVM and the genetic algorithm for high-speed electric-hydraulic proportional control systems in this paper; LSSVM is used to identify and adjust online a nonlinear electric-hydraulic proportional system, and the genetic algorithm is used to optimize the control law of the controlled system and dynamic self-adaptive internal model control and predictive control are implemented by using the mixed intelligent method. The internal model and the inverse control model are online adjusted together. At the same time, a time-dependent Hankel matrix is constructed based on sample data; thus finite dimensional solution can be optimized on finite dimensional space. The results of simulation experiments show that the dynamic characteristics are greatly improved by the mixed intelligent control strategy, and good tracking and high stability are met in condition of high frequency response.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

Science.gov (United States)

Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

2018-03-01

In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

Driving characteristics and adaptive cruise control : A naturalistic driving study

NARCIS (Netherlands)

Schakel, W.J.; Gorter, C.M.; de Winter, J.C.F.; van Arem, B.

2017-01-01

With the increasing number of vehicles equipped with Adaptive Cruise Control (ACC), it becomes important to assess its impact on traffic flow efficiency, in particular with respect to capacity and queue discharge rate. Simulation studies and surveys suggest that ACC has both positive and negative

Impaired Na⁺-dependent regulation of acetylcholine-activated inward-rectifier K⁺ current modulates action potential rate dependence in patients with chronic atrial fibrillation.

Science.gov (United States)

Voigt, Niels; Heijman, Jordi; Trausch, Anne; Mintert-Jancke, Elisa; Pott, Lutz; Ravens, Ursula; Dobrev, Dobromir

2013-08-01

Shortened action-potential duration (APD) and blunted APD rate adaptation are hallmarks of chronic atrial fibrillation (cAF). Basal and muscarinic (M)-receptor-activated inward-rectifier K(+) currents (IK1 and IK,ACh, respectively) contribute to regulation of human atrial APD and are subject to cAF-dependent remodeling. Intracellular Na(+) ([Na(+)]i) enhances IK,ACh in experimental models but the effect of [Na(+)]i-dependent regulation of inward-rectifier K(+) currents on APD in human atrial myocytes is currently unknown. Here, we report a [Na(+)]i-dependent inhibition of outward IK1 in atrial myocytes from sinus rhythm (SR) or cAF patients. In contrast, IK,ACh activated by carbachol, a non-selective M-receptor agonist, increased with elevation of [Na(+)]i in SR. This [Na(+)]i-dependent IK,ACh regulation was absent in cAF. Including [Na(+)]i dependence of IK1 and IK,ACh in a recent computational model of the human atrial myocyte revealed that [Na(+)]i accumulation at fast rates inhibits IK1 and blunts physiological APD rate dependence in both groups. [Na(+)]i-dependent IK,ACh augmentation at fast rates increased APD rate dependence in SR, but not in cAF. These results identify impaired Na(+)-sensitivity of IK,ACh as one potential mechanism contributing to the blunted APD rate dependence in patients with cAF. This article is part of a Special Issue entitled "Na(+) Regulation in Cardiac Myocytes". Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptation in the fuzzy self-organising controller

DEFF Research Database (Denmark)

Jantzen, Jan; Poulsen, Niels Kjølstad

2003-01-01

This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies...... an update mechanism similar to the SOC update mechanism. Two simulations of proportionally controlled systems show the behaviour of the proportional gain as it adapts to a specified behaviour....

Codon adaptation and synonymous substitution rate in diatom plastid genes.

Science.gov (United States)

Morton, Brian R; Sorhannus, Ulf; Fox, Martin

2002-07-01

Diatom plastid genes are examined with respect to codon adaptation and rates of silent substitution (Ks). It is shown that diatom genes follow the same pattern of codon usage as other plastid genes studied previously. Highly expressed diatom genes display codon adaptation, or a bias toward specific major codons, and these major codons are the same as those in red algae, green algae, and land plants. It is also found that there is a strong correlation between Ks and variation in codon adaptation across diatom genes, providing the first evidence for such a relationship in the algae. It is argued that this finding supports the notion that the correlation arises from selective constraints, not from variation in mutation rate among genes. Finally, the diatom genes are examined with respect to variation in Ks among different synonymous groups. Diatom genes with strong codon adaptation do not show the same variation in synonymous substitution rate among codon groups as the flowering plant psbA gene which, previous studies have shown, has strong codon adaptation but unusually high rates of silent change in certain synonymous groups. The lack of a similar finding in diatoms supports the suggestion that the feature is unique to the flowering plant psbA due to recent relaxations in selective pressure in that lineage.

Robust adaptive control for Unmanned Aerial Vehicles

Science.gov (United States)

Kahveci, Nazli E.

anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

Adaptive super twisting vibration control of a flexible spacecraft with state rate estimation

Science.gov (United States)

Malekzadeh, Maryam; Karimpour, Hossein

2018-05-01

The robust attitude and vibration control of a flexible spacecraft trying to perform accurate maneuvers in spite of various sources of uncertainty is addressed here. Difficulties for achieving precise and stable pointing arise from noisy onboard sensors, parameters indeterminacy, outer disturbances as well as un-modeled or hidden dynamics interactions. Based on high-order sliding-mode methods, the non-minimum phase nature of the problem is dealt with through output redefinition. An adaptive super-twisting algorithm (ASTA) is incorporated with its observer counterpart on the system under consideration to get reliable attitude and vibration control in the presence of sensor noise and momentum coupling. The closed-loop efficiency is verified through simulations under various indeterminate situations and got compared to other methods.

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

Science.gov (United States)

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discrete dislocation plasticity analysis of loading rate-dependent static friction.

Science.gov (United States)

Song, H; Deshpande, V S; Van der Giessen, E

2016-08-01

From a microscopic point of view, the frictional force associated with the relative sliding of rough surfaces originates from deformation of the material in contact, by adhesion in the contact interface or both. We know that plastic deformation at the size scale of micrometres is not only dependent on the size of the contact, but also on the rate of deformation. Moreover, depending on its physical origin, adhesion can also be size and rate dependent, albeit different from plasticity. We present a two-dimensional model that incorporates both discrete dislocation plasticity inside a face-centred cubic crystal and adhesion in the interface to understand the rate dependence of friction caused by micrometre-size asperities. The friction strength is the outcome of the competition between adhesion and discrete dislocation plasticity. As a function of contact size, the friction strength contains two plateaus: at small contact length [Formula: see text], the onset of sliding is fully controlled by adhesion while for large contact length [Formula: see text], the friction strength approaches the size-independent plastic shear yield strength. The transition regime at intermediate contact size is a result of partial de-cohesion and size-dependent dislocation plasticity, and is determined by dislocation properties, interfacial properties as well as by the loading rate.

Performance analysis of joint diversity combining, adaptive modulation, and power control schemes

KAUST Repository

Qaraqe, Khalid A.

2011-01-01

Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, in order to improve the performance and the efficiency of these systems, these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low hardware complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze in this paper three joint adaptive modulation, diversity combining, and power control (JAMDCPC) schemes where a constant-power variable-rate adaptive modulation technique is used with an adaptive diversity combining scheme and a common power control process. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible processing power consumption quantified in terms of the average number of combined paths, given the fading channel conditions and the required bit error rate (BER) performance. In this paper, the performance of these three JAMDCPC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal-to-noise ratio range while maintaining compliance with the BER performance and a low radiated power which yields to a substantial decrease in interference to co-existing users and systems. © 2011 IEEE.

Adaptive Nonsingular Terminal Sliding Model Control and Its Application to Permanent Magnet Synchronous Motor Drive System

OpenAIRE

Liu Yue; Zhou Shuo

2016-01-01

To improve the dynamic performance of permanent magnet synchronous motor(PMSM) drive system, a adaptive nonsingular terminal sliding model control((NTSMC) strategy was proposed. The proposed control strategy presents an adaptive variable-rated exponential reaching law which the L1 norm of state variables is introduced. Exponential and constant approach speed can adaptively adjust according to the state variables’ distance to the equilibrium position.The proposed scheme can shorten the reachin...

Temperature uniformity control in RTP using multivariable adaptive control

Energy Technology Data Exchange (ETDEWEB)

Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.

1995-12-31

In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.

Monitoring the Performance of a Neuro-Adaptive Controller

Science.gov (United States)

Schumann, Johann; Gupta, Pramod

2004-01-01

Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

Adaptive Method Using Controlled Grid Deformation

Directory of Open Access Journals (Sweden)

Florin FRUNZULICA

2011-09-01

Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.

Adaptive LQG controller tuning

Czech Academy of Sciences Publication Activity Database

Novák, Miroslav; Böhm, Josef; Nedoma, Petr; Tesař, Ludvík

2003-01-01

Roč. 150, č. 6 (2003), s. 655-665 ISSN 1350-2379 R&D Projects: GA ČR GA102/02/0204; GA AV ČR IBS1075102 Institutional research plan: CEZ:AV0Z1075907 Keywords : adaptive controller * LQG controller * controller design Subject RIV: JB - Sensors, Measurment, Regulation Impact factor: 0.745, year: 2003

Reference-shaping adaptive control by using gradient descent optimizers.

Directory of Open Access Journals (Sweden)

Baris Baykant Alagoz

Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

A technique for improved stability of adaptive feedforward controllers without detailed uncertainty measurements

International Nuclear Information System (INIS)

Berkhoff, A P

2012-01-01

Model errors in adaptive controllers for the reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous research on active structures with small damping has shown that the addition of a low-authority controller which increases damping in the system may lead to improved performance of an adaptive, high-authority controller. Other researchers have suggested the use of frequency dependent regularization based on measured uncertainties. In this paper an alternative method is presented that avoids the disadvantages of these methods, namely the additional complex hardware and the need to obtain detailed information on the uncertainties. An analysis is made of an adaptive feedforward controller in which a difference exists between the secondary path and the model as used in the controller. The real parts of the eigenvalues that determine the stability of the system are expressed in terms of the amount of uncertainty and the singular values of the secondary path. Modifications of the feedforward control scheme are suggested that aim to improve performance without requiring detailed uncertainty measurements. (paper)

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

Science.gov (United States)

Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

2010-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Adaptive tracking control of nonholonomic systems: an example

NARCIS (Netherlands)

Lefeber, A.A.J.; Nijmeijer, Henk

1999-01-01

We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not

An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

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Peng Jing

2017-08-01

Full Text Available In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate urban traffic congestions to achieve desirable objectives (e.g., delay minimization. Connected vehicle technology, as an emerging technology, is a mobile data platform that enables the real-time data exchange among vehicles and between vehicles and infrastructure. Although several reviews about traffic signal control or connected vehicles have been written, a systemic review of adaptive traffic signal control in a connected vehicle environment has not been made. Twenty-six eligible studies searched from six databases constitute the review. A quality evaluation was established based on previous research instruments and applied to the current review. The purpose of this paper is to critically review the existing methods of adaptive traffic signal control in a connected vehicle environment and to compare the advantages or disadvantages of those methods. Further, a systematic framework on connected vehicle based adaptive traffic signal control is summarized to support the future research. Future research is needed to develop more efficient and generic adaptive traffic signal control methods in a connected vehicle environment.

Adaptive multiparameter control: application to a Rapid Thermal Processing process; Commande Adaptative Multivariable: Application a un Procede de Traitement Thermique Rapide

Energy Technology Data Exchange (ETDEWEB)

Morales Mago, S J

1995-12-20

In this work the problem of temperature uniformity control in rapid thermal processing is addressed by means of multivariable adaptive control. Rapid Thermal Processing (RTP) is a set of techniques proposed for semiconductor fabrication processes such as annealing, oxidation, chemical vapour deposition and others. The product quality depends on two mains issues: precise trajectory following and spatial temperature uniformity. RTP is a fabrication technique that requires a sophisticated real-time multivariable control system to achieve acceptable results. Modelling of the thermal behaviour of the process leads to very complex mathematical models. These are the reasons why adaptive control techniques are chosen. A multivariable linear discrete time model of the highly non-linear process is identified on-line, using an identification scheme which includes supervisory actions. This identified model, combined with a multivariable predictive control law allows to prevent the controller from systems variations. The control laws are obtained by minimization of a quadratic cost function or by pole placement. In some of these control laws, a partial state reference model was included. This reference model allows to incorporate an appropriate tracking capability into the control law. Experimental results of the application of the involved multivariable adaptive control laws on a RTP system are presented. (author) refs

Maritime adaptive optics beam control

OpenAIRE

Corley, Melissa S.

2010-01-01

The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...

An inventory model of instantaneous deteriorating items with controllable deterioration rate for time dependent demand and holding cost

Directory of Open Access Journals (Sweden)

Vinod Kumar Mishra

2013-06-01

Full Text Available Purpose: The purpose of this paper to develop an inventory model for instantaneous deteriorating items with the consideration of the facts that the deterioration rate can be controlled by using the preservation technology (PT and the holding cost & demand rate both are linear function of time which was treated as constant in most of the deteriorating inventory model. Design/methodology/approach: Developed the mathematical equation of deterministic deteriorating inventory model in which demand rate and holding cost both is linear function of time, deterioration rate is constant, backlogging rate is variable and depend on the length of the next replenishment, shortages are allowed and partially backlogged and obtain an analytical solution which optimizes the total cost of the proposed inventory model. Findings: The model can be applied for optimizing the total inventory cost of deteriorating items inventory for such business enterprises where they use the preservation technology to control the deterioration rate under other assumptions of the model. Originality/value: The inventory system for deteriorating items has been an object of study for a long time, but little is known about the effect of investing in reducing the rate of product deterioration and their significant impact in the business. The proposed model is effective as well as efficient for the business organization that uses the preservation technology to reduce the deterioration rate of the instantaneous deteriorating items of the inventory.

Temperature dependence of muonium reaction rates in the gas phase

International Nuclear Information System (INIS)

Fleming, D.G.; Garner, D.M.; Mikula, R.J.; British Columbia Univ., Vancouver

1981-01-01

A study of the temperature dependence of reaction rates has long been an important tool in establishing reaction pathways in chemical reactions. This is particularly true for the reactions of muonium (in comparison with those of hydrogen) since a measurement of the activation energy for chemical reaction is sensitive to both the height and the position of the potential barrier in the reaction plane. For collision controlled reactions, on the other hand, the reaction rate is expected to exhibit a weak T 1 sup(/) 2 dependence characteristic of the mean collision velocity. These concepts are discussed and their effects illustrated in a comparison of the chemical and spin exchange reaction rates of muonium and hydrogen in the temperature range approx.300-approx.500 K. (orig.)

Rate of egg maturation in marine turtles exhibits 'universal temperature dependence'.

Science.gov (United States)

Weber, Sam B; Blount, Jonathan D; Godley, Brendan J; Witt, Matthew J; Broderick, Annette C

2011-09-01

1. The metabolic theory of ecology (MTE) predicts that, after correcting for body mass variation among organisms, the rates of most biological processes will vary as a universal function of temperature. However, empirical support for 'universal temperature dependence' (UTD) is currently equivocal and based on studies of a limited number of traits. 2. In many ectothermic animals, the rate at which females produce mature eggs is temperature dependent and may be an important factor in determining the costs of reproduction. 3. We tested whether the rate of egg maturation in marine turtles varies with environmental temperature as predicted by MTE, using the time separating successive clutches of individual females to estimate the rate at which eggs are formed. We also assessed the phenotypic contribution to this rate, by using radio telemetry to make repeated measurements of interclutch intervals for individual green turtles (Chelonia mydas). 4. Rates of egg maturation increased with seasonally increasing water temperatures in radio-tracked green turtles, but were not repeatable for individual females, and did not vary according to maternal body size or reproductive investment (number and size of eggs produced). 5. Using a collated data set from several different populations and species of marine turtles, we then show that a single relationship with water temperature explains most of the variation in egg maturation rates, with a slope that is statistically indistinguishable from the UTD predicted by MTE. However, several alternative statistical models also described the relationship between temperature and egg maturation rates equally parsimoniously. 6. Our results offer novel support for the MTE's predicted UTD of biological rates, although the underlying mechanisms require further study. The strong temperature dependence of egg maturation combined with the apparently weak phenotypic contribution to this rate has interesting behavioural implications in ectothermic

Comparative study of adaptive controller using MIT rules and Lyapunov method for MPPT standalone PV systems

Science.gov (United States)

Tariba, N.; Bouknadel, A.; Haddou, A.; Ikken, N.; Omari, Hafsa El; Omari, Hamid El

2017-01-01

The Photovoltaic Generator have a nonlinear characteristic function relating the intensity at the voltage I = f (U) and depend on the variation of solar irradiation and temperature, In addition, its point of operation depends directly on the load that it supplies. To fix this drawback, and to extract the maximum power available to the terminal of the generator, an adaptation stage is introduced between the generator and the load to couple the two elements as perfectly as possible. The adaptation stage is associated with a command called MPPT MPPT (Maximum Power Point Tracker) whose is used to force the PVG to operate at the MPP (Maximum Power Point) under variation of climatic conditions and load variation. This paper presents a comparative study between the adaptive controller for PV Systems using MIT rules and Lyapunov method to regulate the PV voltage. The Incremental Conductance (IC) algorithm is used to extract the maximum power from the PVG by calculating the voltage Vref, and the adaptive controller is used to regulate and track quickly the PV voltage. The two methods of the adaptive controller will be compared to prove their performance by using the PSIM tools and experimental test, and the mathematical model of step-up with PVG model will be presented.

High mutation rates limit evolutionary adaptation in Escherichia coli.

Directory of Open Access Journals (Sweden)

Kathleen Sprouffske

2018-04-01

Full Text Available Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli's genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild.

High mutation rates limit evolutionary adaptation in Escherichia coli

Science.gov (United States)

Wagner, Andreas

2018-01-01

Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli’s genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild. PMID:29702649

Projection-Based Adaptive Backstepping Control of a Transport Aircraft for Heavyweight Airdrop

Directory of Open Access Journals (Sweden)

Ri Liu

2015-01-01

Full Text Available An autopilot inner loop that combines backstepping control with adaptive function approximation is developed for airdrop operations. The complex nonlinear uncertainty of the aircraft-cargo model is factorized into a known matrix and an uncertainty function, and a projection-based adaptive approach is proposed to estimate this function. Using projection in the adaptation law bounds the estimated function and guarantees the robustness of the controller against time-varying external disturbances and uncertainties. The convergence properties and robustness of the control method are proved via Lyapunov theory. Simulations are conducted under the condition that one transport aircraft performs a maximum load airdrop task at a height of 82 ft, using single row single platform mode. The results show good performance and robust operation of the controller, and the airdrop mission performance indexes are satisfied, even in the presence of ±15% uncertainty in the aerodynamic coefficients, ±0.01 rad/s pitch rate disturbance, and 20% actuators faults.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Science.gov (United States)

VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

2014-01-01

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a

Facial and Bodily Expressions for Control and Adaptation of Games (ECAG 2008)

NARCIS (Netherlands)

Nijholt, Antinus; Poppe, Ronald Walter; Unknown, [Unknown

2008-01-01

In this workshop of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), the emphasis is on research on facial and bodily expressions for the control and adaptation of games. We distinguish between two forms of expressions, depending on whether the user has the

An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control.

Science.gov (United States)

Neilson, Peter D; Neilson, Megan D

2005-09-01

Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.

A new approach to adaptive control of manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

Cognitive control and conflict adaptation in youth with high-functioning autism.

Science.gov (United States)

Larson, Michael J; South, Mikle; Clayson, Peter E; Clawson, Ann

2012-04-01

  Youth diagnosed with autism spectrum disorders (ASD) often show deficits in cognitive control processes, potentially contributing to characteristic difficulties monitoring and regulating behavior. Modification of performance following conflict can be measured by examining conflict adaptation, the adjustment of cognitive resources based on previous-trial conflict. The electrophysiological correlates of these processes can be measured using the N2, a stimulus-locked component of the event-related potential (ERP).   High-density ERPs and behavioral data [i.e. response times (RTs) and error rates] were acquired while 28 youth with ASD and 36 typically developing controls completed a modified Eriksen flanker task.   Behaviorally, groups showed similar conflict adaptation effects; youth with ASD showed larger RT slowing on switch trials. For electrophysiology, controls demonstrated larger N2 amplitudes for incongruent (high-conflict) trials following congruent (low-conflict) trials than for incongruent trials following incongruent trials. Importantly, youth with ASD showed no such differences in N2 amplitude based on previous-trial conflict.   Lack of electrophysiological conflict adaptation effects in youth with ASD indicates irregular neural processing associated with conflict adaptation. Individuals with ASD show declines in level of conflict evaluation and adaptation. Future research is necessary to accurately characterize and understand the behavioral implications of these cognitive control deficits relative to diagnostic severity, anxiety, and personality. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.

An Adaptive Critic Approach to Reference Model Adaptation

Science.gov (United States)

Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

2003-01-01

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

Study on application of adaptive fuzzy control and neural network in the automatic leveling system

Science.gov (United States)

Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

2015-04-01

This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

Directory of Open Access Journals (Sweden)

Omur Can Ozguney

2017-08-01

Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

Controlling the chaotic discrete-Hénon system using a feedforward neural network with an adaptive learning rate

OpenAIRE

GÖKCE, Kürşad; UYAROĞLU, Yılmaz

2013-01-01

This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.

Early and late rate of force development: differential adaptive responses to resistance training?

DEFF Research Database (Denmark)

Andersen, L L; Andersen, Jesper Løvind; Zebis, M K

2010-01-01

The objective of this study is to investigate the potentially opposing influence of qualitative and quantitative muscular adaptations in response to high-intensity resistance training on contractile rate of force development (RFD) in the early (200 ms) of rising muscle force. Fifteen healthy young......-intensity resistance training due to differential influences of qualitative and quantitative muscular adaptations on early and later phases of rising muscle force....... males participated in a 14-week resistance training intervention for the lower body and 10 matched subjects participated as controls. Maximal muscle strength (MVC) and RFD were measured during maximal voluntary isometric contraction of the quadriceps femoris muscle. Muscle biopsies were obtained from...

Modelling and adaptive control of small capacity chillers for HVAC applications

International Nuclear Information System (INIS)

Beghi, A.; Cecchinato, Luca

2011-01-01

An adaptive controller for single and uneven tandem scroll compressor, packaged air-cooled water chillers is described. The designed controller allows to substantially increase the energy performance of the system, as well as to achieve excellent regulation performances in process applications. The controller parameters are adapted on the basis of estimates of the plant thermal load, that are computed by using a Kalman filter. An ad hoc approach is used to define a relay control logic, which is based on a numerical optimization procedure. To support controller design, a detailed simulation environment is developed and validated on an experimental facility. Performance of the algorithm is described with both simulation and experimental data. At low part load ratio values the proposed algorithm grants a 0.6-0.7 K improvement in the regulation performance in terms of supply water temperature standard deviation and mean supply water temperature deviation. The unit energy efficiency improvement with respect to supply water temperature control varies from 7.3% to 3.0% while the experimental seasonal energy efficiency rating improvement is 9.1%. - Research highlights: → Design of an advanced control algorithms for small capacity chillers. → Matlab/Simulink simulation environment development and experimental validation. → Development of an adaptive control algorithm for scroll compressor chillers, which allows to increase both control accuracy and energy performance. → New load estimation scheme based on a Kalman filter.

Direct adaptive control using feedforward neural networks

OpenAIRE

Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

2003-01-01

ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

Nonlinear PI Control with Adaptive Interaction Algorithm for Multivariable Wastewater Treatment Process

Directory of Open Access Journals (Sweden)

S. I. Samsudin

2014-01-01

Full Text Available The wastewater treatment plant (WWTP is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain kn is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting kn has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.

A Rate-Adaptive MAC Protocol Based on TCP throughput for Ad Hoc Networks in Fading Channels

Directory of Open Access Journals (Sweden)

Shoko Uchida

2008-10-01

Full Text Available Wireless technology is becoming a leading option for future Internet access. Transmission Control Protocol (TCP is one of the protocols designed on the basis of the transmission characteristics in wired networks. It is known that the TCP performance deteriorates drastically under a wireless communication environment. On the other hand, many wireless networking standards such as IEEE 802.11a, 802.11b, and 802.11g have multirate capability. Therefore, adaptive rate control methods have been proposed for ad hoc networks. However, almost methods require the modification of the request to send (RTS and clear to send (CTS packets. Therefore, the conventional methods are not compatible with the standardized system. In this paper, we propose adaptive rate control mechanisms for ad hoc networks. Our mechanisms are based on the RTS/CTS mechanisms. However, no modifications to the RTS and CTS packets are required in the proposed method. Therefore, our proposed method can attempt to satisfy the conventional IEEE 802.11 standards. Moreover, an adequate transmission rate is selected based on an estimated TCP throughput performance. From simulation results, it is observed that the proposed method can improve the throughput performance without any modification of packet structures.

Smooth Adaptive Internal Model Control Based on U Model for Nonlinear Systems with Dynamic Uncertainties

Directory of Open Access Journals (Sweden)

Li Zhao

2016-01-01

Full Text Available An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.

Adaptive neural network controller for the molten steel level control of strip casting processes

International Nuclear Information System (INIS)

Chen, Hung Yi; Huang, Shiuh Jer

2010-01-01

The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller

Adaptive control system having hedge unit and related apparatus and methods

Science.gov (United States)

Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

2007-01-01

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

L1 adaptive control of uncertain gear transmission servo systems with deadzone nonlinearity.

Science.gov (United States)

Zuo, Zongyu; Li, Xiao; Shi, Zhiguang

2015-09-01

This paper deals with the adaptive control problem of Gear Transmission Servo (GTS) systems in the presence of unknown deadzone nonlinearity and viscous friction. A global differential homeomorphism based on a novel differentiable deadzone model is proposed first. Since there exist both matched and unmatched state-dependent unknown nonlinearities, a full-state feedback L1 adaptive controller is constructed to achieve uniformly bounded transient response in addition to steady-state performance. Finally, simulation results are included to show the elimination of limit cycles, in addition to demonstrating the main results in this paper. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

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Jian Liu

Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

Science.gov (United States)

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Adaptive PI Controller for a Nonlinear System

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D. Rathikarani

2009-10-01

Full Text Available Most of the industrial processes are inherently nonlinear in their behaviour. Designs of controllers for these nonlinear processes are difficult, as they do not follow superposition theorem. Adaptive controller can change its behaviour in response to changes in the dynamics of the process and disturbances. Hence adaptive controller can be used to control nonlinear processes. Direct Model Reference Adaptive Control is a technique, in which a reference model involving the desired performances is specified. In the present work, a DMRAC is designed and implemented to achieve satisfactory control of a nonlinear system in all its local linear operating regions. The closed loop system is made BIBO stable by proper control techniques. The controller is designed through simulation in Matlab platform and is validated in real time by conducting experiments on the laboratory Air Flow Control System using the dSPACE interface.

A driver-adaptive stability control strategy for sport utility vehicles

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Zhu, Shenjin; He, Yuping

2017-08-01

Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers' driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to 'drive' the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.

Adaptive control method for core power control in TRIGA Mark II reactor

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Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

2018-01-01

The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

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Wang Chao

2016-03-01

Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

Applications of adaptive filters in active noise control

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Darlington, Paul

The active reduction of acoustic noise is achieved by the addition of a cancelling acoustic signal to the unwanted sound. Successful definition of the cancelling signal amounts to a system identification problem. Recent advances in adaptive signal processing have allowed this problem to be tackled using adaptive filters, which offer significant advantages over conventional solutions. The extension of adaptive noise cancelling techniques, which were developed in the electrical signal conditioning context, to the control of acoustic systems is studied. An analysis is presented of the behavior of the Widrow-Hoff LMS adaptive noise canceller with a linear filter in its control loop. The active control of plane waves propagating axially in a hardwalled duct is used as a motivating model problem. The model problem also motivates the study of the effects of feedback around an LMS adaptive filter. An alternative stochastic gradient algorithm for controlling adaptive filters in the presence of feedback is presented.

Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

Directory of Open Access Journals (Sweden)

Guoliang Zhao

2013-01-01

Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

Speed control of permanent magnet excitation transverse flux linear motor by using adaptive neuro-fuzzy controller

Energy Technology Data Exchange (ETDEWEB)

Hasanien, Hany M., E-mail: Hanyhasanien@ieee.or [Dept. of Elec. Power and Machines, Faculty of Eng., Ain-shams Univ. Cairo (Egypt); Muyeen, S.M. [Department of Electrical Engineering, Petroleum Institute, Abu Dhabi (United Arab Emirates); Tamura, Junji [Department of EEE, Kitami Institute of Technology, 165 Koen Cho, Kitami 090-8507, Hokkaido (Japan)

2010-12-15

This paper presents a novel adaptive neuro-fuzzy controller applies on transverse flux linear motor for controlling its speed. The proposed controller presents fuzzy logic controller with self tuning scaling factors based on artificial neural network structure. It has two input variables and one control output variable. Firstly the fuzzy logic control rules are described then NN architecture is represented to self tune the output scaling factors of the controller. The application of this control technique represents the novelty of work, where this algorithm has so far not been stated before for this type of drives. This methodology solves the problem of nonlinearities and load changes of TFLM drives. The dynamic response of the motor is studied under the rated load condition as well as load disturbances. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. The dynamic response of the motor with the proposed controller is compared with PI and adaptive NN controllers. It is found that the proposed controller gives better and faster response from the viewpoint of overshoot and settling time. Matlab/Simulink tool is used for this dynamic simulation study.

Cell Size and Growth Rate Are Modulated by TORC2-Dependent Signals.

Science.gov (United States)

Lucena, Rafael; Alcaide-Gavilán, Maria; Schubert, Katherine; He, Maybo; Domnauer, Matthew G; Marquer, Catherine; Klose, Christian; Surma, Michal A; Kellogg, Douglas R

2018-01-22

The size of all cells, from bacteria to vertebrates, is proportional to the growth rate set by nutrient availability, but the underlying mechanisms are unknown. Here, we show that nutrients modulate cell size and growth rate via the TORC2 signaling network in budding yeast. An important function of the TORC2 network is to modulate synthesis of ceramide lipids, which play roles in signaling. TORC2-dependent control of ceramide signaling strongly influences both cell size and growth rate. Thus, cells that cannot make ceramides fail to modulate their growth rate or size in response to changes in nutrients. PP2A associated with the Rts1 regulatory subunit (PP2A Rts1 ) is embedded in a feedback loop that controls TORC2 signaling and helps set the level of TORC2 signaling to match nutrient availability. Together, the data suggest a model in which growth rate and cell size are mechanistically linked by ceramide-dependent signals arising from the TORC2 network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive control using neural networks and approximate models.

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Narendra, K S; Mukhopadhyay, S

1997-01-01

The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

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Frost, Susan A.; Balas, Mark J.

2011-01-01

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

Attaining the rate-independent limit of a rate-dependent strain gradient plasticity theory

DEFF Research Database (Denmark)

El-Naaman, Salim Abdallah; Nielsen, Kim Lau; Niordson, Christian Frithiof

2016-01-01

The existence of characteristic strain rates in rate-dependent material models, corresponding to rate-independent model behavior, is studied within a back stress based rate-dependent higher order strain gradient crystal plasticity model. Such characteristic rates have recently been observed...... for steady-state processes, and the present study aims to demonstrate that the observations in fact unearth a more widespread phenomenon. In this work, two newly proposed back stress formulations are adopted to account for the strain gradient effects in the single slip simple shear case, and characteristic...... rates for a selected quantity are identified through numerical analysis. Evidently, the concept of a characteristic rate, within the rate-dependent material models, may help unlock an otherwise inaccessible parameter space....

Adaptive change in corporate control practices.

Science.gov (United States)

Alexander, J A

1991-03-01

Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

DEFF Research Database (Denmark)

Andersen, T.O.; Hansen, M.R.; Conrad, Finn

2004-01-01

control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...

Adaptive neural network motion control for aircraft under uncertainty conditions

Science.gov (United States)

Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

2018-02-01

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Feedback control and adaptive control of the energy resource chaotic system

International Nuclear Information System (INIS)

Sun Mei; Tian Lixin; Jiang Shumin; Xu Jun

2007-01-01

In this paper, the problem of control for the energy resource chaotic system is considered. Two different method of control, feedback control (include linear feedback control, non-autonomous feedback control) and adaptive control methods are used to suppress chaos to unstable equilibrium or unstable periodic orbits. The Routh-Hurwitz criteria and Lyapunov direct method are used to study the conditions of the asymptotic stability of the steady states of the controlled system. The designed adaptive controller is robust with respect to certain class of disturbances in the energy resource chaotic system. Numerical simulations are presented to show these results

A novel adaptive force control method for IPMC manipulation

International Nuclear Information System (INIS)

Hao, Lina; Sun, Zhiyong; Su, Yunquan; Gao, Jianchao; Li, Zhi

2012-01-01

IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable. (paper)

Adaptive twisting sliding mode algorithm for hypersonic reentry vehicle attitude control based on finite-time observer.

Science.gov (United States)

Guo, Zongyi; Chang, Jing; Guo, Jianguo; Zhou, Jun

2018-06-01

This paper focuses on the adaptive twisting sliding mode control for the Hypersonic Reentry Vehicles (HRVs) attitude tracking issue. The HRV attitude tracking model is transformed into the error dynamics in matched structure, whereas an unmeasurable state is redefined by lumping the existing unmatched disturbance with the angular rate. Hence, an adaptive finite-time observer is used to estimate the unknown state. Then, an adaptive twisting algorithm is proposed for systems subject to disturbances with unknown bounds. The stability of the proposed observer-based adaptive twisting approach is guaranteed, and the case of noisy measurement is analyzed. Also, the developed control law avoids the aggressive chattering phenomenon of the existing adaptive twisting approaches because the adaptive gains decrease close to the disturbance once the trajectories reach the sliding surface. Finally, numerical simulations on the attitude control of the HRV are conducted to verify the effectiveness and benefit of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.

Science.gov (United States)

Savran, Aydogan; Kahraman, Gokalp

2014-03-01

We develop a novel adaptive tuning method for classical proportional-integral-derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input-output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities. © 2013 Published by ISA on behalf of ISA.

Adaptive Control Of Remote Manipulator

Science.gov (United States)

Seraji, Homayoun

1989-01-01

Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

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Muhammad Iqbal

2018-02-01

Full Text Available This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided.

Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

Science.gov (United States)

Iqbal, Muhammad; Rehan, Muhammad; Hong, Keum-Shik

2018-01-01

This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN) neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided. PMID:29535622

Adaptive modification of the delayed feedback control algorithm with a continuously varying time delay

International Nuclear Information System (INIS)

Pyragas, V.; Pyragas, K.

2011-01-01

We propose a simple adaptive delayed feedback control algorithm for stabilization of unstable periodic orbits with unknown periods. The state dependent time delay is varied continuously towards the period of controlled orbit according to a gradient-descent method realized through three simple ordinary differential equations. We demonstrate the efficiency of the algorithm with the Roessler and Mackey-Glass chaotic systems. The stability of the controlled orbits is proven by computation of the Lyapunov exponents of linearized equations. -- Highlights: → A simple adaptive modification of the delayed feedback control algorithm is proposed. → It enables the control of unstable periodic orbits with unknown periods. → The delay time is varied continuously according to a gradient descend method. → The algorithm is embodied by three simple ordinary differential equations. → The validity of the algorithm is proven by computation of the Lyapunov exponents.

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

Science.gov (United States)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus

2014-01-01

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia

Science.gov (United States)

Yang, Yuxiao; Shanechi, Maryam M.

2016-12-01

Objective. Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. Approach. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. Main results. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. Significance. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost

Control of District Heating System with Flow-dependent Delays

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Ledesma, Jorge Val; Kallesøe, Carsten Skovmose

2017-01-01

All flow systems are subject to transport delays, which are governed by the flow rates in the system. When the flow rates themselves are control inputs, the system becomes subject to input-dependent state delays, which poses significant theoretical problems. In an earlier paper, we proposed...

Algebraic and adaptive learning in neural control systems

Science.gov (United States)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

Robust and Adaptive Control With Aerospace Applications

CERN Document Server

Lavretsky, Eugene

2013-01-01

Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems.  The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: ·         case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; ·         detailed background material for each chapter to motivate theoretical developments; ·         realistic examples and simulation data illustrating key features ...

Estimating the effect of a rare time-dependent treatment on the recurrent event rate.

Science.gov (United States)

Smith, Abigail R; Zhu, Danting; Goodrich, Nathan P; Merion, Robert M; Schaubel, Douglas E

2018-05-30

In many observational studies, the objective is to estimate the effect of treatment or state-change on the recurrent event rate. If treatment is assigned after the start of follow-up, traditional methods (eg, adjustment for baseline-only covariates or fully conditional adjustment for time-dependent covariates) may give biased results. We propose a two-stage modeling approach using the method of sequential stratification to accurately estimate the effect of a time-dependent treatment on the recurrent event rate. At the first stage, we estimate the pretreatment recurrent event trajectory using a proportional rates model censored at the time of treatment. Prognostic scores are estimated from the linear predictor of this model and used to match treated patients to as yet untreated controls based on prognostic score at the time of treatment for the index patient. The final model is stratified on matched sets and compares the posttreatment recurrent event rate to the recurrent event rate of the matched controls. We demonstrate through simulation that bias due to dependent censoring is negligible, provided the treatment frequency is low, and we investigate a threshold at which correction for dependent censoring is needed. The method is applied to liver transplant (LT), where we estimate the effect of development of post-LT End Stage Renal Disease (ESRD) on rate of days hospitalized. Copyright © 2018 John Wiley & Sons, Ltd.

Adaptive Piezoelectric Absorber for Active Vibration Control

Directory of Open Access Journals (Sweden)

Sven Herold

2016-02-01

Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.

Neural networks based identification and compensation of rate-dependent hysteresis in piezoelectric actuators

International Nuclear Information System (INIS)

Zhang, Xinliang; Tan, Yonghong; Su, Miyong; Xie, Yangqiu

2010-01-01

This paper presents a method of the identification for the rate-dependent hysteresis in the piezoelectric actuator (PEA) by use of neural networks. In this method, a special hysteretic operator is constructed from the Prandtl-Ishlinskii (PI) model to extract the changing tendency of the static hysteresis. Then, an expanded input space is constructed by introducing the proposed hysteretic operator to transform the multi-valued mapping of the hysteresis into a one-to-one mapping. Thus, a feedforward neural network is applied to the approximation of the rate-independent hysteresis on the constructed expanded input space. Moreover, in order to describe the rate-dependent performance of the hysteresis, a special hybrid model, which is constructed by a linear auto-regressive exogenous input (ARX) sub-model preceded with the previously obtained neural network based rate-independent hysteresis sub-model, is proposed. For the compensation of the effect of the hysteresis in PEA, the PID feedback controller with a feedforward hysteresis compensator is developed for the tracking control of the PEA. Thus, a corresponding inverse model based on the proposed modeling method is developed for the feedforward hysteresis compensator. Finally, both simulations and experimental results on piezoelectric actuator are presented to verify the effectiveness of the proposed approach for the rate-dependent hysteresis.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Adaptive Convergence Rates of a Dirichlet Process Mixture of Multivariate Normals

OpenAIRE

Tokdar, Surya T.

2011-01-01

It is shown that a simple Dirichlet process mixture of multivariate normals offers Bayesian density estimation with adaptive posterior convergence rates. Toward this, a novel sieve for non-parametric mixture densities is explored, and its rate adaptability to various smoothness classes of densities in arbitrary dimension is demonstrated. This sieve construction is expected to offer a substantial technical advancement in studying Bayesian non-parametric mixture models based on stick-breaking p...

Improved adaptive input voltage control of a solar array interfacing current mode controlled boost power stage

International Nuclear Information System (INIS)

Sitbon, Moshe; Schacham, Shmuel; Suntio, Teuvo; Kuperman, Alon

2015-01-01

Highlights: • Photovoltaic generator dynamic resistance online estimation method is proposed. • Control method allowing to achieve nominal performance at all time is presented. • The method is suitable for any type of photovoltaic system. - Abstract: Nonlinear characteristics of photovoltaic generators were recently shown to significantly influence the dynamics of interfacing power stages. Moreover, since the dynamic resistance of photovoltaic generators is both operating point and environmental variables dependent, the combined dynamics exhibits these dependencies as well, burdening control challenge. Typically, linear time invariant input voltage loop controllers (e.g. Proportional-Integrative-Derivative) are utilized in photovoltaic applications, designed according to nominal operating conditions. Nevertheless, since actual dynamics is seldom nominal, closed loop performance of such systems varies as well. In this paper, adaptive control method is proposed, allowing to estimate photovoltaic generator resistance online and utilize it to modify the controller parameters such that closed loop performance remains nominal throughout the whole operation range. Unlike previously proposed method, utilizing double-grid-frequency component for estimation purposes and suffering from various drawbacks such as operation point dependence and applicability to single-phase grid connected systems only, the proposed method is based on harmonic current injection and is independent on operating point and system topology

LMI-based adaptive reliable H∞ static output feedback control against switched actuator failures

Science.gov (United States)

An, Liwei; Zhai, Ding; Dong, Jiuxiang; Zhang, Qingling

2017-08-01

This paper investigates the H∞ static output feedback (SOF) control problem for switched linear system under arbitrary switching, where the actuator failure models are considered to depend on switching signal. An active reliable control scheme is developed by combination of linear matrix inequality (LMI) method and adaptive mechanism. First, by exploiting variable substitution and Finsler's lemma, new LMI conditions are given for designing the SOF controller. Compared to the existing results, the proposed design conditions are more relaxed and can be applied to a wider class of no-fault linear systems. Then a novel adaptive mechanism is established, where the inverses of switched failure scaling factors are estimated online to accommodate the effects of actuator failure on systems. Two main difficulties arise: first is how to design the switched adaptive laws to prevent the missing of estimating information due to switching; second is how to construct a common Lyapunov function based on a switched estimate error term. It is shown that the new method can give less conservative results than that for the traditional control design with fixed gain matrices. Finally, simulation results on the HiMAT aircraft are given to show the effectiveness of the proposed approaches.

Adaptive Sliding Mode Control for Hydraulic Drives

DEFF Research Database (Denmark)

Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

2013-01-01

This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...... employing parameter adaption through a recursive algorithm is presented. This is based on a reduced order model approximation of a VCD with unmatched valve flow- and cylinder asymmetries. Bounds on parameters are obtained despite lack of parameter knowledge, and the proposed controller demonstrates improved...

Projection Operator: A Step Towards Certification of Adaptive Controllers

Science.gov (United States)

Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

Programming adaptive control to evolve increased metabolite production.

Science.gov (United States)

Chou, Howard H; Keasling, Jay D

2013-01-01

The complexity inherent in biological systems challenges efforts to rationally engineer novel phenotypes, especially those not amenable to high-throughput screens and selections. In nature, increased mutation rates generate diversity in a population that can lead to the evolution of new phenotypes. Here we construct an adaptive control system that increases the mutation rate in order to generate diversity in the population, and decreases the mutation rate as the concentration of a target metabolite increases. This system is called feedback-regulated evolution of phenotype (FREP), and is implemented with a sensor to gauge the concentration of a metabolite and an actuator to alter the mutation rate. To evolve certain novel traits that have no known natural sensors, we develop a framework to assemble synthetic transcription factors using metabolic enzymes and construct four different sensors that recognize isopentenyl diphosphate in bacteria and yeast. We verify FREP by evolving increased tyrosine and isoprenoid production.

[Dose rate-dependent cellular and molecular effects of ionizing radiation].

Science.gov (United States)

Przybyszewski, Waldemar M; Wideł, Maria; Szurko, Agnieszka; Maniakowski, Zbigniew

2008-09-11

The aim of radiation therapy is to kill tumor cells while minimizing damage to normal cells. The ultimate effect of radiation can be apoptotic or necrotic cell death as well as cytogenetic damage resulting in genetic instability and/or cell death. The destructive effects of radiation arise from direct and indirect ionization events leading to peroxidation of macromolecules, especially those present in lipid-rich membrane structures as well as chromatin lipids. Lipid peroxidative end-products may damage DNA and proteins. A characteristic feature of radiation-induced peroxidation is an inverse dose-rate effect (IDRE), defined as an increase in the degree of oxidation(at constant absorbed dose) accompanying a lower dose rate. On the other hand, a low dose rate can lead to the accumulation of cells in G2, the radiosensitive phase of the cell cycle since cell cycle control points are not sensitive to low dose rates. Radiation dose rate may potentially be the main factor improving radiotherapy efficacy as well as affecting the intensity of normal tissue and whole-body side effects. A better understanding of dose rate-dependent biological effects may lead to improved therapeutic intervention and limit normal tissue reaction. The study reviews basic biological effects that depend on the dose rate of ionizing radiation.

Adaptive Controller Design for Continuous Stirred Tank Reactor

OpenAIRE

K. Prabhu; V. Murali Bhaskaran

2014-01-01

Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...

An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

OpenAIRE

Peng Jing; Hao Huang; Long Chen

2017-01-01

In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate u...

From dysfunction to adaptation: an interactionist model of dependency.

Science.gov (United States)

Bornstein, Robert F

2012-01-01

Contrary to clinical lore, a dependent personality style is associated with active as well as passive behavior and may be adaptive in certain contexts (e.g., in fostering compliance with medical and psychotherapeutic treatment regimens). The cognitive/interactionist model conceptualizes dependency-related responding in terms of four components: (a) motivational (a marked need for guidance, support, and approval from others); (b) cognitive (a perception of oneself as powerless and ineffectual); (c) affective (a tendency to become anxious when required to function autonomously); and (d) behavioral (use of diverse self-presentation strategies to strengthen ties to potential caregivers). Clinicians' understanding of the etiology and dynamics of dependency has improved substantially in recent years; current challenges include delineating useful subtypes of dependency, developing valid symptom criteria for Dependent Personality Disorder in DSM-5 and beyond, and working effectively with dependent patients in the age of managed care.

Adaptive neuro-fuzzy controller of switched reluctance motor

Directory of Open Access Journals (Sweden)

Tahour Ahmed

2007-01-01

Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.

Adaptive control of bifurcation and chaos in a time-delayed system

International Nuclear Information System (INIS)

Li Ning; Zhang Qing-Ling; Yuan Hui-Qun; Sun Hai-Yi

2013-01-01

In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. A comparison of the two adaptive control methods is also made in an experimental study

Adaptive Nonsingular Terminal Sliding Model Control and Its Application to Permanent Magnet Synchronous Motor Drive System

Directory of Open Access Journals (Sweden)

Liu Yue

2016-01-01

Full Text Available To improve the dynamic performance of permanent magnet synchronous motor(PMSM drive system, a adaptive nonsingular terminal sliding model control((NTSMC strategy was proposed. The proposed control strategy presents an adaptive variable-rated exponential reaching law which the L1 norm of state variables is introduced. Exponential and constant approach speed can adaptively adjust according to the state variables’ distance to the equilibrium position.The proposed scheme can shorten the reaching time and weaken system chatting. The method was applied to the PMSM speed servo system, and compared with the traditional terminal-sliding-mode regulator and PI regulator. Simulation results show that the proposed control strategy can improve dynamic, steady performance and robustness.

Convexity, gauge-dependence and tunneling rates

Energy Technology Data Exchange (ETDEWEB)

Plascencia, Alexis D.; Tamarit, Carlos [Institute for Particle Physics Phenomenology, Durham University,South Road, DH1 3LE (United Kingdom)

2016-10-19

We clarify issues of convexity, gauge-dependence and radiative corrections in relation to tunneling rates. Despite the gauge dependence of the effective action at zero and finite temperature, it is shown that tunneling and nucleation rates remain independent of the choice of gauge-fixing. Taking as a starting point the functional that defines the transition amplitude from a false vacuum onto itself, it is shown that decay rates are exactly determined by a non-convex, false vacuum effective action evaluated at an extremum. The latter can be viewed as a generalized bounce configuration, and gauge-independence follows from the appropriate Nielsen identities. This holds for any election of gauge-fixing that leads to an invertible Faddeev-Popov matrix.

Convexity, gauge-dependence and tunneling rates

International Nuclear Information System (INIS)

Plascencia, Alexis D.; Tamarit, Carlos

2016-01-01

We clarify issues of convexity, gauge-dependence and radiative corrections in relation to tunneling rates. Despite the gauge dependence of the effective action at zero and finite temperature, it is shown that tunneling and nucleation rates remain independent of the choice of gauge-fixing. Taking as a starting point the functional that defines the transition amplitude from a false vacuum onto itself, it is shown that decay rates are exactly determined by a non-convex, false vacuum effective action evaluated at an extremum. The latter can be viewed as a generalized bounce configuration, and gauge-independence follows from the appropriate Nielsen identities. This holds for any election of gauge-fixing that leads to an invertible Faddeev-Popov matrix.

Controlling chaos based on an adaptive adjustment mechanism

International Nuclear Information System (INIS)

Zheng Yongai

2006-01-01

In this paper, we extend the ideas and techniques developed by Huang [Huang W. Stabilizing nonlinear dynamical systems by an adaptive adjustment mechanism. Phys Rev E 2000;61:R1012-5] for controlling discrete-time chaotic system using adaptive adjustment mechanism to continuous-time chaotic system. Two control approaches, namely adaptive adjustment mechanism (AAM) and modified adaptive adjustment mechanism (MAAM), are investigated. In both case sufficient conditions for the stabilization of chaotic systems are given analytically. The simulation results on Chen chaotic system have verified the effectiveness of the proposed techniques

Full Gradient Solution to Adaptive Hybrid Control

Science.gov (United States)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2017-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Adaptive fuzzy PID control for a quadrotor stabilisation

Science.gov (United States)

Cherrat, N.; Boubertakh, H.; Arioui, H.

2018-02-01

This paper deals with the design of an adaptive fuzzy PID control law for attitude and altitude stabilization of a quadrotor despite the system model uncertainties and disturbances. To this end, a PID control with adaptive gains is used in order to approximate a virtual ideal control previously designed to achieve the predefined objective. Specifically, the control gains are estimated and adjusted by mean of a fuzzy system whose parameters are adjusted online via a gradient descent-based adaptation law. The analysis of the closed-loop system is given by the Lyapunov approach. The simulation results are presented to illustrate the efficiency of the proposed approach.

Connection adaption for control of networked mobile chaotic agents.

Science.gov (United States)

Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S

2017-11-22

In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.

Adaptive learning fuzzy control of a mobile robot

International Nuclear Information System (INIS)

Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

1989-11-01

In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

Adaptive mechanism-based congestion control for networked systems

Science.gov (United States)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Model-Free Adaptive Control Algorithm with Data Dropout Compensation

Directory of Open Access Journals (Sweden)

Xuhui Bu

2012-01-01

Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

Science.gov (United States)

Rajasekaran, Vijaykumar; López-Larraz, Eduardo; Trincado-Alonso, Fernando; Aranda, Joan; Montesano, Luis; Del-Ama, Antonio J; Pons, Jose L

2018-01-03

Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI). A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation. The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the

ADEX optimized adaptive controllers and systems from research to industrial practice

CERN Document Server

Martín-Sánchez, Juan M

2015-01-01

This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

All-Coefficient Adaptive Control of Dual-Motor Driving Servo System

Directory of Open Access Journals (Sweden)

Zhao Haibo

2017-01-01

Full Text Available Backlash nonlinearity and friction nonlinearity exist in dual-motor driving servo system, which reducing system response speed, steady accuracy and anti-interference ability. In order to diminish the adverse effects of backlash and friction nonlinearity to system, we proposed a new all-coefficient adaptive control method. Firstly, we introduced the dynamic model of backlash and friction nonlinearity respectively. Then on this basis, we established the characteristic model when backlash and friction nonlinearity coexist. We used recursive least square method for parameter estimation. Finally we designed the all-coefficient adaptive controller. On the basis of simplex all-coefficient adaptive controller, we designed a feedforward all-coefficient adaptive controller. The simulations of feedforward all-coefficient adaptive control and simplex all-coefficient adaptive control were compared. The results show that the former has quicker response speed, higher steady accuracy, stronger anti-interference performance and better robustness, which validating the efficacy of the proposed control strategy.

Robust Adaptive Speed Control of Induction Motor Drives

DEFF Research Database (Denmark)

Bidstrup, N.

, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

Adaptive Control Methods for Soft Robots

Data.gov (United States)

National Aeronautics and Space Administration — I propose to develop methods for soft and inflatable robots that will allow the control system to adapt and change control parameters based on changing conditions...

Disturbance Accommodating Adaptive Control with Application to Wind Turbines

Science.gov (United States)

Frost, Susan

2012-01-01

Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.

Transmission History Based Distributed Adaptive Contention Window Adjustment Algorithm Cooperating with Automatic Rate Fallback for Wireless LANs

Science.gov (United States)

Ogawa, Masakatsu; Hiraguri, Takefumi; Nishimori, Kentaro; Takaya, Kazuhiro; Murakawa, Kazuo

This paper proposes and investigates a distributed adaptive contention window adjustment algorithm based on the transmission history for wireless LANs called the transmission-history-based distributed adaptive contention window adjustment (THAW) algorithm. The objective of this paper is to reduce the transmission delay and improve the channel throughput compared to conventional algorithms. The feature of THAW is that it adaptively adjusts the initial contention window (CWinit) size in the binary exponential backoff (BEB) algorithm used in the IEEE 802.11 standard according to the transmission history and the automatic rate fallback (ARF) algorithm, which is the most basic algorithm in automatic rate controls. This effect is to keep CWinit at a high value in a congested state. Simulation results show that the THAW algorithm outperforms the conventional algorithms in terms of the channel throughput and delay, even if the timer in the ARF is changed.

Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

2016-01-01

Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

Adaptive Backstepping Flight Control for Modern Fighter Aircraft

NARCIS (Netherlands)

Sonneveldt, L.

2010-01-01

The main goal of this thesis is to investigate the potential of the nonlinear adaptive backstepping control technique in combination with online model identification for the design of a reconfigurable flight control system for a modern fighter aircraft. Adaptive backstepping is a recursive,

Design and implementation of adaptive inverse control algorithm for a micro-hand control system

Directory of Open Access Journals (Sweden)

Wan-Cheng Wang

2014-01-01

Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.

Adaptive landing gear concept—feedback control validation

Science.gov (United States)

Mikulowski, Grzegorz M.; Holnicki-Szulc, Jan

2007-12-01

The objective of this paper is to present an integrated feedback control concept for adaptive landing gears (ALG) and its experimental validation. Aeroplanes are subjected to high dynamic loads as a result of the impact during each landing. Classical landing gears, which are in common use, are designed in accordance with official regulations in a way that ensures the optimal energy dissipation for the critical (maximum) sink speed. The regulations were formulated in order to ensure the functional capability of the landing gears during an emergency landing. However, the landing gears, whose characteristics are optimized for these critical conditions, do not perform well under normal impact conditions. For that situation it is reasonable to introduce a system that would adapt the characteristics of the landing gears according to the sink speed of landing. The considered system assumes adaptation of the damping force generated by the landing gear, which would perform optimally in an emergency situation and would adapt itself for regular landings as well. This research covers the formulation and design of the control algorithms for an adaptive landing gear based on MR fluid, implementation of the algorithms on an FPGA platform and experimental verification on a lab-scale landing gear device. The main challenge of the research was to develop a control methodology that could operate effectively within 50 ms, which is assumed to be the total duration of the phenomenon. The control algorithm proposed in this research was able to control the energy dissipation process on the experimental stand.

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

Science.gov (United States)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Control of multi-machine using adaptive fuzzy

Directory of Open Access Journals (Sweden)

Bouchiba Bousmaha

2011-01-01

Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.

Adaptive control of manipulators handling hazardous waste

International Nuclear Information System (INIS)

Colbaugh, R.; Glass, K.

1994-01-01

This article focuses on developing a robot control system capable of meeting hazardous waste handling application requirements, and presents as a solution an adaptive strategy for controlling the mechanical impedance of kinematically redundant manipulators. The proposed controller is capable of accurate end-effector impedance control and effective redundancy utilization, does not require knowledge of the complex robot dynamic model or parameter values for the robot or the environment, and is implemented without calculation of the robot inverse transformation. Computer simulation results are given for a four degree of freedom redundant robot under adaptive impedance control. These results indicate that the proposed controller is capable of successfully performing important tasks in robotic waste handling applications. (author) 3 figs., 39 refs

Neural and Fuzzy Adaptive Control of Induction Motor Drives

International Nuclear Information System (INIS)

Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

2008-01-01

This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

Tuning of gravity-dependent and gravity-independent vertical angular VOR gain changes by frequency of adaptation.

Science.gov (United States)

Yakushin, Sergei B

2012-06-01

The gain of the vertical angular vestibulo-ocular reflex (aVOR) was adaptively increased and decreased in a side-down head orientation for 4 h in two cynomolgus monkeys. Adaptation was performed at 0.25, 1, 2, or 4 Hz. The gravity-dependent and -independent gain changes were determined over a range of head orientations from left-side-down to right-side-down at frequencies from 0.25 to 10 Hz, before and after adaptation. Gain changes vs. frequency data were fit with a Gaussian to determine the frequency at which the peak gain change occurred, as well as the tuning width. The frequency at which the peak gravity-dependent gain change occurred was approximately equal to the frequency of adaptation, and the width increased monotonically with increases in the frequency of adaptation. The gravity-independent component was tuned to the adaptive frequency of 0.25 Hz but was uniformly distributed over all frequencies when the adaptation frequency was 1-4 Hz. The amplitude of the gravity-independent gain changes was larger after the aVOR gain decrease than after the gain increase across all tested frequencies. For the aVOR gain decrease, the phase lagged about 4° for frequencies below the adaptation frequency and led for frequencies above the adaptation frequency. For gain increases, the phase relationship as a function of frequency was inverted. This study demonstrates that the previously described dependence of aVOR gain adaptation on frequency is a property of the gravity-dependent component of the aVOR only. The gravity-independent component of the aVOR had a substantial tuning curve only at an adaptation frequency of 0.25 Hz.

Adaptive robust control of the EBR-II reactor

International Nuclear Information System (INIS)

Power, M.A.; Edwards, R.M.

1996-01-01

Simulation results are presented for an adaptive H ∞ controller, a fixed H ∞ controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H ∞ controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H ∞ and classical controllers. This makes for a superior and more robust controller

Epistasis increases the rate of conditionally neutral substitution in an adapting population.

Science.gov (United States)

Draghi, Jeremy A; Parsons, Todd L; Plotkin, Joshua B

2011-04-01

Kimura observed that the rate of neutral substitution should equal the neutral mutation rate. This classic result is central to our understanding of molecular evolution, and it continues to influence phylogenetics, genomics, and the interpretation of evolution experiments. By demonstrating that neutral mutations substitute at a rate independent of population size and selection at linked sites, Kimura provided an influential justification for the idea of a molecular clock and emphasized the importance of genetic drift in shaping molecular evolution. But when epistasis among sites is common, as numerous empirical studies suggest, do neutral mutations substitute according to Kimura's expectation? Here we study simulated, asexual populations of RNA molecules, and we observe that conditionally neutral mutations--i.e., mutations that do not alter the fitness of the individual in which they arise, but that may alter the fitness effects of subsequent mutations--substitute much more often than expected while a population is adapting. We quantify these effects using a simple population-genetic model that elucidates how the substitution rate at conditionally neutral sites depends on the population size, mutation rate, strength of selection, and prevalence of epistasis. We discuss the implications of these results for our understanding of the molecular clock, and for the interpretation of molecular variation in laboratory and natural populations.

Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES

International Nuclear Information System (INIS)

Muyeen, S.M.; Hasanien, Hany M.; Al-Durra, Ahmed

2014-01-01

Highlights: • We present an ANN-controlled SMES in this paper. • The objective is to enhance transient stability of WF connected to power system. • The control strategy depends on a PWM VSC and DC–DC converter. • The effectiveness of proposed controller is compared with PI controller. • The validity of the proposed system is verified by simulation results. - Abstract: This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) system to enhance the transient stability of wind farms connected to a multi-machine power system during network disturbances. The control strategy of SMES depends mainly on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and an adaptive ANN-controlled DC–DC converter using insulated gate bipolar transistors (IGBTs). The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of proportional-integral (PI)-controlled SMES optimized by response surface methodology and genetic algorithm (RSM–GA) considering both of symmetrical and unsymmetrical faults. For realistic responses, real wind speed data and two-mass drive train model of wind turbine generator system is considered in the analyses. The validity of the proposed system is verified by the simulation results which are performed using the laboratory standard dynamic power system simulator PSCAD/EMTDC. Notably, the proposed adaptive ANN-controlled SMES enhances the transient stability of wind farms connected to a multi-machine power system

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

Science.gov (United States)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Adaptive control of a PWR core power using neural networks

International Nuclear Information System (INIS)

Arab-Alibeik, H.; Setayeshi, S.

2005-01-01

Reactor power control is important because of safety concerns and the call for regular and appropriate operation of nuclear power plants. It seems that the load-follow operation of these plants will be unavoidable in the future. Discrepancies between the real plant and the model used in controller design for load-follow operation encourage one to use auto-tuning and (or) adaptive techniques. Neural network technology shows great promise for addressing many problems in non-model-based adaptive control methods. Also, there has been a great attention to inverse control especially in the neural and fuzzy control context. Fortunately, online adaptation eliminates some limitations of inverse control and its shortcomings for real world applications. We use a neural adaptive inverse controller to control the power of a PWR reactor. The stability of the system and convergence of the controller parameters are guaranteed during online adaptation phase provided the controller is near the plant's real inverse after offline training period. The performance of the controller is verified using nonlinear simulations in diverse operating conditions

An Adaptive Speed Control Approach for DC Shunt Motors

Directory of Open Access Journals (Sweden)

Ruben Tapia-Olvera

2016-11-01

Full Text Available A B-spline neural networks-based adaptive control technique for angular speed reference trajectory tracking tasks with highly efficient performance for direct current shunt motors is proposed. A methodology for adaptive control and its proper training procedure are introduced. This algorithm sets the control signal without using a detailed mathematical model nor exact values of the parameters of the nonlinear dynamic system. The proposed robust adaptive tracking control scheme only requires measurements of the velocity output signal. Thus, real-time measurements or estimations of acceleration, current and disturbance signals are avoided. Experimental results confirm the efficient and robust performance of the proposed control approach for highly demanding motor operation conditions exposed to variable-speed reference trajectories and completely unknown load torque. Hence, laboratory experimental tests on a direct current shunt motor prove the viability of the proposed adaptive output feedback trajectory tracking control approach.

Adaptive Critic Nonlinear Robust Control: A Survey.

Science.gov (United States)

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Fault diagnosis and fault-tolerant control based on adaptive control approach

CERN Document Server

Shen, Qikun; Shi, Peng

2017-01-01

This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .

Antifouling composites with self-adaptive controlled release based on an active compound intercalated into layered double hydroxides

Science.gov (United States)

Yang, Miaosen; Gu, Lianghua; Yang, Bin; Wang, Li; Sun, Zhiyong; Zheng, Jiyong; Zhang, Jinwei; Hou, Jian; Lin, Cunguo

2017-12-01

This paper reports a novel method to prepare the antifouling composites with properties of self-adaptive controlled release (defined as control the release rate autonomously and adaptively according to the change of environmental conditions) by intercalation of sodium paeonolsilate (PAS) into MgAl and ZnAl layered double hydroxide (LDH) with the molar ratio (M2+/M3+) of 2:1 and 3:1, respectively. The powder X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) confirm the intercalation of PAS into the galleries of LDH. The controlled release behavior triggered by temperature for the PAS-LDH composites has been investigated, and the results show that the release rate of all PAS-LDH composites increases as the increase of temperature. However, the MgAl-PAS-LDH composites (Mg2Al-PAS-LDH and Mg3Al-PAS-LDH) exhibit the increased release rate of 0.21 ppm/°C from 15 to 30 °C in 3.5% NaCl solution, more than three times of the ZnAl-PAS-LDH composites (0.06 ppm/°C), owing to the confined microenvironment influenced by metal types in LDH layers. In addition, a possible diffusion-controlled process with surface diffusion, bulk diffusion and heterogeneous flat surface diffusion has been revealed via fitting four kinetic equations. Moreover, to verify the practical application of the PAS-LDH composites, a model coating denoted as Mg2Al-PAS-LDH coating was fabricated. The release result displays that the release rate increases or decreases as temperature altered at 15 and 25 °C alternately, indicating its self-adaptive controlled release behavior with temperature. Moreover, the superior resistance to the settlement of Ulva spores at 15 and 25 °C was observed for the Mg2Al-PAS-LDH coating, as a result of the controllable release of antifoulant. Therefore, this work provides a facile and effective method for the fabrication of antifouling composites with self-adaptive controlled release behavior in response to temperature, which can be used to prolong

Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses

Science.gov (United States)

Patel, Gauravkumar K.; Hahne, Janne M.; Castellini, Claudio; Farina, Dario; Dosen, Strahinja

2017-10-01

Objective. Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. Approach. We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control. Further, a realistic evaluation of the cxMYO was performed online in able-bodied subjects using three functional tasks, during which the cxMYO was compared to a purely machine-learning-based myoelectric control (MYO). Main results. The results demonstrated that utilizing context information decreased the number of unwanted commands, improving the performance (success rate and dropped objects) in all three functional tasks. Specifically, the median number of objects dropped per round with cxMYO was zero in all three tasks and a significant increase in the number of successful transfers was seen in two out of three functional tasks. Additionally, the subjects reported better user experience. Significance. This is the first online evaluation of a method integrating information from multiple on-board prosthesis sensors to modulate the output of a machine-learning-based myoelectric controller. The proposed scheme is general and presents a simple, non-invasive and cost-effective approach for improving the robustness of myoelectric control.

Bayesian nonparametric adaptive control using Gaussian processes.

Science.gov (United States)

Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

2015-03-01

Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

Directory of Open Access Journals (Sweden)

Wenjie Lou

2016-02-01

Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

Design of adaptive switching control for hypersonic aircraft

Directory of Open Access Journals (Sweden)

Xin Jiao

2015-10-01

Full Text Available This article proposes a novel adaptive switching control of hypersonic aircraft based on type-2 Takagi–Sugeno–Kang fuzzy sliding mode control and focuses on the problem of stability and smoothness in the switching process. This method uses full-state feedback to linearize the nonlinear model of hypersonic aircraft. Combining the interval type-2 Takagi–Sugeno–Kang fuzzy approach with sliding mode control keeps the adaptive switching process stable and smooth. For rapid stabilization of the system, the adaptive laws use a direct constructive Lyapunov analysis together with an established type-2 Takagi–Sugeno–Kang fuzzy logic system. Simulation results indicate that the proposed control scheme can maintain the stability and smoothness of switching process for the hypersonic aircraft.

An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

Directory of Open Access Journals (Sweden)

Shun-Yuan Wang

2015-03-01

Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

Dependent interest and transition rates in life insurance

DEFF Research Database (Denmark)

Buchardt, Kristian

2014-01-01

For market consistent life insurance liabilities modelled with a multi-state Markov chain, it is of importance to consider the interest and transition rates as stochastic processes, for example in order to consider hedging possibilities of the risks, and for risk measurement. In the literature......, this is usually done with an assumption of independence between the interest and transition rates. In this paper, it is shown how to valuate life insurance liabilities using affine processes for modelling dependent interest and transition rates. This approach leads to the introduction of so-called dependent...... forward rates. We propose a specific model for surrender modelling, and within this model the dependent forward rates are calculated, and the market value and the Solvency II capital requirement are examined for a simple savings contract....

Exponential cluster synchronization in directed community networks via adaptive nonperiodically intermittent pinning control

Science.gov (United States)

Zhou, Peipei; Cai, Shuiming; Jiang, Shengqin; Liu, Zengrong

2018-02-01

In this paper, the problem of exponential cluster synchronization for a class of directed community networks is investigated via adaptive nonperiodically intermittent pinning control. By constructing a novel piecewise continuous Lyapunov function, some sufficient conditions to guarantee globally exponential cluster synchronization are derived. It is noted that the derived cluster synchronization criteria rely on the control rates, but not the control widths or the control periods, which facilitates the choice of the control periods in practical applications. A numerical example is finally presented to show the effectiveness of the obtained theoretical results.

Polymer degradation rate control of hybrid rocket combustion

Science.gov (United States)

Stickler, D. B.; Ramohalli, K. N. R.

1970-01-01

Polymer degradation to small fragments is treated as a rate controlling step in hybrid rocket combustion. Both numerical and approximate analytical solutions of the complete energy and polymer chain bond conservation equations for the condensed phase are obtained. Comparison with inert atmosphere data is very good. It is found that the intersect of curves of pyrolysis rate versus interface temperature for hybrid combustors, with the thermal degradation theory, falls at a pyrolysis rate very close to that for which a pressure dependence begins to be observable. Since simple thermal degradation cannot give sufficient depolymerization at higher pyrolysis rates, it is suggested that oxidative catalysis of the process occurs at the surface, giving a first order dependence on reactive species concentration at the wall. Estimates of the ratio of this activation energy and interface temperature are in agreement with best fit procedures for hybrid combustion data. Requisite active species concentrations and flux are shown to be compatible with turbulent transport. Pressure dependence of hybrid rocket fuel regression rate is thus shown to be describable in a consistent manner in terms of reactive species catalysis of polymer degradation.

Channel allocation and rate adaptation for relayed transmission over correlated fading channels

KAUST Repository

Hwang, Kyusung

2009-09-01

We consider, in this paper, channel allocation and rate adaptation scheme for relayed transmission over correlated fading channels via cross-layer design. Specifically, jointly considering the data link layer buffer occupancy and channel quality at both the source and relay nodes, we develop an optimal channel allocation and rate adaptation policy for a dual-hop relayed transmission. As such the overall transmit power for the relayed system is minimized while a target packet dropping rate (PDR) due to buffer over flows is guaranteed. In order to find such an optimal policy, the channel allocation and rate adaptation transmission framework is formulated as a constraint Markov decision process (CMDP). The PDR performance of the optimal policy is compared with that of two conventional suboptimal schemes, namely the channel quality based and the buffer occupancy based channel allocation schemes. Numerical results show that for a given power budget, the optimal scheme requires significantly less power than the conventional schemes in order to maintain a target PDR. ©2009 IEEE.

Novel strategies in feedforward adaptation to a position-dependent perturbation.

Science.gov (United States)

Hinder, Mark R; Milner, Theodore E

2005-08-01

To investigate the control mechanisms used in adapting to position-dependent forces, subjects performed 150 horizontal reaching movements over 25 cm in the presence of a position-dependent parabolic force field (PF). The PF acted only over the first 10 cm of the movement. On every fifth trial, a virtual mechanical guide (double wall) constrained subjects to move along a straight-line path between the start and target positions. Its purpose was to register lateral force to track formation of an internal model of the force field, and to look for evidence of possible alternative adaptive strategies. The force field produced a force to the right, which initially caused subjects to deviate in that direction. They reacted by producing deviations to the left, "into" the force field, as early as the second trial. Further adaptation resulted in rapid exponential reduction of kinematic error in the latter portion of the movement, where the greatest perturbation to the handpath was initially observed, whereas there was little modification of the handpath in the region where the PF was active. Significant force directed to counteract the PF was measured on the first guided trial, and was modified during the first half of the learning set. The total force impulse in the region of the PF increased throughout the learning trials, but it always remained less than that produced by the PF. The force profile did not resemble a mirror image of the PF in that it tended to be more trapezoidal than parabolic in shape. As in previous studies of force-field adaptation, we found that changes in muscle activation involved a general increase in the activity of all muscles, which increased arm stiffness, and selectively-greater increases in the activation of muscles which counteracted the PF. With training, activation was exponentially reduced, albeit more slowly than kinematic error. Progressive changes in kinematics and EMG occurred predominantly in the region of the workspace beyond the

Time-Dependent Behaviors of Granite: Loading-Rate Dependence, Creep, and Relaxation

Science.gov (United States)

Hashiba, K.; Fukui, K.

2016-07-01

To assess the long-term stability of underground structures, it is important to understand the time-dependent behaviors of rocks, such as their loading-rate dependence, creep, and relaxation. However, there have been fewer studies on crystalline rocks than on tuff, mudstone, and rock salt, because the high strength of crystalline rocks makes the detection of their time-dependent behaviors much more difficult. Moreover, studies on the relaxation, temporal change of stress and strain (TCSS) conditions, and relations between various time-dependent behaviors are scarce for not only granites, but also other rocks. In this study, previous reports on the time-dependent behaviors of granites were reviewed and various laboratory tests were conducted using Toki granite. These tests included an alternating-loading-rate test, creep test, relaxation test, and TCSS test. The results showed that the degree of time dependence of Toki granite is similar to other granites, and that the TCSS resembles the stress-relaxation curve and creep-strain curve. A viscoelastic constitutive model, proposed in a previous study, was modified to investigate the relations between the time-dependent behaviors in the pre- and post-peak regions. The modified model reproduced the stress-strain curve, creep, relaxation, and the results of the TCSS test. Based on a comparison of the results of the laboratory tests and numerical simulations, close relations between the time-dependent behaviors were revealed quantitatively.

Adaptive control of biomass and substrate concentration in a continuous-flow. Fermentation process

Energy Technology Data Exchange (ETDEWEB)

Chamilothoris, G; Sevely, Y; Sevely, Y

1988-01-01

This paper presents a simple adaptive control scheme for the simultaneous regulation of biomass and substrate concentration in a continuous fermentation process. The proposed algorithm includes the on-line estimation of a time-varying parameter (namely the specific growth rate) and two cascaded regulators of self-tuning inspiration. Convergence of the control algorithm, in the BIBO sense, is theoretically established and its effectiveness is illustrated by simulation examples.

Preliminary Test of Adaptive Neuro-Fuzzy Inference System Controller for Spacecraft Attitude Control

Directory of Open Access Journals (Sweden)

Sung-Woo Kim

2012-12-01

Full Text Available The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS. An ANFIS produces a control signal for one of the three axes of a spacecraft’s body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

Parallel efficient rate control methods for JPEG 2000

Science.gov (United States)

Martínez-del-Amor, Miguel Á.; Bruns, Volker; Sparenberg, Heiko

2017-09-01

Since the introduction of JPEG 2000, several rate control methods have been proposed. Among them, post-compression rate-distortion optimization (PCRD-Opt) is the most widely used, and the one recommended by the standard. The approach followed by this method is to first compress the entire image split in code blocks, and subsequently, optimally truncate the set of generated bit streams according to the maximum target bit rate constraint. The literature proposes various strategies on how to estimate ahead of time where a block will get truncated in order to stop the execution prematurely and save time. However, none of them have been defined bearing in mind a parallel implementation. Today, multi-core and many-core architectures are becoming popular for JPEG 2000 codecs implementations. Therefore, in this paper, we analyze how some techniques for efficient rate control can be deployed in GPUs. In order to do that, the design of our GPU-based codec is extended, allowing stopping the process at a given point. This extension also harnesses a higher level of parallelism on the GPU, leading to up to 40% of speedup with 4K test material on a Titan X. In a second step, three selected rate control methods are adapted and implemented in our parallel encoder. A comparison is then carried out, and used to select the best candidate to be deployed in a GPU encoder, which gave an extra 40% of speedup in those situations where it was really employed.

Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

Science.gov (United States)

Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

2018-01-01

The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

Adaptive Backstepping Self-balancing Control of a Two-wheel Electric Scooter

Directory of Open Access Journals (Sweden)

Nguyen Ngoc Son

2014-10-01

Full Text Available This paper introduces an adaptive backstepping control law for a two-wheel electric scooter (eScooter with a nonlinear uncertain model. Adaptive backstepping control is integrated with feedback control that satisfies Lyapunov stability. By using the recursive structure to find the controlled function and estimate uncertain parameters, an adaptive backstepping method allows us to build a feedback control law that efficiently controls a self-balancing controller of the eScooter. Additionally, a controller area network (CAN bus with high reliability is applied for communicating between the modules of the eScooter. Simulation and experimental results demonstrate the robustness and good performance of the proposed adaptive backstepping control.

Adaptive feedforward in the LANL rf control system

International Nuclear Information System (INIS)

Ziomek, C.D.

1992-01-01

This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

Exercise, Insulin Absorption Rates, and Artificial Pancreas Control

Science.gov (United States)

Frank, Spencer; Hinshaw, Ling; Basu, Rita; Basu, Ananda; Szeri, Andrew J.

2016-11-01

Type 1 Diabetes is characterized by an inability of a person to endogenously produce the hormone insulin. Because of this, insulin must be injected - usually subcutaneously. The size of the injected dose and the rate at which the dose reaches the circulatory system have a profound effect on the ability to control glucose excursions, and therefore control of diabetes. However, insulin absorption rates via subcutaneous injection are variable and depend on a number of factors including tissue perfusion, physical activity (vasodilation, increased capillary throughput), and other tissue geometric and physical properties. Exercise may also have a sizeable effect on the rate of insulin absorption, which can potentially lead to dangerous glucose levels. Insulin-dosing algorithms, as implemented in an artificial pancreas controller, should account accurately for absorption rate variability and exercise effects on insulin absorption. The aforementioned factors affecting insulin absorption will be discussed within the context of both fluid mechanics and data driven modeling approaches.

Exercise training improves heart rate variability after methamphetamine dependency.

Science.gov (United States)

Dolezal, Brett Andrew; Chudzynski, Joy; Dickerson, Daniel; Mooney, Larissa; Rawson, Richard A; Garfinkel, Alan; Cooper, Christopher B

2014-06-01

Heart rate variability (HRV) reflects a healthy autonomic nervous system and is increased with physical training. Methamphetamine dependence (MD) causes autonomic dysfunction and diminished HRV. We compared recently abstinent methamphetamine-dependent participants with age-matched, drug-free controls (DF) and also investigated whether HRV can be improved with exercise training in the methamphetamine-dependent participants. In 50 participants (MD = 28; DF = 22), resting heart rate (HR; R-R intervals) was recorded over 5 min while seated using a monitor affixed to a chest strap. Previously reported time domain (SDNN, RMSSD, pNN50) and frequency domain (LFnu, HFnu, LF/HF) parameters of HRV were calculated with customized software. MD were randomized to thrice-weekly exercise training (ME = 14) or equal attention without training (MC = 14) over 8 wk. Groups were compared using paired and unpaired t-tests. Statistical significance was set at P ≤ 0.05. Participant characteristics were matched between groups (mean ± SD): age = 33 ± 6 yr; body mass = 82.7 ± 12 kg, body mass index = 26.8 ± 4.1 kg·min. Compared with DF, the MD group had significantly higher resting HR (P HRV indices were similar between ME and MC groups. However, after training, the ME group significantly (all P HRV, based on several conventional indices, was diminished in recently abstinent, methamphetamine-dependent individuals. Moreover, physical training yielded a marked increase in HRV, representing increased vagal modulation or improved autonomic balance.

Adaptive nonlinear control using input normalized neural networks

International Nuclear Information System (INIS)

Leeghim, Henzeh; Seo, In Ho; Bang, Hyo Choong

2008-01-01

An adaptive feedback linearization technique combined with the neural network is addressed to control uncertain nonlinear systems. The neural network-based adaptive control theory has been widely studied. However, the stability analysis of the closed-loop system with the neural network is rather complicated and difficult to understand, and sometimes unnecessary assumptions are involved. As a result, unnecessary assumptions for stability analysis are avoided by using the neural network with input normalization technique. The ultimate boundedness of the tracking error is simply proved by the Lyapunov stability theory. A new simple update law as an adaptive nonlinear control is derived by the simplification of the input normalized neural network assuming the variation of the uncertain term is sufficiently small

Adaptive slope compensation for high bandwidth digital current mode controller

DEFF Research Database (Denmark)

Taeed, Fazel; Nymand, Morten

2015-01-01

An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations...... in converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter...

Adaptive fuzzy controller based MPPT for photovoltaic systems

International Nuclear Information System (INIS)

Guenounou, Ouahib; Dahhou, Boutaib; Chabour, Ferhat

2014-01-01

Highlights: • We propose a fuzzy controller with adaptive output scaling factor as a maximum power point tracker of photovoltaic system. • The proposed controller integrates two different rule bases defined on error and change of error. • Our controller can track the maximum power point with better performances when compared to its conventional counterpart. - Abstract: This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart

An adaptation method to improve secret key rates of time-frequency QKD in atmospheric turbulence channels

Science.gov (United States)

Sun, Xiaole; Djordjevic, Ivan B.; Neifeld, Mark A.

2016-03-01

Free-space optical (FSO) channels can be characterized by random power fluctuations due to atmospheric turbulence, which is known as scintillation. Weak coherent source based FSO quantum key distribution (QKD) systems suffer from the scintillation effect because during the deep channel fading the expected detection rate drops, which then gives an eavesdropper opportunity to get additional information about protocol by performing photon number splitting (PNS) attack and blocking single-photon pulses without changing QBER. To overcome this problem, in this paper, we study a large-alphabet QKD protocol, which is achieved by using pulse-position modulation (PPM)-like approach that utilizes the time-frequency uncertainty relation of the weak coherent photon state, called here TF-PPM-QKD protocol. We first complete finite size analysis for TF-PPM-QKD protocol to give practical bounds against non-negligible statistical fluctuation due to finite resources in practical implementations. The impact of scintillation under strong atmospheric turbulence regime is studied then. To overcome the secure key rate performance degradation of TF-PPM-QKD caused by scintillation, we propose an adaptation method for compensating the scintillation impact. By changing source intensity according to the channel state information (CSI), obtained by classical channel, the adaptation method improves the performance of QKD system with respect to the secret key rate. The CSI of a time-varying channel can be predicted using stochastic models, such as autoregressive (AR) models. Based on the channel state predictions, we change the source intensity to the optimal value to achieve a higher secret key rate. We demonstrate that the improvement of the adaptation method is dependent on the prediction accuracy.

Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure

Directory of Open Access Journals (Sweden)

Ashraf Ahmed Fahmy

2014-03-01

Full Text Available This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation.  Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.

Development of adaptive control applied to chaotic systems

Science.gov (United States)

Rhode, Martin Andreas

1997-12-01

Continuous-time derivative control and adaptive map-based recursive feedback control techniques are used to control chaos in a variety of systems and in situations that are of practical interest. The theoretical part of the research includes the review of fundamental concept of control theory in the context of its applications to deterministic chaotic systems, the development of a new adaptive algorithm to identify the linear system properties necessary for control, and the extension of the recursive proportional feedback control technique, RPF, to high dimensional systems. Chaos control was applied to models of a thermal pulsed combustor, electro-chemical dissolution and the hyperchaotic Rossler system. Important implications for combustion engineering were suggested by successful control of the model of the thermal pulsed combustor. The system was automatically tracked while maintaining control into regions of parameter and state space where no stable attractors exist. In a simulation of the electrochemical dissolution system, application of derivative control to stabilize a steady state, and adaptive RPF to stabilize a period one orbit, was demonstrated. The high dimensional adaptive control algorithm was applied in a simulation using the Rossler hyperchaotic system, where a period-two orbit with two unstable directions was stabilized and tracked over a wide range of a system parameter. In the experimental part, the electrochemical system was studied in parameter space, by scanning the applied potential and the frequency of the rotating copper disk. The automated control algorithm is demonstrated to be effective when applied to stabilize a period-one orbit in the experiment. We show the necessity of small random perturbations applied to the system in order to both learn the dynamics and control the system at the same time. The simultaneous learning and control capability is shown to be an important part of the active feedback control.

Assessment of Adaptive Rate Response Provided by Accelerometer, Minute Ventilation and Dual Sensor Compared with Normal Sinus Rhythm During Exercise: A Self-controlled Study in Chronotropically Competent Subjects

Directory of Open Access Journals (Sweden)

Yuanyuan Cao

2015-01-01

Full Text Available Background: Dual sensor (DS for rate adaption was supposed to be more physiological. To evaluate its superiority, the DS (accelerometer [ACC] and minute ventilation [MV] and normal sinus rate response were compared in a self-controlled way during exercise treadmill testing. Methods: This self-controlled study was performed in atrioventricular block patients with normal sinus function who met the indications of pacemaker implant. Twenty-one patients came to the 1-month follow-up visit. Patients performed a treadmill test 1-month post implant while programmed in DDDR and sensor passive mode. For these patients, sensor response factors were left at default settings (ACC = 8, MV = 3 and sensor indicated rates (SIRs for DS, ACC and MV sensor were retrieved from the pacemaker memories, along with measured sinus node (SN rates from the beginning to 1-minute after the end of the treadmill test, and compared among study groups. Repeated measures analysis of variance and profile analysis, as well as variance analysis of randomized block designs, were used for statistical analysis. Results: Fifteen patients (15/21 were determined to be chronotropically competent. The mean differences between DS SIRs and intrinsic sinus rates during treadmill testing were smaller than those for ACC and MV sensor (mean difference between SIR and SN rate: ACC vs. SN, MV vs. SN, DS vs. SN, respectively, 34.84, 17.60, 16.15 beats/min, though no sensors could mimic sinus rates under the default settings for sensor response factor (ACC vs. SN P-adjusted < 0.001; MV vs. SN P-adjusted = 0.002; DS vs. SN P-adjusted = 0.005. However, both in the range of 1 st minute and first 3 minutes of exercise, only the DS SIR profile did not differ from sinus rates (P-adjusted = 0.09, 0.90, respectively. Conclusions: The DS under default settings provides more physiological rate response during physical activity than the corresponding single sensors (ACC or MV sensor. Further study is needed to

Experimental comparison of rate-dependent hysteresis models in characterizing and compensating hysteresis of piezoelectric tube actuators

Energy Technology Data Exchange (ETDEWEB)

Aljanaideh, Omar, E-mail: omaryanni@gmail.com [Department of Mechanical Engineering, The University of Jordan, Amman 11942 (Jordan); Habineza, Didace; Rakotondrabe, Micky [AS2M department, FEMTO-ST Institute, Univ. Bourgogne Franche-Comté, Univ. de Franche-Comté/CNRS/ENSMM, 25000 Besançon (France); Al Janaideh, Mohammad [Department of Mechanical and Industrial Engineering, The Mechatronics and Microsystems Design Laboratory, University of Toronto (Canada); Department of Mechatronics Engineering, The University of Jordan, Amman 11942 (Jordan)

2016-04-01

An experimental study has been carried out to characterize rate-dependent hysteresis of a piezoelectric tube actuator at different excitation frequencies. The experimental measurements were followed by modeling and compensation of the hysteresis nonlinearities of the piezoelectric tube actuator using both the inverse rate-dependent Prandtl–Ishlinskii model (RDPI) and inverse rate-independent Prandtl–Ishlinskii model (RIPI) coupled with a controller. The comparison of hysteresis modeling and compensation of the actuator with both models is presented.

Experimental comparison of rate-dependent hysteresis models in characterizing and compensating hysteresis of piezoelectric tube actuators

International Nuclear Information System (INIS)

Aljanaideh, Omar; Habineza, Didace; Rakotondrabe, Micky; Al Janaideh, Mohammad

2016-01-01

An experimental study has been carried out to characterize rate-dependent hysteresis of a piezoelectric tube actuator at different excitation frequencies. The experimental measurements were followed by modeling and compensation of the hysteresis nonlinearities of the piezoelectric tube actuator using both the inverse rate-dependent Prandtl–Ishlinskii model (RDPI) and inverse rate-independent Prandtl–Ishlinskii model (RIPI) coupled with a controller. The comparison of hysteresis modeling and compensation of the actuator with both models is presented.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer

2015-07-23

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer; Hong-Chuan Yang; Gebali, Fayez; Alouini, Mohamed-Slim

2015-01-01

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

Design of L1 -Adaptive Controller for Single Axis Positioning Table

Directory of Open Access Journals (Sweden)

Amjad Jalil Humaidi

2017-11-01

Full Text Available L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC. The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance

Adaptive traffic control systems for urban networks

Directory of Open Access Journals (Sweden)

Radivojević Danilo

2017-01-01

Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

Directory of Open Access Journals (Sweden)

Peng Song

2012-01-01

Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

Modeling adaptive and non-adaptive responses to environmental change

DEFF Research Database (Denmark)

Coulson, Tim; Kendall, Bruce E; Barthold, Julia A.

2017-01-01

, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we...... construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive....... Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full...

Application of adaptive fuzzy control technology to pressure control of a pressurizer

Institute of Scientific and Technical Information of China (English)

YANG Ben-kun; BIAN Xin-qian; GUO Wei-lai

2005-01-01

A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor,therefor,the study of pressurizer's pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a pressurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.

Control uncertain Genesio-Tesi chaotic system: Adaptive sliding mode approach

International Nuclear Information System (INIS)

Dadras, Sara; Momeni, Hamid Reza

2009-01-01

An adaptive sliding mode control (ASMC) technique is introduced in this paper for a chaotic dynamical system (Genesio-Tesi system). Using the sliding mode control technique, a sliding surface is determined and the control law is established. An adaptive sliding mode control law is derived to make the states of the Genesio-Tesi system asymptotically track and regulate the desired state. The designed control scheme can control the uncertain chaotic behaviors to a desired state without oscillating very fast and guarantee the property of asymptotical stability. An illustrative simulation result is given to demonstrate the effectiveness of the proposed adaptive sliding mode control design.

Dependence module of the MINI plus adapted for sugar dependence: psychometric properties Módulo de dependência do MINI plus adaptado para dependência de açúcar: propriedades psicométricas

Directory of Open Access Journals (Sweden)

Marco Aurélio Camargo da Rosa

2013-01-01

Full Text Available This study aimed to analyze the factorial structure and the scale of measurement of the items for dependence of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV adapted for sugar consumption in order to verify if the structural characteristics can be applied to sugar dependence. The questionnaire was applied to a sample of 500 subjects in Brazil (67% female; mean age: 38 y.o.; 43% from weight control clinics; 63% with normal BMI. An exploratory factor analysis was performed to determine the factorial structure and unidimensionality; and, a Rasch model analysis, to verify unidimensionality and items distribution. The model with best fit is unidimensional. All items had good fit to the Rasch model with a reliability of .99, infit between .86 and 1.14 and outfit from .71 to 1.20. The items of MINI Plus adapted for sugar dependence presented good psychometric properties, suggesting that the dependence criteria of DSM-IV support the verification of the construct for sugar addiction.Analisar a estrutura fatorial e a escala de medida dos critérios de dependência do DSM-IV adaptado para açúcar a fim de verificar se as características estruturais são aplicaveis para dependência de açúcar. O questionário foi aplicado numa amostra de 500 pessoas (67% mulheres; média idade: 38 anos; 43% de clínicas obesidade; 63% IMC normal. A análise fatorial exploratória determinou a estrutura fatorial e unidimensionalidade; a análise de Rasch, a unidimensionalidade e distribuição dos itens. O modelo com melhor ajuste era unidimensional. Todos os itens apresentaram ajustes adequados na análise de Rasch com confiabilidade de 0,99, infit entre 0,86 a 1,14 e outfit entre 0,71 e 1,20. Os itens de dependência do MINI Plus adaptados para açúcar apresentaram boas propriedades psicométricas, sugerindo que os critérios do DSM-IV contribuem na verificação do constructo dependência de açúcar.

Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

Directory of Open Access Journals (Sweden)

Shaohua Luo

2016-09-01

Full Text Available This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the “explosion of complexity” of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

Using An Adapter To Perform The Chalfant-Style Containment Vessel Periodic Maintenance Leak Rate Test

International Nuclear Information System (INIS)

Loftin, B.; Abramczyk, G.; Trapp, D.

2011-01-01

Recently the Packaging Technology and Pressurized Systems (PT and PS) organization at the Savannah River National Laboratory was asked to develop an adapter for performing the leak-rate test of a Chalfant-style containment vessel. The PT and PS organization collaborated with designers at the Department of Energy's Pantex Plant to develop the adapter currently in use for performing the leak-rate testing on the containment vessels. This paper will give the history of leak-rate testing of the Chalfant-style containment vessels, discuss the design concept for the adapter, give an overview of the design, and will present results of the testing done using the adapter.

How to determine control of growth rate in a chemostat. Using metabolic control analysis to resolve the paradox

DEFF Research Database (Denmark)

Snoep, Jacky L.; Jensen, Peter Ruhdal; Groeneveld, Philip

1994-01-01

how, paradoxically, one can determine control of growth rate, of growth yield and of other fluxes in a chemostat. We develop metabolic control analysis for the chemostat. this analysis does not depend on the particular way in which specific growth rate varies with the concentration of the growth...

Adaptive Optics Facility: control strategy and first on-sky results of the acquisition sequence

Science.gov (United States)

Madec, P.-Y.; Kolb, J.; Oberti, S.; Paufique, J.; La Penna, P.; Hackenberg, W.; Kuntschner, H.; Argomedo, J.; Kiekebusch, M.; Donaldson, R.; Suarez, M.; Arsenault, R.

2016-07-01

The Adaptive Optics Facility is an ESO project aiming at converting Yepun, one of the four 8m telescopes in Paranal, into an adaptive telescope. This is done by replacing the current conventional secondary mirror of Yepun by a Deformable Secondary Mirror (DSM) and attaching four Laser Guide Star (LGS) Units to its centerpiece. In the meantime, two Adaptive Optics (AO) modules have been developed incorporating each four LGS WaveFront Sensors (WFS) and one tip-tilt sensor used to control the DSM at 1 kHz frame rate. The four LGS Units and one AO module (GRAAL) have already been assembled on Yepun. Besides the technological challenge itself, one critical area of AOF is the AO control strategy and its link with the telescope control, including Active Optics used to shape M1. Another challenge is the request to minimize the overhead due to AOF during the acquisition phase of the observation. This paper presents the control strategy of the AOF. The current control of the telescope is first recalled, and then the way the AO control makes the link with the Active Optics is detailed. Lab results are used to illustrate the expected performance. Finally, the overall AOF acquisition sequence is presented as well as first results obtained on sky with GRAAL.

A comparison of two adaptive algorithms for the control of active engine mounts

Science.gov (United States)

Hillis, A. J.; Harrison, A. J. L.; Stoten, D. P.

2005-08-01

This paper describes work conducted in order to control automotive active engine mounts, consisting of a conventional passive mount and an internal electromagnetic actuator. Active engine mounts seek to cancel the oscillatory forces generated by the rotation of out-of-balance masses within the engine. The actuator generates a force dependent on a control signal from an algorithm implemented with a real-time DSP. The filtered-x least-mean-square (FXLMS) adaptive filter is used as a benchmark for comparison with a new implementation of the error-driven minimal controller synthesis (Er-MCSI) adaptive controller. Both algorithms are applied to an active mount fitted to a saloon car equipped with a four-cylinder turbo-diesel engine, and have no a priori knowledge of the system dynamics. The steady-state and transient performance of the two algorithms are compared and the relative merits of the two approaches are discussed. The Er-MCSI strategy offers significant computational advantages as it requires no cancellation path modelling. The Er-MCSI controller is found to perform in a fashion similar to the FXLMS filter—typically reducing chassis vibration by 50-90% under normal driving conditions.

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

Science.gov (United States)

Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

Influence of Sensory Dependence on Postural Control

Science.gov (United States)

Santana, Patricia A.; Mulavara, Ajitkumar P.; Fiedler, Matthew J.

2011-01-01

The current project is part of an NSBRI funded project, "Development of Countermeasures to Aid Functional Egress from the Crew Exploration Vehicle Following Long-Duration Spaceflight." The development of this countermeasure is based on the use of imperceptible levels of electrical stimulation to the balance organs of the inner ear to assist and enhance the response of a person s sensorimotor function. These countermeasures could be used to increase an astronaut s re-adaptation rate to Earth s gravity following long-duration space flight. The focus of my project is to evaluate and examine the correlation of sensory preferences for vision and vestibular systems. Disruption of the sensorimotor functions following space flight affects posture, locomotion and spatial orientation tasks in astronauts. The Group Embedded Figures Test (GEFT), the Rod and Frame Test (RFT) and the Computerized Dynamic Posturography Test (CDP) are measurements used to examine subjects visual and vestibular sensory preferences. The analysis of data from these tasks will assist in relating the visual dependence measures recognized in the GEFT and RFT with vestibular dependence measures recognized in the stability measures obtained during CDP. Studying the impact of sensory dependence on the performance in varied tasks will help in the development of targeted countermeasures to help astronauts readapt to gravitational changes after long duration space flight.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Adaptive Non-linear Control of Hydraulic Actuator Systems

DEFF Research Database (Denmark)

Hansen, Poul Erik; Conrad, Finn

1998-01-01

Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....

Adaptive control for accelerators

International Nuclear Information System (INIS)

Eaton, L.E.; Jachim, S.P.; Natter, E.F.

1991-01-01

This patent describes an adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity

Adaptive control for accelerators

Science.gov (United States)

Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

1991-01-01

An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles

Science.gov (United States)

2007-11-01

Tolerant Overactuated Autonomous Vehicles Casavola, A.; Garone, E. (2007) Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous ...Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Tolerant Overactuated Autonomous Vehicles 3.2 - 2 RTO-MP-AVT-145 UNCLASSIFIED/UNLIMITED Control allocation problem (CAP) - Given a virtual input v(t

Adaptive Robot Control – An Experimental Comparison

Directory of Open Access Journals (Sweden)

Francesco Alonge

2012-11-01

Full Text Available This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with the new management algorithm, outperforms the conventional Model-Based schemes in the presence of structural uncertainties in the mathematical model of the robot, without pre-training and more efficiently than the Neural Network approach.

Recurrent myocardial infarction: Mechanisms of free-floating adaptation and autonomic derangement in networked cardiac neural control.

Science.gov (United States)

Kember, Guy; Ardell, Jeffrey L; Shivkumar, Kalyanam; Armour, J Andrew

2017-01-01

The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as 'free-floating' in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease.

Model reference adaptive control and adaptive stability augmentation

DEFF Research Database (Denmark)

Henningsen, Arne; Ravn, Ole

1993-01-01

A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...... stability augmented model reference design is proposed. By utilizing the closed-loop control error, a simple auxiliary controller is tuned, using a normalized MIT rule for the parameter adjustment. The MIT adjustment is protected against the effects of unmodelled dynamics by lowpass filtering...... of the gradient. The proposed method is verified through simulation results indicating that the method may lead to an improvement of the model reference controller in the presence of unmodelled dynamics...

Illusory reversal of causality between touch and vision has no effect on prism adaptation rate

Directory of Open Access Journals (Sweden)

Hirokazu eTanaka

2012-12-01

Full Text Available Learning, according to Oxford Dictionary, is to gain knowledge or skill by studying, from experience, from being taught, etc. In order to learn from experience, the central nervous system has to decide what action leads to what consequence, and temporal perception plays a critical role in determining the causality between actions and consequences. In motor adaptation, causality between action and consequence is implicitly assumed so that a subject adapts to a new environment based on the consequence caused by her action. Adaptation to visual displacement induced by prisms is a prime example; the visual error signal associated with the motor output contributes to the recovery of accurate reaching, and a delayed feedback of visual error can decrease the adaptation rate. Subjective feeling of temporal order of action and consequence, however, can be modified or even reversed when her sense of simultaneity is manipulated with an artificially delayed feedback. Our previous study (Tanaka, Homma & Imamizu (2011 Exp Brain Res demonstrated that the rate of prism adaptation was unaffected when the subjective delay of visual feedback was shortened. This study asked whether subjects could adapt to prism adaptation and whether the rate of prism adaptation was affected when the subjective temporal order was illusory reversed. Adapting to additional 100 ms delay and its sudden removal caused a positive shift of point of simultaneity in a temporal-order judgment experiment, indicating an illusory reversal of action and consequence. We found that, even in this case, the subjects were able to adapt to prism displacement with the learning rate that was statistically indistinguishable to that without temporal adaptation. This result provides further evidence to the dissociation between conscious temporal perception and motor adaptation.

Illusory Reversal of Causality between Touch and Vision has No Effect on Prism Adaptation Rate.

Science.gov (United States)

Tanaka, Hirokazu; Homma, Kazuhiro; Imamizu, Hiroshi

2012-01-01

Learning, according to Oxford Dictionary, is "to gain knowledge or skill by studying, from experience, from being taught, etc." In order to learn from experience, the central nervous system has to decide what action leads to what consequence, and temporal perception plays a critical role in determining the causality between actions and consequences. In motor adaptation, causality between action and consequence is implicitly assumed so that a subject adapts to a new environment based on the consequence caused by her action. Adaptation to visual displacement induced by prisms is a prime example; the visual error signal associated with the motor output contributes to the recovery of accurate reaching, and a delayed feedback of visual error can decrease the adaptation rate. Subjective feeling of temporal order of action and consequence, however, can be modified or even reversed when her sense of simultaneity is manipulated with an artificially delayed feedback. Our previous study (Tanaka et al., 2011; Exp. Brain Res.) demonstrated that the rate of prism adaptation was unaffected when the subjective delay of visual feedback was shortened. This study asked whether subjects could adapt to prism adaptation and whether the rate of prism adaptation was affected when the subjective temporal order was illusory reversed. Adapting to additional 100 ms delay and its sudden removal caused a positive shift of point of simultaneity in a temporal order judgment experiment, indicating an illusory reversal of action and consequence. We found that, even in this case, the subjects were able to adapt to prism displacement with the learning rate that was statistically indistinguishable to that without temporal adaptation. This result provides further evidence to the dissociation between conscious temporal perception and motor adaptation.

Adaptive neuro-fuzzy control of ionic polymer metal composite actuators

International Nuclear Information System (INIS)

Thinh, Nguyen Truong; Yang, Young-Soo; Oh, Il-Kwon

2009-01-01

An adaptive neuro-fuzzy controller was newly designed to overcome the degradation of the actuation performance of ionic polymer metal composite actuators that show highly nonlinear responses such as a straightening-back problem under a step excitation. An adaptive control algorithm with the merits of fuzzy logic and neural networks was applied for controlling the tip displacement of the ionic polymer metal composite actuators. The reference and actual displacements and the change of the error with the electrical inputs were recorded to generate the training data. These data were used for training the adaptive neuro-fuzzy controller to find the membership functions in the fuzzy control algorithm. Software simulation and real-time experiments were conducted by using the Simulink and dSPACE environments. Present results show that the current adaptive neuro-fuzzy controller can be successfully applied to the reliable control of the ionic polymer metal composite actuator for which the performance degrades under long-time actuation

Functional Dual Adaptive Control with Recursive Gaussian Process Model

International Nuclear Information System (INIS)

Prüher, Jakub; Král, Ladislav

2015-01-01

The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition

Science.gov (United States)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu

2010-01-01

Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.

Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design

DEFF Research Database (Denmark)

Fazio, Alessandro; Jewett, Michael Christopher; Daran-Lapujade, Pascale

2008-01-01

, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets. Conclusion: Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more......Background: Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of Saccharomyces cerevisiae. The three...... factors we considered were specific growth rate, nutrient limitation, and oxygen availability. Results: We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which m...