Hybrid structural control using magnetorheological dampers for base isolated structures

In this paper two nonlinear model based control algorithms have been developed to monitor the magnetorheological (MR) damper voltage. The main advantage of the proposed algorithms is that it is possible to directly monitor the voltage required to control the structural vibration considering the effect of the supplied and commanded voltage dynamics of the damper. The efficiency of the proposed techniques has been shown and compared taking an example of a base isolated three-storey building under a set of seismic excitations. Comparison of the performances with a fuzzy based intelligent control algorithm and a widely used clipped optimal strategy has also been shown.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies

A new structured model-following adaptive approach is presented in this paper to achieve large attitude maneuvers of rigid bodies. First, a nominal controller is designed using the dynamic inversion philosophy. Next, a neuro- adaptive design is proposed to augment the nominal design in order to assure robust performance in the presence of parameter inaccuracies as well as unknown constant external disturbances. The structured approach proposed in this paper (where kinematic and dynamic equations are handled separately), reduces the complexity of the controller structure. From simulation studies, this adaptive controller is found to be very effective in assuring robust performance.

Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0)

Increasing concentrations of atmospheric CO2 decrease stomatal conductance of plants and thus suppress canopy transpiration. The climate response to this CO2-physiological forcing is investigated using the Community Atmosphere Model version 3.1 coupled to Community Land Model version 3.0. In response to the physiological effect of doubling CO2, simulations show a decrease in canopy transpiration of 8%, a mean warming of 0.1K over the land surface, and negligible changes in the hydrological cycle. These climate responses are much smaller than what were found in previous modeling studies. This is largely a result of unrealistic partitioning of evapotranspiration in our model control simulation with a greatly underestimated contribution from canopy transpiration and overestimated contributions from canopy and soil evaporation. This study highlights the importance of a realistic simulation of the hydrological cycle, especially the individual components of evapotranspiration, in reducing the uncertainty in our estimation of climatic response to CO2-physiological forcing. Citation: Cao, L., G. Bala, K. Caldeira, R. Nemani, and G.Ban-Weiss (2009), Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0).

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

Indian Ocean sea surface salinity variations in a coupled model

The variability of the sea surface salinity (SSS) in the Indian Ocean is studied using a 100-year control simulation of the Community Climate System Model (CCSM 2.0). The monsoon-driven seasonal SSS pattern in the Indian Ocean, marked by low salinity in the east and high salinity in the west, is captured by the model. The model overestimates runoff int the Bay of Bengal due to higher rainfall over the Himalayan-Tibetan regions which drain into the Bay of Bengal through Ganga-Brahmaputra rivers. The outflow of low-salinity water from the Bay of Bengal is to strong in the model. Consequently, the model Indian Ocean SSS is about 1 less than that seen in the climatology. The seasonal Indian Ocean salt balance obtained from the model is consistent with the analysis from climatological data sets. During summer, the large freshwater input into the Bay of Bengal and its redistribution decide the spatial pattern of salinity tendency. During winter, horizontal advection is the dominant contributor to the tendency term. The interannual variability of the SSS in the Indian Ocean is about five times larger than that in coupled model simulations of the North Atlantic Ocean. Regions of large interannual standard deviations are located near river mouths in the Bay of Bengal and in the eastern equatorial Indian Ocean. Both freshwater input into the ocean and advection of this anomalous flux are responsible for the generation of these anomalies. The model simulates 20 significant Indian Ocean Dipole (IOD) events and during IOD years large salinity anomalies appear in the equatorial Indian Ocean. The anomalies exist as two zonal bands: negative salinity anomalies to the north of the equator and positive to the south. The SSS anomalies for the years in which IOD is not present and for ENSO years are much weaker than during IOD years. Significant interannual SSS anomalies appear in the Indian Ocean only during IOD years.

Performance Study of a Centralized Concurrency Control Algorithm for Distributed Database Systems using SIMULA

The stimulation technique has gained much importance in the performance studies of Concurrency Control (CC) algorithms for distributed database systems. However, details regarding the simulation methodology and implementation are seldom mentioned in the literature. One objective of this paper is to elaborate the simulation methodology using SIMULA. Detailed studies have been carried out on a centralised CC algorithm and its modified version. The results compare well with a previously reported study on these algorithms. Here, additional results concerning the update intensiveness of transactions and the degree of conflict are obtained. The degree of conflict is quantitatively measured and it is seen to be a useful performance index. Regression analysis has been carried out on the results, and an optimisation study using the regression model has been performed to minimise the response time. Such a study may prove useful for the design of distributed database systems.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

Self-tuning control of a class of multivariable non-linear systems

Self-tuning is applied to the minimum variance control of non-linear multivariable systems which can be characterized by a ' multivariable Hammerstein model '. It is also shown that such systems are not amenable to self-tuning control if control costing is to be included in the performance criterion.

Catalyst effectiveness factor for redox model kinetic equation

A generalized isothermal effectiveness factor correlation has been proposed for catalytic reactions whose intrinsic kinetics are based on the redox model. In this correlation which is exact for asymptotic values of the Thiele parameter the effect of the parameters appearing in the model, the order of the reaction and particle geometry are incorporated in a modified form of Thiele parameter. The relationship takes the usual form: Image and predicts effectiveness factor with an error of less than 2% in a range of Thiele parameter that accommodates both the kinetic and diffusion control regimes.

Optimal maintenance policy for equipment subject to random deterioration and random failure A modern control theory approach.

The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example

Automatic Path Planning and Control Design for Autonomous Landing of UAVs using Dynamic Inversion

In this paper a nonlinear control has been designed using the dynamic inversion approach for automatic landing of unmanned aerial vehicles (UAVs), along with associated path planning. This is a difficult problem because of light weight of UAVs and strong coupling between longitudinal and lateral modes. The landing maneuver of the UAV is divided into approach, glideslope and flare. In the approach UAV aligns with the centerline of the runway by heading angle correction. In glideslope and flare the UAV follows straight line and exponential curves respectively in the pitch plane with no lateral deviations. The glideslope and flare path are scheduled as a function of approach distance from runway. The trajectory parameters are calculated such that the sink rate at touchdown remains within specified bounds. It is also ensured that the transition from the glideslope to flare path is smooth by ensuring C-1 continuity at the transition. In the outer loop, the roll rate command is generated by assuring a coordinated turn in the alignment segment and by assuring zero bank angle in the glideslope and flare segments. The pitch rate command is generated from the error in altitude to control the deviations from the landing trajectory. The yaw rate command is generated from the required heading correction. In the inner loop, the aileron, elevator and rudder deflections are computed together to track the required body rate commands. Moreover, it is also ensured that the forward velocity of the UAV at the touch down remains close to a desired value by manipulating the thrust of the vehicle. A nonlinear six-DOF model, which has been developed from extensive wind-tunnel testing, is used both for control design as well as to validate it.

Partial Integrated Guidance and Control of Surface-to-Air Interceptors for High Speed Targets

An important limitation of the existing IGC algorithms, is that they do not explicitly exploit the inherent time scale separation that exist in aerospace vehicles between rotational and translational motions and hence can be ineffective. To address this issue, a two-loop partial integrated guidance and control (PIGC) scheme has been proposed in this paper. In this design, the outer loop uses a recently developed, computationally efficient, optimal control formulation named as model predictive static programming. It gives the commanded pitch and yaw rates whereas necessary roll-rate command is generated from a roll-stabilization loop. The inner loop tracks the outer loop commands using the Dynamic inversion philosophy. Uncommonly, Six-Degree of freedom (Six-DOF) model is used directly in both the loops. This intelligent manipulation preserves the inherent time scale separation property between the translational and rotational dynamics, and hence overcomes the deficiency of current IGC designs, while preserving its benefits. Comparative studies of PIGC with one loop IGC and conventional three loop design were carried out for engaging incoming high speed target. Simulation studies demonstrate the usefulness of this method.

Spiral-Wave Turbulence and Its Control in the Presence of Inhomogeneities in Four Mathematical Models of Cardiac Tissue

Regular electrical activation waves in cardiac tissue lead to the rhythmic contraction and expansion of the heart that ensures blood supply to the whole body. Irregularities in the propagation of these activation waves can result in cardiac arrhythmias, like ventricular tachycardia (VT) and ventricular fibrillation (VF), which are major causes of death in the industrialised world. Indeed there is growing consensus that spiral or scroll waves of electrical activation in cardiac tissue are associated with VT, whereas, when these waves break to yield spiral- or scroll-wave turbulence, VT develops into life-threatening VF: in the absence of medical intervention, this makes the heart incapable of pumping blood and a patient dies in roughly two-and-a-half minutes after the initiation of VF. Thus studies of spiral- and scroll-wave dynamics in cardiac tissue pose important challenges for in vivo and in vitro experimental studies and for in silico numerical studies of mathematical models for cardiac tissue. A major goal here is to develop low-amplitude defibrillation schemes for the elimination of VT and VF, especially in the presence of inhomogeneities that occur commonly in cardiac tissue. We present a detailed and systematic study of spiral- and scroll-wave turbulence and spatiotemporal chaos in four mathematical models for cardiac tissue, namely, the Panfilov, Luo-Rudy phase 1 (LRI), reduced Priebe-Beuckelmann (RPB) models, and the model of ten Tusscher, Noble, Noble, and Panfilov (TNNP). In particular, we use extensive numerical simulations to elucidate the interaction of spiral and scroll waves in these models with conduction and ionic inhomogeneities; we also examine the suppression of spiral- and scroll-wave turbulence by low-amplitude control pulses. Our central qualitative result is that, in all these models, the dynamics of such spiral waves depends very sensitively on such inhomogeneities. We also study two types of control chemes that have been suggested for the control of spiral turbulence, via low amplitude current pulses, in such mathematical models for cardiac tissue; our investigations here are designed to examine the efficacy of such control schemes in the presence of inhomogeneities. We find that a local pulsing scheme does not suppress spiral turbulence in the presence of inhomogeneities; but a scheme that uses control pulses on a spatially extended mesh is more successful in the elimination of spiral turbulence. We discuss the theoretical and experimental implications of our study that have a direct bearing on defibrillation, the control of life-threatening cardiac arrhythmias such as ventricular fibrillation.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.