Multivariable controller design in an adaptive control scheme

A multivariable control system design approach in the frequency domain is presented. The issue of control system redesign in an adaptive control scheme is discussed. Expert system techniques have been used for the automated design of controllers for multivariable systems. Design knowledge has been represented using rules, facts and objects. The design process consists of a sequence of operations obtained by heuristics and experience in the the design techniques. An automated design session of a multivariable plant using the expert system demonstrates that the expert system appears to work well in its prototype implementation.     

A process-control and diagnostic tool based on continuous fuzzy Petri nets

The use of Petri nets and fuzzy logic in intelligent process control has caught the attention of many researchers. In this paper, a Continuous Fuzzy Petri Net (CFPN) tool which integrates the three technologies of fuzzy control, Petri nets and real-time expert systems is presented. The CFPN approach can deal with real-time continuous inferencing, for the purpose of process monitoring and diagnostics, at a high level in the presence of uncertainty. This tool has been implemented in the G2 real-time expert-system environment and is currently being used by ESSO Canada.     

Hydrologic scaling for hydrogeomorphic floodplain mapping: Insights into human‐induced floodplain disconnectivity

Hydrogeomorphic approaches for floodplain modelling are valuable tools for water resource and flood hazard management and mapping, especially as the global availability and accuracy of terrain data increases. Digital terrain models implicitly contain information about floodplain landscape morphology that was produced by hydrologic processes over long time periods, as well as recent anthropogenic modifications to floodplain features and processes. The increased availability of terrain data and distributed hydrologic datasets provide an opportunity to develop hydrogeomorphic floodplain delineation models that can quickly be applied at large spatial scales. This research investigates the performance of a hydrogeomorphic floodplain model in two large urbanized and gauged river basins in the United States, the Susquehanna and the Wabash basins. The models were calibrated by a hydrologic data scaling technique, implemented through regression analyses of USGS peak flow data to estimate floodplain flow levels across multiple spatial scales. Floodplain model performance was assessed through comparison with 100‐year Federal Emergency Management Agency flood hazard maps. Results show that the hydrogeomorphic floodplain maps are generally consistent with standard flood maps, even when significantly and systematically varying scaling parameters within physically feasible ranges, with major differences that are likely due to infrastructure (levees, bridges, etc.) in highly urbanized areas and other locations where the geomorphic signature of fluvial processes has been altered. This study demonstrates the value of geomorphic information for large‐scale floodplain mapping and the potential use of hydrogeomorphic models for evaluating human‐made impacts to floodplain ecosystems and patterns of disconnectivity in urbanized catchments.     

Servo controller design using neural networks

The dynamics of a physical plant may be difficult to express as concise mathematical equations. In practice there exist uncertainties that cannot be modeled with the system equations. Hence, robustness against system uncertainties is essential in a control system design. In this article, multilayered neural networks (MNNs) are used to compensate for model uncertainties of a dynamical system. Neural network models are used along with a classical linear servo controller derived from the linear state space equations. These models are trained so that system uncertainties are compensated. The design of a servo system indicates the enhanced performance of the neural-network-based servo controller as compared to the classical servo controller.     

Effects of counselor sex, race, and language style on black students in initial interviews.

Hypothesized that greater counselor-subject compatibility in race, sex, and language would result in greater client satisfaction and depth of exploration. Ss were 37 black students in a special program for the disadvantaged at a leading eastern state university and 3 black male, 2 black female, 6 white male, and 3 white female counselors. Data were analyzed using the multivariate analysis of covariance with counselor sex and race the independent variables and client depth of self-exploration and satisfaction the dependent variables. Covariates were counselor's level of facilitative conditions and comprehension of nonstandard English. Results indicate that Ss preferred black counselors to a significantly greater degree than white counselors and that they explored themselves in greater depth with female counselors (p     

Response of a silicon photodiode to pulsed radiation

Both the integrated-charge and the peak-voltage responsivity of a 1-cm2 Si photodiode optimized for the extreme ultraviolet have been measured with 532-nm-wavelength pulsed radiation. The peak power of the optical pulse is varied from 35 mW to 24 kW with a pulse width of 8.25 ns. A decrease in responsivity is observed with increasing pulse energy, and a model is presented that accounts for the observed loss of responsivity. The integrated-charge responsivity decreases because the presence of photogenerated majority carriers increases the direct recombination rate. The peak-voltage responsivity is reduced because the electric susceptibility of the electrons and holes in the depletion region increases the capacitance of the device. The influence of an applied reverse bias on both responsivities is investigated. The integrated-charge responsivity is found to be identical, with a 1% uncertainty, to the cw responsivity of the device if the energy dependence is considered.     

Evaluation of a Low-cost MEMS Accelerometer for Distance Measurement

This paper gives an evaluation of a low-cost MEMS accelerometer. The accelerometer is intended for the distance measurement of a mobile robot or platform in short duration. The distance traveled is obtained by double integration of the sensor signal with time. Bias offset drift exhibited in the acceleration signal is accumulative and the accuracy of the distance measurement can deteriorate with time due to the integration. This problem can be fixed by periodic recalibration with the help of external measurements on position, velocity and attitude. These external signals can be calculated by an inertial system. A Kalman filter can use the differences between these values to provide an optimum estimate of the system error. The random bias drift of the accelerometer was found by experiment to be 2.5 mg. The bias drift rate due to temperature was 0.108 g/s when the accelerometer was placed at room temperature. With proper compensation on gravitation, the accelerometer can be a viable solution as a short duration distance-measuring device for a mobile robot.     

EVALUATING TRADEOFFS BETWEEN ENVIRONMENTAL FLOW PROTECTIONS AND AGRICULTURAL WATER SECURITY

River basin managers responsible for water allocation decisions are increasingly required to evaluate tradeoffs between environmental flow protections and human water security. However, the basin‐scale effects of environmental flow regulations on water users are not well understood, in part because analyses are complicated by the spatial and temporal variation in water availability, human demands, and ecosystem needs. Here, we examine alternative regional environmental flow policies and their effects on a distributed network of water users in a small (182 km²) river basin in coastal California. We use a hydrologic model to simulate water diversion operations under three policy scenarios and quantify potential impacts to bypass flows for adult migrating salmon and agricultural water storage. The results indicate that there are inherent tradeoffs between environmental flows and agricultural water security, with the most restrictive environmental policy associated with the greatest impacts to water users. Surprisingly, the moderate environmental flow policy had larger impacts to bypass flows than the unregulated management scenario, suggesting that ecological benefits of the moderate policy are small relative to the adverse effects on agricultural water users. Conflicts between environmental and human water needs were greatest in upper catchments (<2.5 km²), where flow protections caused the greatest reduction in water storage. Although natural supplies were adequate for meeting water needs in most years regardless of policy restrictions, potential for conflict between environmental flow protections and water security was evident in dry years. Therefore, strategies are particularly needed for drought‐year water management to ensure adequate environmental flows while reducing human water allocations in an equitable manner. Copyright © 2013 John Wiley & Sons, Ltd.     

Design of Bang-bang Controller Based on a Fuzzy-Neuro Approach: Application to a Heating System

A fuzzy-neuro approach for the design of bang-bang controller is presented in this paper. The approach has been used with success for the time optimal bang-bang control of a heating system. The improved bang-bang controller suppresses the oscillations often observed at the output of an on-off controller. A fuzzy system is used for the implementation of the on-off control. An extension of the fuzzy control is provided by an equivalent neural network of the fuzzy system. A test application, that of a house heating with a two-state furnace, is developed and evaluated with standard hysteresis switching, fuzzy control, and fuzzy-neuro control.