V. Gourishankar

Optimal control for large-scale systems: a recursive approach

A recursive fixed-point-type method is presented for the study of the optimal control problem of large-scale systems. The control is obtained by decomposition of the system to ‘e coupled’ subsystems so that only low-order systems are involved in algebraic computations. It is shown that the developed reduced-order parallel algorithms converge to the desired solution with the rate O(e). Owing to its recursive nature, the presented method produces a considerable saving of computation. An illustrative numerical example is given to verify the proposed approach.

Optimal control of water pollution in a river stream

This paper is concerned with the application of optimal control techniques to ecological systems. In particular, the control of pollution of water in a river stream is considered. The variables to be controlled are the concentration of Biochemical Oxygen Demand (BOD) and the level of Dissolved Oxygen (DO) in the water. This is proposed to be achieved by controlled dumping of industrial effluents and/or artificial aeration. These constitute the controls. A realistic determination of the optimum values of these controls is subject to several performance criteria relating to water quality. Since some of these criteria are contradictory the problem is tackled (unlike previous investigators) from the point of view of a multi-cost system. Recently published theory on multi-cost system optimization is used. Numerical examples are presented.

A digital water quality controller for polluted streams

A procedure is described for designing a digital controller for maintaining the level of dissolved oxygen in a polluted river. The controller generates discrete-time profiles for aeration input and rate of effluent discharge which are used as the controls. Simulation results show that the digital controller performs quite well compared to the continuous-time controllers described in an earlier paper (Gourishankar and Ramar 1977). Computer simulation results are presented to show that the digital controller, designed on the basis that the river system model parameters are constant, performs well with seasonal temperature variations which affect the model parameters.

Control of water quality in polluted streams

A technique familiar to control system engineers, namely pole assignment, is used to design a controller for maintaining the concentration of dissolved oxygon in a polluted stream at a desired level. Artificial in-stream aeration and volumetric flow rate of effluent discharge are used as the controls. Since the model parameter values are affected by the controls, and since all the states are not available for feedback, the polo-assignment technique described here uses output feedback and minimizes the sensitivity of the polos to parameter variations. Computer simulation results are included.

Composite control of discrete singularly perturbed systems with stochastic jump parameters

Abstract In this paper, a singular perturbation approach is presented to study discrete systems with stochastic jump parameters. The feedback controller design is decomposed into the design of slow and fast controllers which are combined to form the composite control. The multirate control structure allows the designer to accomodate multiple information rates and to implement required control computations. Conditions for complete separation of slow and fast regulator designs are given. It is shown that the composite feedback control is O(e) close to the optimal one, which yields an O(e2) approximation of optimal performance.

Robust estimation and compensation for actuator and sensor failures in linear systems

A computationally feasible technique for the robust detection and estimation for actuator and sensor failures is presented. Model errors and component failures are represented by a bias vector called the failure state in system and measurement equations. A Kalman-Bucy filter is implemented to estimate the system state, and to generate the corresponding residuals. These residuals are then processed by using an adaptive fading Kalman filter to give the failure state estimate. The final state estimate is obtained by compensating model errors and component failures in the filter based on no failure assumption. The divergency of the filter based on no failure assumption is avoided by stepwise compensation of the failure state. The technique is applicable to the detection, estimation and compensation of slowly varying model errors and suddenly occurring component failures, and to the discrimination between them

Near-optimum control of flexible manipulators

In this paper, the control problem for flexible manipulators is considered. The results are based on the singular perturbation formulation of flexible manipulator equations. A complete model of system dynamics is utilized in the design, but it is separated into slow (rigid) and fast (flexible) subsystems. A composite controller is obtained by combining a controller for the slow component and a second controller devoted to stabilizing the link compliance modes. Since the design method incorporates structural flexibility in the model, the results appear quite promising.<<ETX>>

Robust Failure Detection, Estimation and Compensation in Linear Systems

1 Failure model of linear systems Kalman filters can not work well in the cases where the systems include significan t model errors and com pone n t failu res. A filter which is able to detect and compensate the failures is required. Two failure detection techniques [1][2] have beeni developed using the separated-bias estimation algorithm [3]. In this paper, the separated-bias estimation algorithm is combined with the adaptive fading Kalman filter [4] to give a simple and effective detection technique for actuator and sensor failures. The failure states (biases) represent component failures when some failure occurs, otherwise represent model errors. Consider a linear, discrete time, stochastic system

An observer-based water quality controller for polluted river streams

A feedback controller for maintaining the concentration of dissolved oxygen (DO) at a specified level in a single stretch of a non-tidal river stream polluted by effluents is described. The control signals are artificial instream aeration and rate of effluent discharge. An observer is used to estimate the incremental changes in the down stream biochemical oxygen demand (BOD) from a knowledge of the output DO and upstream DO and BOD. This estimate and the output DO are used to generate the control signals. Computer simulation results are included. A comparison of these results with those obtained earlier by mentis of n constant gain output feedback control (Gouriahankar and Ramur 1077) indicates that the present scheme enables greater quantities of effluents to be discharged for the same upstream disturbances.