OPTIMAL CONTROL FOR GROUNDWATER REMEDIATION BY DIFFERENTIAL DYNAMIC PROGRAMMING WITH QUASI-NEWTON APPROXIMATIONS

Differential dynamic programming with quasi-Newton approximations (QNDDP) is combined with a finite element groundwater quality simulation model to determine optimal time-varying pumping policies for reclamation of a contaminated aquifer. The purpose of the QNDDP model is to significantly reduce the large computational effort associated with calculation of optimal time-varying policies. A Broyden rank-one quasi-Newton technique is developed to approximate the second derivatives of the groundwater quality model; these second derivatives are difficult to calculate directly. The performance of the QNDDP algorithm is compared to the successive approximation linear quadratic regulator (SALQR) technique, which sets the complicated second derivatives to 0. QNDDP converged to the optimal pumping policy in approximately half the time that the SALQR technique required. The QNDDP algorithm thus shows great promise for the management of complex, time-varying systems.

[1]  C. Shoemaker,et al.  Dynamic optimal control for groundwater remediation with flexible management periods , 1992 .

[2]  P. Gill,et al.  Aquifer Reclamation Design: The Use of Contaminant Transport Simulation Combined With Nonlinear Programing , 1984 .

[3]  L. Liao,et al.  Convergence in unconstrained discrete-time differential dynamic programming , 1991 .

[4]  S. Yakowitz,et al.  Constrained differential dynamic programming and its application to multireservoir control , 1979 .

[5]  L. Jones,et al.  Optimal control of nonlinear groundwater hydraulics using differential dynamic programming , 1987 .

[6]  G. Pinder,et al.  Contaminated groundwater remediation design using simulation, optimization, and sensitivity theory: 2. Analysis of a field site , 1988 .

[7]  Tsung‐Wu Lin Well‐behaved penalty functions for constrained optimization , 1990 .

[8]  S. Sen,et al.  A quasi-newton differential dynamic programming algorithm for discrete-time optimal control , 1987, Autom..

[9]  Sidney Yakowitz,et al.  Algorithms and Computational Techniques in Differential Dynamic Programming , 1989 .

[10]  S. Gorelick,et al.  Hydraulic gradient control for groundwater contaminant removal , 1985 .

[11]  L. Liao,et al.  Advantages of Differential Dynamic Programming Over Newton''s Method for Discrete-time Optimal Control Problems , 1992 .

[12]  David P. Ahlfeld,et al.  Two‐Stage Ground‐Water Remediation Design , 1990 .

[13]  R. Willis Optimal groundwater quality management: Well injection of waste waters , 1976 .

[14]  D. Mayne A Second-order Gradient Method for Determining Optimal Trajectories of Non-linear Discrete-time Systems , 1966 .

[15]  John M. Mulvey,et al.  Contaminated groundwater remediation design using simulation, optimization, and sensitivity theory: 1. Model development , 1988 .

[16]  John M. Mulvey,et al.  Designing optimal strategies for contaminated groundwater remediation , 1986 .

[17]  Roko Andričević,et al.  A Real‐Time Approach to Management and Monitoring of Groundwater Hydraulics , 1990 .

[18]  C. Shoemaker,et al.  Optimal time-varying pumping rates for groundwater remediation: Application of a constrained optimal control algorithm , 1992 .

[19]  P. Kitanidis,et al.  Optimization of the pumping schedule in aquifer remediation under uncertainty , 1990 .

[20]  Sang-Il Lee,et al.  Optimal Estimation and Scheduling in Aquifer Remediation With Incomplete Information , 1991 .

[21]  Miguel A. Mariño,et al.  Optimal control of groundwater by the feedback method of control , 1989 .

[22]  S. Yakowitz,et al.  Computational aspects of discrete-time optimal control , 1984 .

[23]  R. Willis A planning model for the management of groundwater quality , 1979 .