HYDRAULIC COMPLIANCE IDENTIFICATION USING A PARALLEL GENETIC ALGORITHM

The application of a genetic algorithm to the estimation of hydraulic system parameters in heavy-duty hydraulically-actuated manipulators is described. Identification of hydraulic compliance (indication of join t flexibility) was particularly of interest because of its significant effect on the performance of the class of machines under investigatio n. Robust and fast identification of this important parameter is essen tial for diagnosis purposes as well as for improving the control actio ns. Using real experimental data obtained from an instrumented Caterpi llar 215B excavator, the values of the hydraulic compliance for variou s links were successfully identified. The algorithm was able to handle the nonlinear and coupled actuation dynamics of the hydraulic system with its nonrecursive, population-based search power. The scheme was f urther studied in order to enhance its speed as well as its parameter tracking ability. Two different parallelization techniques, namely syn chronous master-slave and cooperating sequential, were combined at bot h population and fitness evaluation levels. The algorithm was then imp lemented using 16 T800 transputers connected to a SUN host workstation . It achieved a speed-up factor of 12 over a traditional genetic algor ithm. At such speed, real-time simultaneous monitoring of hydraulic co mpliances at two joints was possible. Using normal operating data, the right values of compliances from the parameter space were achieved in only a few iterations.