GAOT-ECM Seismic Vibration Case Study

GAOT-ECM: Extension For Control And Modeling - Seismic Vibration Case Study with MR Damper

GAOT-ECM (GAOT - Extension For Control And Modeling) is an extension of the Genetic Algorithm Optimization Toolbox (GAOT) by C.R. Houck, J.A. Joines, M.G. Kay, that implements genetic algorithms for industrial plant identification and PID controller design.
This file contains the Seismic Vibration Case Study. For other examples, please consult the GAOT-ECM: Extension For Control And Modeling main file.
This extension brings forth the practical aspect of using genetic algorithms in aiding plant modeling and PID control design for real world industrial processes. Plants such water tanks, heaters, fans and motors are usually hard to model or tune on-site, especially after prolonged use of the equipment when degradation of performances is inevitable. Therefore, this toolbox extension introduces a series of practical steps that can be taken by control engineers in order to re-design viable PID controllers for their plants.
Inside the GAOT-ECM Seismic Vibration Case Study archive you will find the folder: MR Damper, which runs a PID controller design genetic algorithm under various customizable performance criteria.

For this case study, a base isolation system is considered for a three story building. The damper is mounted in the base of the structure, which is controlled via an LQR law on the outer loop of a cascaded control system. A PID controller is chosen to be designed using GAs for the inner loop containing the damper. The output forces generated by seismic dampers are required to be maintained between specific limits, so they do not cause instability to the structure, breaks support beams and so on. Therefore, a control loop for the actuator is required, that will receive the desired control forces computed by higher algorithms (such as robust laws, intelligent controllers, adaptive, modal, etc.) as setpoints and ensure that they are precisely reproduced by the actual damper output force. Analysis for validation and LQR command matrix are included.

GAOT-ECM was implemented and tested under Matlab 7 (R2011b).

Enjoy!

Acknowledgements: GAOT-ECM Toolbox(GAOT - Extension For Control And Modeling ) was inspired by Genetic Algorithm Optimization Toolbox (GAOT) by C.R. Houck, J.A. Joines, M.G. Kay.

Citing information: Patrascu M., Ion A. 2016 - Evolutionary Modeling of Industrial Plants and Design of PID Controllers. Case Studies and Practical Applications, Nature-Inspired Computing for Control Systems (Ed. H.E.Ponce Espinosa), Series Studies in Systems, Decision and Control, vol. 40, pp. 73-119, Springer International Publishing, doi: 10.1007/978-3-319-26230-7_4