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Fractional Order LQR for Optimal Control of Civil Structures Abdollah Shafieezadeh*, Keri Ryan*, YangQuan Chen+ *Civil and Environmental Engineering Dept. +Electrical and Computer Engineering Dept. Utah State University. Speaker: Abdollah Shafieezadeh Email: abdshafiee@cc.usu.edu
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Fractional Order LQR for Optimal Control of Civil StructuresAbdollah Shafieezadeh*, Keri Ryan*, YangQuan Chen+*Civil and Environmental Engineering Dept.+Electrical and Computer Engineering Dept.Utah State University Speaker: Abdollah Shafieezadeh Email: abdshafiee@cc.usu.edu 2007 ASME DETC 3RD FDTA, Sept. 4, 2007
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Introduction • Optimal control theories have been studied intensely for civil engineering structures. • In most cases, idealized models were used for both the structure and actuators. • Fractional order filters, offering more features are applied here.
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Goals of Structural Control • Functionality • Safety • Human comfort • Flexibility for design
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
f(t) FD f(t) FI FS Example of A Fractional Order System • A mass-damper-spring system • Conventional models • Hook’s law • Ideal viscoelastic materials • Second Newton’s law • New fractional models
Mathematical Definition • Definitions of fractional derivatives and integrals • Rienmann-Liouville • Grunvald-Letnikov • Caputo • Miller-Ross • Caputo (1967)
Modified Oustaloup’s approximation algorithm for Sα by Xue et al. Numerical Solution where Using Oustaloup’s approximation
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Optimization Process • Analytical optimization • Given a set of gains for output and input control force, LQR approach gives the best controller. • Numerical optimization • The output is sensitive to chosen gains • H2 method leads to an optimal controller in the sense of 2-norm if the input disturbance is white noise.
Numerical Optimization Process • Performance Index • RMS response for frequent moderate events like wind • MAX response for extreme events like earthquake • Selection of β1 and β2 are based on the control objectives • 64 artificially generated earthquakes are used in optimization part.
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Combined FOC-LQR Strategies • Case (1) • Case (2a) • Case (2b) • Case (3)
Combined FOC-LQR Strategiesloop diagram Case (1), (2a), and (2b) Case (3)
Civil Structure Model • Governing Equation • State Space Model • Natural periods of the building are 0.3 and 0.14 seconds • Damping is 2% in each mode
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Results • Case (1) • Klqr is constant and a search is done to find α • In other cases, Matlab Optimization Toolbox is used to find optimal gains and fractional orders
Results • The structural performance for El Centro earthquake is much better than for Kobe and Northridge earthquakes • Filter model: The Kanai-Tajimi filter used in optimization gives similar trend to real ground motions in frequency domain but not in time domain • Saturation limit: Larger ground motions require larger control force. Kobe and Northridge have PGA of 2.5 times larger than El Centro
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Future Works • A more realistic structure is considered. • The building model is nonlinear which can form plastic hinges at the column ends. • MR dampers which are more applicable replaced ideal actuators. • General H2 robust control approach is used as the primary controller • The performance is enhanced by introducing some filters for input disturbance, output, and actuator.
Hybrid Testing • part of the structure which is numerically hard to model is constructed at lab and tested • Other parts of the structure is numerically modeled in computer • The interaction between superstructure and substructure are applied by actuators
Outlines • Goals of structural control • Introducing fractional calculus • Optimization process • Combined FOC-LQR strategies • Results • Future works • Conclusions
Conclusion • Several combinations of FOC and LQR were considered. • 64 artificially generated earthquakes were used to optimize the controller gains. • Case (2a) gives the best performance. It reduces the performance index by 36% compared to LQR. • Controllers led to the same trend in performance for real earthquakes as the artificial ones.