Concetti Chiave
Developing a Multiple Model Reference Adaptive Control scheme with blending for non-square multivariable systems to achieve robust state tracking.
Sintesi
The article introduces a Multiple Model Reference Adaptive Control (MMRAC) scheme with blending for non-square, multi-input, linear, time-invariant systems with uncertain parameters. It discusses the benefits of blending techniques over switching control and presents applications in adaptive identification and control of time-varying systems. The paper extends previous work by developing a parameter identification scheme and control law to ensure state tracking convergence. The stability and efficacy of the proposed MMRAC scheme are illustrated through numerical simulations.
The content is structured as follows:
Introduction to multiple model control techniques
Application of blending control in adaptive identification and control
Development of a MMRAC scheme for state tracking
Parameter identification and stability analysis
Simulation results and comparisons with single model MRAC
Conclusion and final remarks
Statistiche
The plant matrices: Ap = [-4.725, -6.275, -2.175; -0.925, -3.85, 0.35; -3.65, -8.125, -2.825], Bp = [-0.575, -2.2; -0.45, 0.575; -1.025, -1.625]
Reference model matrices: Ar = [-1, 0, 0; 0, -1, 0; 1, 1, -1], Br = [1, 0; 0, 1; 1, 1]
Fixed model pairs A1, B1, A2, B2, A3, B3, A4, B4, A5, B5
Citazioni
"The control architecture is proven to provide boundedness of all closed-loop signals and to asymptotically drive the state tracking error to zero."
"Mixing adaptive techniques have been used to achieve faster tracking for a class of nonlinear discrete-time systems."