Robust Optimal Control of Uncertain Nonaffine MIMO Nonlinear Discrete-Time Systems with Application to HCCI Engines
MIMO optimal control of unknown nonaffine nonlinear discrete-time systems is a challenging problem owing to the presence of control inputs inside the unknown nonlinearity. in this paper, the nonaffine nonlinear discrete-time system is transformed to an affine-like equivalent nonlinear discrete-time system in the input-output form. Next, a forward-in-time Hamilton-Jacobi-Bellman equation-based optimal approach, without using value and policy iterations, is developed to control the affine-like nonlinear discrete-time system by using both NN as an online approximator and output measurements alone. to overcome the need to know the control gain matrix in the optimal controller, a new online discrete-time NN identifier is introduced. the robustness of the overall closed-loop system is shown via singular perturbation analysis by using an additional auxiliary term to mitigate the higher-order terms. Lyapunov stability of the overall system, which includes the online identifier and robust control term, demonstrates that the closed-loop signals are bounded and the approximate control input approaches the optimal control signal with a bounded error. the proposed optimal control approach is applied to a cycle-by-cycle discrete-time representation of an experimentally validated homogeneous charge compression ignition fuel-flexible engine whose dynamics are modeled as uncertain nonlinear, nonaffine, and MIMO discrete-time system. Simulation results are included to demonstrate the efficacy of the approach in presence of actuator disturbances. Copyright © 2012 John Wiley & Sons, Ltd.
H. Zargarzadeh et al., "Robust Optimal Control of Uncertain Nonaffine MIMO Nonlinear Discrete-Time Systems with Application to HCCI Engines," International Journal of Adaptive Control and Signal Processing, Wiley-Blackwell, Jan 2012.
The definitive version is available at https://doi.org/10.1002/acs.2294
Mechanical and Aerospace Engineering
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© 2012 Wiley-Blackwell, All rights reserved.
01 Jan 2012