Nonlinear Predictive Control of Transients in Automotive Variable Cam Timing Engine Using Nonlinear Parametric Approximation

2003 ◽  
Vol 125 (3) ◽  
pp. 429-438 ◽  
Author(s):  
Dimitry Gorinevsky ◽  
Jeffrey Cook ◽  
George Vukovich

The paper considers design of a predictive Linear Time Varying model-based controller with nonlinear feedforward for regulation of transient processes caused by setpoint step changes in a nonlinear plant. An optimal feedforward control sequence is computed based on an empirical Finite Impulse Response model of the process. Though the control techniques developed in this paper are meant to have more general industrial applicability, a specific automotive engine control application—control of Variable Cam Timing automotive engine—is pursued. An advantage of the proposed controller design in this problem is that no first principle models are required. Instead, nonlinear parametric approximations of a neural network type are being used to describe and identify static nonlinear mappings encountered in the problem. A number of simplifying assumptions and approximations are made to make practical implementation of the proposed scheme possible. Validity of the designed controller is verified by simulation. The proposed “model-free” design can potentially increase flexibility and save labor in development and deployment of such controllers for industrial systems.

Author(s):  
Sicheng Yi ◽  
Qingze Zou

In this paper, we propose a finite-impulse-response (FIR)-based feedforward control approach to mitigate the acoustic-caused probe vibration during atomic force microscope (AFM) imaging. Compensation for the extraneous probe vibration is needed to avoid the adverse effects of environmental disturbances such as acoustic noise on AFM imaging, nanomechanical characterization, and nanomanipulation. Particularly, residual noise still exists even though conventional passive noise cancellation apparatus has been employed. The proposed technique exploits a data-driven approach to capture both the noise propagation dynamics and the noise cancellation dynamics in the controller design, and is illustrated through the experimental implementation in AFM imaging application.


Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.


2020 ◽  
Vol 10 (10) ◽  
pp. 3592
Author(s):  
Bo-Sheng Chen ◽  
Ching-Hung Lee

In this study, we introduce an adaptive model-free coupling controller while using recurrent fuzzy neural network (RFNN) for multi-axis system to minimize the contour error. The proposed method can be applied to linear or nonlinear multi-axis motion control systems following desired paths. By the concept of cross-coupling control (CCC), multi-axis system is transferred into a nonlinear time-varying system due to the time-dependent coordinate transformation; tangential, normal, and bi-normal components of desired contour. Herein, we propose a model-free adaptive coupling controller design approach for multi-axis linear motor system with uncertainty and nonlinear phenomena. RFNN establishes the corresponding adaptive coupling controller to treat the uncertain system with nonlinear phenomenon. The stability of closed-loop system is guaranteed by the Lyapunov method and the adaptation of RFNN is also obtained. Simulation results are introduced in order to illustrate the effectiveness.


2002 ◽  
Vol 8 (5) ◽  
pp. 659-671 ◽  
Author(s):  
Mosaad Mosleh ◽  
Amier Al-Ali

A linear time invariant (LTI) model of a marine diesel engine is presented. The effect of the discontinuity of the fuel injection into the cylinders and the injection period is considered. The proposed discrete model consists of a sampler and zero-order-hold mechanism, representing the fuel injection process. The design of the discrete controller is based on the pole assignment of the characteristic polynomial of the closed-loop transfer function with the goal of achieving zero steady-state error, and satisfying other design specifications. A numerical example illustrating the characteristic performance of a two stroke marine diesel engine is presented.


Author(s):  
Gullik A. Jensen ◽  
Thor I. Fossen

This paper considers mathematical models for model-based controller design in offshore pipelay operations. Three classes of models for control design are discussed, real-world models suitable for controller design verification, controller and observer models which are used on-line in the control system implementation. The control application place requirements on the model with respect to the computational time, dynamic behavior, stability and accuracy. Models such as the beam model, two catenary models, as well as general finite element (FE) models obtained from computer programs were not able to meet all of the requirements, and two recent dynamic models designed for control are presented, which bridge the gap between the simple analytical and more complex FE models. For completeness, modeling of the pipelay vessel, stinger and roller interaction, soil and seabed interaction and environmental loads are discussed.


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