Engine Idle Speed Control Problem Research Articles

Adaptive neural tracking control for automotive engine idle speed regulation using extreme learning machine

The automotive engine idle speed control problem is a compromise among low engine speed for fuel saving, minimum emissions and disturbance rejection ability to prevent engine stall. However, idle speed regulation is very challenging due to the presence of high nonlinearity and aging-caused uncertainties in the engine dynamics. Therefore, the engine idle speed system is a typical uncertain nonlinear system. To address the problems of inherent nonlinearity and uncertainties in idle speed regulation, an extreme learning machine (ELM)-based adaptive neural control algorithm is proposed for tracking the target idle speed adaptively. The purpose of ELM is to rapidly deal with the uncertain nonlinear engine system. Since the original ELM is not designed for adaptive control, a new adaptation law is designed to update the weights of ELM in the sense of Lyapunov stability. Experiment is conducted to validate the performance of the proposed control method. Experimental result indicates that the ELM-based adaptive neural control outperforms the classical proportional–integral–derivative (PID), fuzzy-PID and back-propagation-neural-network-based controllers in terms of tracking performance under the variation of engine load.

Fast Nonlinear Model Predictive Control on FPGA Using Particle Swarm Optimization

Nonlinear model predictive control (NMPC) requires a repeated online solution of a nonlinear optimal control problem. The computation load remains the main challenge for the real-time practical application of the NMPC technique, particularly for fast systems. This paper presents a fast NMPC algorithm implemented on a field-programmable gate array (FPGA) that employs a particle swarm optimization (PSO) algorithm to handle nonlinear optimization. The FPGA is used to explore the possibilities of parallel architecture for the substantial acceleration of NMPC. PSO is employed to achieve real-time operation due to its naturally parallel capabilities. The proposed FPGA-based NMPC-PSO controller consists of a random-number generator, a fixed-point arithmetic, a PSO solver, and a universal asynchronous receiver/transmitter communication interface. Then, this controller is applied to an engine idle speed control problem and demonstrated with an FPGA-in-the-loop testbench. The experimental results indicate that the NMPC-on-FPGA-chip strategy has good computational performance and achieves satisfactory control performance.

Direct Optimal Design for Component Swapping Modularity in Control Systems

This paper presents a new method for the design of distributed controllers that achieves component swapping modularity (CSM) in control systems. Our approach, referred to as the direct method, is based on solving a bilevel optimization problem to obtain the distributed controller gains directly. In the previously proposed three-step method, the distributed controllers were obtained by matching with a precomputed centralized controller. To illustrate our approach, we consider an engine idle speed control problem, where CSM is achieved with respect to the throttle actuator. The results indicate that the direct method can significantly improve the CSM metric compared to the three-step method. In addition, for a certain distributed control structure, the direct method enables the designer to tradeoff between desired system performance and CSM.

Observer-based robust control of time-delay uncertain systems with application to engine idle speed control

A combined controller-observer design procedure for a class of timedelay uncertain systems is proposed. First, a sufficient condition for robust asymptotical stability of the closed-loop systems is presented based on Lyapunov function theory. Next, by using matrix’s Singular Value Decomposition (SVD) and Linear Matrix Inequality (LMI) techniques, the existence condition and method of designing an observer-based feedback controller is derived. The result is obtained in terms of LMI, which make all the gain matrices can be easily obtained by Matlab’s LMI toolbox. Finally, the developed design techniques are applied to an engine idle speed control problem. The simulation results demonstrate the validity of this approach.

Combined Controller-Observer Design for Uncertain Time Delay Systems With Application to Engine Idle Speed Control

This paper sets forth two approaches for a combined controller-observer design procedure for a class of uncertain time delay systems. The first procedure uses a delay-independent LMI (linear matrix inequality) formulation that sets forth sufficient conditions for the existence of appropriate feedback and observer matrices that guarantee asymptotic stability of the system-error dynamic combination. The second procedure generates a similar delay-dependent LMI. Standard toolboxes can be used to generate solutions to the LMIs when solutions exist. The observer-control design techniques are applied to an internal combustion (IC) engine idle speed control problem; simulation results demonstrate the effectiveness of the proposed techniques.

Linear Robust Control of Identified Nonlinear Inverse Compensated SI Engine

A technique based on Horowitz’s nonlinear quantitative feedback theory is presented, in which the size of the uncertainty is reduced by cancellation of the plant nonlinearity through nonlinear inverse compensation. Linear identification of the open loop nonlinear inverse compensated plant is used to obtain an unstructured uncertainty representation, however, rather than computing QFT templates based on parametric uncertainty. An increase in achievable robust performance with any linear robust performance control design technique may then be obtained. The method is experimentally validated by application to a SISO automotive SI engine idle speed control problem using an electric dynamometer.

Linear Robust Control of Identified State-Space Non-Linear Inverse Compensated SI Engine

This paper presents a non-linear inverse compensation methodology based on a technique similar to Horowitz's non-linear quantitative feedback theory. A causal inverse is found based on an identified non-linear plant model. Linear identification of the non-linear identified inverse compensated system is carried out in order to achieve a reduction in the unstructured uncertainty representation. Subsequent robust control design results in an improvement in robust stability and robust performance over the uncompensated system. Using a parameter space linear robust control design technique, the method is applied to the automotive Spark ignition (SI) engine idle speed control problem and is experimentally validated using an electric dynamometer.

Sliding mode control of delayed systems with application to engine idle speed control

A sliding mode control (SMC) design method is proposed for a class of point delayed systems. A linear transformation is applied to convert the delayed system to delay-free system whose spectra embed all the unstable poles of the original system with given stability margin. It is proved that the delayed system is asymptotically stable with SMC based on the delay-free system. The method is applied to the internal combustion engine idle speed control problem dealing with the induction-to-power delay inherent in the plant. Both the simulation and experimental results show the efficiency of the approach and demonstrate the controller's capability of disturbance rejection.

Neural Network Based, Discrete Adaptive Sliding Mode Control for Idle Speed Regulation in IC Engines

An adaptive sliding mode control design method is proposed for discrete nonlinear systems where explicit knowledge of the system dynamics is not available. Three-layer feedforward neural networks are used as function approximators for the unknown dynamics. The control law is designed based on the outputs of the approximators, and the sliding surface is defined in terms of a stable polynomial of the system outputs. Convergence of the state trajectories into a small sliding sector is proved. The method is applied to the internal combustion (IC) engine idle speed control problem. Simulation and experimental results are provided. [S0022-0434(00)01702-0]

Application of l/sub 1/ optimal control to the engine idle speed control problem

In this paper, the engine idle speed control (ISC) problem is revisited with the l/sub 1/ optimization design methodology. A controller configuration consisting of a feedback linear quadratic Gaussian (LQG) optimal controller and a feedforward l/sub 1/ optimal controller is chosen to satisfy the design objectives. The main goal of this work is to demonstrate the application of the l/sub 1/ optimal control methodology on a standard automotive control problem and evaluate the advantages and disadvantages of the l/sub 1/ design method. Using the idle bypass valve as the only actuator, the l/sub 1/ optimal feedforward control is shown to be effective in reducing the idle speed errors at the expense of extra control energy being spent during the transient. The controller design process is described along with the simulation and experimental results on a 4.6L 2 valve V8 production engine. A method to address tradeoff issues in evaluating the performance of a feedforward control system is also discussed.