Xun Gong

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.

Automotive Control: the State of the Art and Perspective

Abstract Automotive control technology plays a significant role for the sustainable development of auto-industry. Under gradually fierce circumstance of competition around the world, how to strengthen our capacity of independent research and development of auto-control technology through the innovation of theory and method presents a grand challenge of our time. This paper introduces the state of the art of automotive control focusing on the power-train control, active safety control and new energy vehicle control, then summarizes their common problems and finally puts forward a series of perspective for the future researches.

Engine Idle Speed Control Using Nonlinear Model Predictive Control

Abstract In this paper, a nonlinear model predictive controller is presented for idle speed control (ISC) problem of spark ignition (SI) engine. The objective is to maintain the engine speed at a prescribed set-point through actuating a electronic throttle, and minimize the effects of load torque disturbances and model uncertainties. The nonlinear programming (NLP) problem formed by nonlinear model predictive control (NMPC) is solved by using particle swarm optimization (PSO) algorithm. Simulation results show that the designed nonlinear model predictive controller can achieve satisfactory performance for ISC.

Idle speed controller design for SI engine based on ADRC

In this paper, an idle speed controller is designed in the framework of active disturbance rejection control (ADRC) for spark ignition (SI) engine. The SI engine model based on the mean value model is proposed. As the system can be considered as a cascade system, the developed controller incorporates a nonlinear state error feedback law (NLSEF) which handles the speed tracking and an ADRC controller based on the Extended State Observer (ESO) to deal with the unknown dynamics and disturbance of the engine system.The robustness stability of the controller is analyzed. Simulation results are provided to demonstrate the advantage and effectiveness of the controller.

Active disturbance rejection control of common rail pressure for Gasoline Direct Injection engine

The rail pressure control in Gasoline Direct Injection (GDI) engines is considered as one of key issues for precise control of fuel injection. This paper presents a rail pressure controller based on the framework of active disturbance rejection control (ADRC). The detailed nonlinear model of the fuel injection system for GDI engine is carried out. Suitable model simplification is introduced for the controller design. According to the complex nonlinear system which contains internal uncertainties and external disturbance, a nonlinear state error feedback control and an extended state observer are applied to deal with the pressure tracking problem. Simulation results are provided to demonstrate the effectiveness of the proposed controller.

A nonlinear feedforward-feedback controller design for electronic throttle based on flatness

Electronic throttle is a dc-motor-driven valve that plays an important role to modulate airflow into the combustion system of an engine. However, it is difficult to design an effective controller to deal well with the inherent nonlinearity of the plant, such as the strong nonlinear effects of friction and return spring. In this paper, taking these factors into consideration, a controller is proposed: a nonlinear feedforward control is carried out in consideration of the system nonlinearities based on flatness, a linear feedback control is given to handle the uncertainties and disturbances. The simulation results verify the effectiveness of the proposed controller and its strong robustness to model uncertainties. Finally, the real time performance of the designed controller is tested by the Hardware in the Loop (HiL) platform based on xPC-Target. For all cases, the controller works rather well and meets the performance specifications.

Modeling and control of the air path system in turbocharged gasoline engine

Turbocharging technology has been widely used in automotive products for improving the power of the vehicle effectively. In this paper, a physics-map mixed air path model of turbo-gasoline engine is proposed. The accuracy of the proposed model is validated by the engine dynamics simulation software enDYNA. Then, an air path control system which contains torque based throttle control and intake manifold pressure control is deduced to coordinate the throttle and wastegate for satisfying the torque demand and the limitation of intake manifold pressure. And a control strategy is proposed in order to fully utilize turbocharger. Finally, the simulation results show the effectiveness of the control system.

A new procedure to design nonlinear controller for rail pressure control of GDI engines

This paper presents a novel approach for rail pressure control of GDI engines. The control objective is to make the rail pressure track the given reference. Different from the existing nonlinear controller design methods, the proposed procedure can be divided into 3 steps: 1) A steady state control is deduced, playing the similar role of the map-based control strategy that widely used in automotive control; 2) A feedforward control is derived based on the reference dynamics; 3) A feedback control is also considered which can be rearranged into a state-dependent PID. The proposed method provides a concise derivation procedure and the structure is comparable to those widely used in modern automotive control. Finally, simulation results in the environment of commercial software AMESim with actual system parameters show the efficiency of the proposed approach.

Idle speed control for SI engine using triple-step nonlinear method

Idle speed control is considered as one of the most important issues in engine control. In this paper, we develop a triple-step nonlinear method to solve the idle speed control problem based on a data-physics mixed engine model. Concerning about the implementation issue, the map-related derivative items in the controller deduction are elaborately pretreated in the modeling step. Then, the controller design procedure is introduced step by step and ultimately can be divided as a steady state control, a reference dynamic based feed-forward control and a feedback control. The gains of controller are state-dependent and parameter-varying. The structure of the proposed nonlinear controller is concise and is comparable to those widely used in modern automotive control. Simulation results show the effectiveness of the designed controller.

Modelling and control of urea-SCR systems through the triple-step non-linear method in consideration of time-varying parameters and reference dynamics

Owing to the dynamic operation mode of urea selective catalytic reduction (urea-SCR) systems, advanced control strategies are required to improve urea dosing control. A new control-oriented model presentation of urea-SCR systems is developed in this study. A novel controller based on the triple-step non-linear method is designed. The controller drives the non-linear system with time-varying parameters to track the variable ammonia coverage ratio. Unlike the existing triple-step non-linear method, the third design procedure in the proposed method is adjusted as an H ∞ error feedback control. The proposed method provides a concise design process so that derivation of the control law can be simple and straightforward. The robustness of the controller against measurement noises and system uncertainties is analysed. A transient simulation is conducted to evaluate the effectiveness of the proposed control strategy.