Adaptive-smith predictor for controlling an automotive electronic throttle over network

The paper presents a control strategy for an automotive electronic throttle, a device used to regulate the power produced by spark-ignition engines. Controlling the electronic throttle body is a difficult task because the throttle accounts strong nonlinearities. The difficulty increases when the control works through communication networks subject to random delay. In this paper, we revisit the Smith-predictor control, and show how to adapt it for controlling the electronic throttle body over a delay-driven network. Experiments were carried out in a laboratory, and the corresponding data indicate the benefits of our approach for applications.Peer ReviewedPostprint (published version

Linear active disturbance rejection control of waste heat recovery systems with organic Rankine cycles

In this paper, a linear active disturbance rejection controller is proposed for a waste heat recovery system using an organic Rankine cycle process, whose model is obtained by applying the system identification technique. The disturbances imposed on the waste heat recovery system are estimated through an extended linear state observer and then compensated by a linear feedback control strategy. The proposed control strategy is applied to a 100 kW waste heat recovery system to handle the power demand variations of grid and process disturbances. The effectiveness of this controller is verified via a simulation study, and the results demonstrate that the proposed strategy can provide satisfactory tracking performance and disturbance rejection

Electronic Throttle Valve Takagi-Sugeno Fuzzy Control Based on Nonlinear Unknown Input Observers

This paper deals with the synthesis of a new fuzzy controller applied to Electronic Throttle Valve (ETV) affected by an unknown input in order to enhance the rapidity and accuracy of trajectory tracking performance. Firstly, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate this nonlinear system. Secondly, a novel Nonlinear Unknown Input Observer (NUIO)-based controller is designed by the use of the concept of Parallel Distributed Compensation (PDC). Then, based on Lyapunov method, asymptotic stability conditions of the error dynamics are given by solving Linear Matrix Inequalities (LMIs). Finally, the effectiveness of the proposed control strategy in terms of tracking trajectory and in the presence of perturbations is verified in comparison with a control strategy based on Unknown Input Observers (UIO) of the ETV described by a switched system for Pulse-Width-Modulated (PWM) reference signal

Robust H2 static output feedback to control an autmomotive throttle valve

The paper presents a control strategy for an automotive electronic throttle body, a device largely used into vehicles to increase the efficiency of the combustion engines. The synthesis of the proposed controller is based on a linear matrix inequality (LMI) formulation, which allows us to deal with uncertainties on the measurements of the position of the throttle valve. The LMI approach generates a suboptimal solution for the robust H-2 static output feedback control problem, and the corresponding suboptimal control gain was evaluated in practice to control the valve position of the throttle. The usefulness of the approach has been verified not only by numerical simulations but also by real experiments taken in a laboratory prototype.Postprint (published version

Low Complexity Model Predictive Control of a Diesel Engine Airpath.

The diesel air path (DAP) system has been traditionally challenging to control due to its highly coupled nonlinear behavior and the need for constraints to be considered for driveability and emissions. An advanced control technology, model predictive control (MPC), has been viewed as a way to handle these challenges, however, current MPC strategies for the DAP are still limited due to the very limited computational resources in engine control units (ECU). A low complexity MPC controller for the DAP system is developed in this dissertation where, by "low complexity," it is meant that the MPC controller achieves tracking and constraint enforcement objectives and can be executed on a modern ECU within 200 microseconds, a computation budget set by Toyota Motor Corporation. First, an explicit MPC design is developed for the DAP. Compared to previous explicit MPC examples for the DAP, a significant reduction in computational complexity is achieved. This complexity reduction is accomplished through, first, a novel strategy of intermittent constraint enforcement. Then, through a novel strategy of gain scheduling explicit MPC, the memory usage of the controller is further reduced and closed-loop tracking performance is improved. Finally, a robust version of the MPC design is developed which is able to enforce constraints in the presence of disturbances without a significant increase in computational complexity compared to non-robust MPC. The ability of the controller to track set-points and enforce constraints is demonstrated in both simulations and experiments. A number of theoretical results pertaining to the gain scheduling strategy is also developed. Second, a nonlinear MPC (NMPC) strategy for the DAP is developed. Through various innovations, a NMPC controller for the DAP is constructed that is not necessarily any more computationally complex than linear explicit MPC and is characterized by a very streamlined process for implementation and calibration. A significant reduction in computational complexity is achieved through the novel combination of Kantorovich's method and constrained NMPC. Zero-offset steady state tracking is achieved through a novel NMPC problem formulation, rate-based NMPC. A comparison of various NMPC strategies and developments is presented illustrating how a low complexity NMPC strategy can be achieved.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120832/1/huxuli_1.pd

Adaptive-Smith Predictor for Controlling an Automotive Electronic Throttle over Network

The paper presents a control strategy for an automotive electronic throttle, a device used to regulate the power produced by spark-ignition engines. Controlling the electronic throttle body is a difficult task because the throttle accounts strong nonlinearities. The difficulty increases when the control works through communication networks subject to random delay. In this paper, we revisit the Smith-predictor control, and show how to adapt it for controlling the electronic throttle body over a delay-driven network. Experiments were carried out in a laboratory, and the corresponding data indicate the benefits of our approach for applications

Low-Cost Throttle-By-Wire-System Architecture For Two-Wheeler Vehicles

This paper investigates the performance of a low-cost Throttle-by-Wire-System (TbWS) for two-wheeler applications. Its consisting of an AMR throttle position sensor and a position controlled stepper motor driven throttle valve actuator. The decentralized throttle position sensor is operating contactless and acquires redundant data. Throttle valve actuation is realized through a position controlled stepper motor, sensing its position feedback by Hall effect. Using a PI-controller the stepper motors position is precisely set. Sensor and actuator units are transceiving data by a CAN bus. Furthermore, failsafe functions, plausibility checks, calibration algorithms and energy saving modes have been implemented. Both modules have been evaluated within a Hardware-in-the-Loop test environment in terms of reliability and measurement/positioning performance before the TbWS was integrated in a Peugeot Kisbee 50 4T (Euro 5/injected). Finally, the sensor unit comes with a measurement deviation of less then 0.16% whereas the actuator unit can approach throttle valve positions with a deviation of less then 0.37%. The actuators settling time does not exceed 0.13s while stable, step-loss free and noiseless operation

An Innovative Feedback Controls Design Approach for Aero Engines

The paper describes a feedback controls design approach for a generic regional jet turbofan engine, which can be adapted to aero engines in general. To demonstrate this approach, linear models for control design are generated at different operating conditions from a full envelope nonlinear simulation created with the NASA Glenn Research Center-developed Toolbox for the Modeling and Analysis of Thermodynamic Systems. The primary objective is to design a single feedback controller that achieves good performance, without the need of developing scheduled control designs to cover the engine operating envelope. An additional objective is to progressively design more robust controllers that can perform under large variations in plant dynamics to also cover control for engine limits and potentially for some off nominal or even damaged conditions

Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR

The efficiency of modern downsized SI engines has been significantly improved using cooled Low-Pressure Exhaust Gas Recirculation, Turbocharging and Variable Valve Timing actuation. Control of these sub-systems is challenging due to their inter-dependence and the increased number of actuators associated with engine control. Much research has been done on developing algorithms which improve the transient turbocharged engine response without affecting fuel-economy. With the addition of newer technologies like external cooled EGR the control complexity has increased exponentially. This research proposes a methodology to evaluate the ability of a Model Predictive Controller to coordinate engine and air-path actuators simultaneously. A semi-physical engine model has been developed and analyzed for non-linearity. The computational burden of implementing this control law has been addressed by utilizing a semi-physical engine system model and basic analytical differentiation. The resulting linearization process requires less than 10% of the time required for widely used numerical linearization approach. Based on this approach a Nonlinear MPC-Quadratic Program has been formulated and solved with preliminary validation applied to a 1D Engine model followed by implementation on an experimental rapid prototyping control system. The MPC based control demonstrates the ability to co-ordinate different engine and air-path actuators simultaneously for torque-tracking with minimal constraint violation. Avenues for further improvement have been identified and discussed