Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/2/rnc5188.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/1/rnc5188_am.pd

Transient Load-Speed Control in Multi-Cylinder Recompression HCCI Engines

Strict proposed fuel economy and emissions standards for automotive internal combustion engines have motivated the study of advanced low-temperature combustion modes that promise higher combustion efficiencies with low engine-out emissions. This work presents modeling and control results for one such combustion mode -- recompression homogeneous charge compression ignition (HCCI) combustion. Regulating desired charge properties in recompression HCCI involves the retention of a large amount of the residual charge between engine cycles, thus introducing significant inter-cycle feedback in the system. This work considers a baseline controller from literature, and proposes two improved model-based control strategies. The controllers use exhaust valve timing and fuel injection timings to track combustion phasings during transitions in the HCCI region of the multi-cylinder engine load-speed operating map. Fast and stable control of these transitions is demonstrated, which maximizes the length of stay in the HCCI region, and hence the efficiency benefit of advanced combustion. The baseline controller, which is a feedback-feedforward controller adapted from literature, is tuned using a low-order, discrete-time, control-oriented model that describes the stable, high efficiency HCCI region. The first improved control strategy augments the baseline controller with a reference or fuel governor that modifies transient fuel mass commands during large load transitions, when the possibility of future actuator constraint violations exists. This approach is shown in experiments to improve the combustion phasing and load responses, as well as prevent engine misfires. Issues with high cyclic variability during late phasing and low load conditions, and their impact on transient performance, are discussed. These issues are physically explained through recompression heat release caused due to unburned and recycled fuel. The control-oriented model is augmented with recompression heat release to predict the onset of the oscillatory, high variability region. The second improved control strategy uses this physical understanding to improve combustion phasing tracking performance. Transitions tested on a multicylinder HCCI engine include load transitions at fixed engine speeds, engine speed ramps at fixed load, simultaneous load and speed transitions, and select FTP75 drive-cycle transitions with high load slew rates. This improved model-based control strategy is proposed as a solution for the HCCI transient control problem.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107072/1/sjade_1.pd

Computationally efficient robust model predictive control strategies for linear constrained systems

This thesis deals with control problem of designing low computationally demanding robust model predictive controllers (MPC) for constrained systems subject to states/input limitations and bounded disturbances. In particular, the proposed solutions are based on a dual-mode control paradigm known as Set-Theoretic MPC (ST-MPC). This control schemes are particularly appealing for their capability of reducing the typical computation burden of robust MPC controllers. The latter is obtained by moving most of the required computations into an off-line phase, while leaving a simple and real-time affordable computational algorithm in the on-line phase. In this work, such a paradigm has been properly extended to deal with regulation and tracking problems appearing in two different control applications, namely transient stability regulation in smart grid and reference tracking in multi autonomous vehicles. In the transient stability control problem, we consider an operative scenario where a physical fault or a cyber-attack produces an impulsive state perturbation, and a controller must be designed to robustly recover, in a finite-time, transient stability despite initial perturbation and uncertainties. In such scenario, first we have used the standard feedback linearizion technicalities to linearize the smart grid model, then, we have applied a set-theoretic MPC scheme to robustly regulate the state trajectory towards the transient stability region. Moreover, to validate the proposed theory, a simulation campaign has been performed to contrast the proposed solution with a state-of-the-art competitor. Simulation results has shown that the proposed strategy outperforms the competitor scheme both in terms of settling time and robustness. In the multi-vehicle control problem, we exploit set-theoretic arguments to solve the reference tracking problem when the vehicles have different dynamics and/or constraints and/or disturbance, and each vehicle must follow uncoordinated reference trajectories. More in specific, we propose a novel control architecture where robust collision-free reference tracking is ensured by jointly using the set-theoretic control scheme and graph theory. To better clarify the potential and effectiveness of the proposed architecture, a simulation example involving 5 heterogeneous vehicles has been conducted

Constraint-Aware and Efficiency-Aware Control of Air-Path in Fuel Cell Vehicles

Fuel cell technology offers the potential for clean, efficient, robust energy productionfor both stationary and mobile applications. But without fast and robust control systems, fuel cells cannot hope to maintain real-life efficiencies near enough to their theoretical potential. This work studies control and constraint management techniques to regulate a nonlinear multivariable air-path system for a proton exchange membrane fuel cell (PEMFC). The control objectives are to avoid oxygen starvation, run at the maximum net efficiency, achieve fast tracking of air flow and pressure set-points, and be easy to calibrate. To operate at maximum efficiency, a set-point map is generated for air pressure at the cathode inlet. Considering that the conventional PEMFC system cannot independently control the inlet pressure using only the compressor motor, a new multivariable analysis and control scheme is formulated by considering an electronic throttle body (ETB) valve downstream of the cathode as a new degree of freedom in the control problem. Based on this new configuration of the fuel cell model, an internal model control (IMC) controller is designed with intuitive tuning parameters to simultaneously control airflow and pressure, and achieves a fast and smooth response despite strongly coupled plant dynamics. Further, a reference governor (RG) using a computationally tractable linear prediction model is included with IMC-based Multi-Input Multi-Output (MIMO) controller to satisfy the constraint on oxygen level. Compared with a Single-Input Single-Output (SISO) air-flow control approach, the proposed MIMO control approach demonstrated up to 7.36 percent lower hydrogen fuel consumption

Robust control strategies for hybrid solid oxide fuel cell systems

Solid Oxide Fuel Cell (SOFC) systems are electrochemical energy conversion devices characterized by the use of solid oxide as the electrolyte. They operate at high temperatures (between 800± ¡ 1000±C). Mitigating fuel starvation and improving load-following capability of SOFCs are conflicting control objectives. In this thesis, this issue is addressed using a hybrid SOFC ultra-capacitor configuration. The fuel cell is controlled by incorporating a steady-state property of fuel utilization into an input-shaping framework. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H-infinity robust control. Both strategies additionally control the state of charge (SOC) of the ultra-capacitor that provides transient power compensation. A hardware-in-the-loop test-stand is developed where the proposed control strategies are verified. An investigation to improve the hybrid fuel cell system by incorporating a lithium-ion battery as an additional power source is conducted. Combining both battery and ultra-capacitor with a fuel cell is potentially a winning combination especially for high power applications. A novel SOC estimation method for lithium-ion battery is investigated. Based on the combined ultra-capacitor battery hybrid system, a lyapunov-Based nonlinear control strategy is designed

Advanced Computational-Effective Control and Observation Schemes for Constrained Nonlinear Systems

Constraints are one of the most common challenges that must be faced in control systems design. The sources of constraints in engineering applications are several, ranging from actuator saturations to safety restrictions, from imposed operating conditions to trajectory limitations. Their presence cannot be avoided, and their importance grows even more in high performance or hazardous applications. As a consequence, a common strategy to mitigate their negative effect is to oversize the components. This conservative choice could be largely avoided if the controller was designed taking all limitations into account. Similarly, neglecting the constraints in system estimation often leads to suboptimal solutions, which in turn may negatively affect the control effectiveness. Therefore, with the idea of taking a step further towards reliable and sustainable engineering solutions, based on more conscious use of the plants' dynamics, we decide to address in this thesis two fundamental challenges related to constrained control and observation. In the first part of this work, we consider the control of uncertain nonlinear systems with input and state constraints, for which a general approach remains elusive. In this context, we propose a novel closed-form solution based on Explicit Reference Governors and Barrier Lyapunov Functions. Notably, it is shown that adaptive strategies can be embedded in the constrained controller design, thus handling parametric uncertainties that often hinder the resulting performance of constraint-aware techniques. The second part of the thesis deals with the global observation of dynamical systems subject to topological constraints, such as those evolving on Lie groups or homogeneous spaces. Here, general observability analysis tools are overviewed, and the problem of sensorless control of permanent magnets electrical machines is presented as a case of study. Through simulation and experimental results, we demonstrate that the proposed formalism leads to high control performance and simple implementation in embedded digital controllers

Advances in PID Control

Since the foundation and up to the current state-of-the-art in control engineering, the problems of PID control steadily attract great attention of numerous researchers and remain inexhaustible source of new ideas for process of control system design and industrial applications. PID control effectiveness is usually caused by the nature of dynamical processes, conditioned that the majority of the industrial dynamical processes are well described by simple dynamic model of the first or second order. The efficacy of PID controllers vastly falls in case of complicated dynamics, nonlinearities, and varying parameters of the plant. This gives a pulse to further researches in the field of PID control. Consequently, the problems of advanced PID control system design methodologies, rules of adaptive PID control, self-tuning procedures, and particularly robustness and transient performance for nonlinear systems, still remain as the areas of the lively interests for many scientists and researchers at the present time. The recent research results presented in this book provide new ideas for improved performance of PID control applications

Observer-based event-triggered and set-theoretic neuro-adaptive controls for constrained uncertain systems

In this study, several new observer-based event-triggered and set-theoretic control schemes are presented to advance the state of the art in neuro-adaptive controls. In the first part, six new event-triggered neuro-adaptive control (ETNAC) schemes are presented for uncertain linear systems. These comprehensive designs offer flexibility to choose a design depending upon system performance requirements. Stability proofs for each scheme are presented and their performance is analyzed using benchmark examples. In the second part, the scope of the ETNAC is extended to uncertain nonlinear systems. It is applied to a case of precision formation flight of the microsatellites at the Sun-Earth/Moon L1 libration point. This dynamic system is selected to evaluate the performance of the ETNAC techniques in a setting that is highly nonlinear and chaotic in nature. Moreover, factors like restricted controls, response to uncertainties and jittering makes the controller design even trickier for maintaining a tight formation precision. Lyapunov function-based stability analysis and numerical results are presented. Note that most real-world systems involve constraints due to hardware limitations, disturbances, uncertainties, nonlinearities, and cannot always be efficiently controlled by using linearized models. To address all these issues simultaneously, a barrier Lyapunov function-based control architecture called the segregated prescribed performance guaranteeing neuro-adaptive control is developed and tested for the constrained uncertain nonlinear systems, in the third part. It guarantees strict performance that can be independently prescribed for each individual state and/or error signal of the given system. Furthermore, the proposed technique can identify unknown dynamics/uncertainties online and provides a way to regulate the control input --Abstract, page iv

Automotive Powertrain Control — A Survey

This paper surveys recent and historical publications on automotive powertrain control. Control-oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72023/1/j.1934-6093.2006.tb00275.x.pd