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Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

A diesel piloted natural gas engine's performance varies depending on operating conditions and has performed best under medium to high loads. It can often equal or better the fuel conversion efficiency of a diesel-only engine in this operating range. This paper presents a study performed on a multi-cylinder Cummins ISB 6.7L diesel engine converted to run stoichiometric natural gas/diesel micro-pilot combustion with a maximum diesel contribution of 10%. This study systematically quantifies and ranks the sensitivity of control factors on combustion and performance while operating at medium loads. The effects of combustion control parameters, including the pilot start of injection, pilot injection pressure, pilot injection quantity, exhaust gas recirculation, and global equivalence ratio, were tested using a design of experiments orthogonal matrix approach.