In contrast to the calibration of an engine volumetric efficiency map (or lookup tables) from steady-state data, a method for the identification of the engine volumetric efficiency map using transient condition data is developed in this article, which can reduce the time and cost of engine map calibration. To expediently identify the map parameters, the mathematical description of the volumetric efficiency for a spark ignition (SI) gasoline engine is approximated in terms of a piecewise bilinear interpolation model with unknown map parameters, which can be rewritten as a dot product between a regression vector and a parameter vector using a membership function. With the combination of a map regression model and an SI gasoline engine air path dynamic model, a finite-time adaptive observer is designed to estimate the constant map parameters, for which the parameter estimation error information is explicitly derived. To guarantee the convergence of the identification for all map parameters, a trajectory scheme of the transient condition data from the map input that passes through all of the interpolation regions is introduced. The performance of the proposed algorithm is validated against transient condition data generated by the engine simulation software enDYNA provided by Tesis. It is shown that the volumetric efficiency map of an SI gasoline engine simulated with enDYNA is approximated acceptably by the proposed method.

This paper develops a fractional‐order adaptive fuzzy backstepping control scheme for incommensurate fractional‐order nonlinear uncertain systems with external disturbances and input saturation. Based on backstepping algorithm, the fuzzy logic system is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the fractional‐order parameters update laws for fuzzy logic system, unknown parameters, and the external disturbances are proposed. With the aids of the frequency distributed model of fractional integrator for the fractional‐order systems in the procedure of controller design, the stability of the closed‐loop system is established. To verify the effectiveness and robustness of the proposed controller, two simulation examples are demonstrated at last.

This paper develops a fractional order adaptive fuzzy backstepping control scheme for an incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems with external disturbance and input saturation. Combined with the adaptive and backstepping technique, the fuzzy logic system is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the incommensurate fractional order parameters update laws for fuzzy logic system, unknown parameters as well as the external disturbances are proposed in the controller to compensate the unknown nonlinearities, unknown parameters and disturbances. With the aids of the frequency distributed model of fractional integrator for the fractional order systems in the procedure of controller design, the stability of the closed loop system is established. At last, two simulation examples are demonstrated to verify the robustness and effectiveness of the proposed controller.

An adaptive backstepping control scheme for a class of incommensurate fractional order uncertain nonlinear multiple‐input multiple‐output (MIMO) systems subjected to constraints is discussed in this paper, which ensures the convergence of tracking errors even with dead‐zone and saturation nonlinearities in the controller input. Combined with backstepping and adaptive technique, the unknown nonlinear uncertainties are approximated by the radial basis function neural network (RBF NN) in each step of the backstepping procedure. Frequency distributed model of a fractional integrator and Lyapunov stability theory are used for ensuring asymptotic stability of the overall closed‐loop system under input dead‐zone and saturation. Moreover, the parameter update laws with incommensurate fractional order are used in the controller to compensate unknown nonlinearities. Two simulation results are presented at the end to ensure the efficacy of the proposed scheme.

Locators are important parts for clamping and locating auto-bodies in the jigs of an automobile welding line. Their diverse shapes and number lead to the complexity of the toolpath planning for them. Thus the efficiency of the numeric control(NC) for them is important to the productivity of automobile welding lines. An automatic NC programming system for locators has been developed. Manufacturing features are automatically extracted from the design features of locators and the assembly relationships between them and other parts. Toolpaths are generated automatically using knowledge-based approach. NC code files transmission, task assignment and the monitor of machine states in workshop are achieved through the distributed numeric control(DNC) system. The key technologies of the system are studied in detail. This system has been put into the enterprise's production.