This study formulated an iterative learning-based predictive control strategy for asynchronous switching of multiphase batch processes with complex characteristics in the framework of a two-dimensional (2-D) system. First, we constructed a Fornasini–Marchesini comprehensive feedback error model, considering the state deviation and output error. Using this model, we developed a switching model considering the match and mismatch cases. Furthermore, an iterative learning-based predictive control mechanism was designed for asynchronous switching with a greater freedom of adjustment and fast learning ability in the batch direction. Second, the asymptotic and exponential stability were discussed based on the related methods and theories, and the system stability conditions were expressed in the form of linear matrix inequality (LMI). Following an online mechanism to determine the LMI conditions, we derived the real-time optimal gains of the control law, the maximum dwell period (Max-DT) for the mismatch case, and the minimum dwell period for the match case. The switching signal was transmitted in advance according to the Max-DT to ensure the stability of the system during switching. Finally, the effectiveness of the proposed method was confirmed by utilizing the injection molding process.

When an oil pipeline has small leaks, the change of the sound velocity of an ultrasonic signal cannot be easily detected. Based on the method of characteristics (MOC) theory, the leakage occurrence mechanism of a pipeline and the propagation mechanism of the sound velocity of the ultrasonic signal along the pipeline were studied. Additionally, the computational models of generating the sound velocity of the ultrasonic signal induced by pipeline leakage and calculating the propagation attenuation of the ultrasonic wave along the pipeline were established. A small leak localization method for pipelines based on information fusion is proposed, which is a combination of the sound velocity of the ultrasonic and flow rate signals. First, the fusion signals are extracted from the signal inflection point using a modified cross-correlation to determine the time difference of the fusion signal changes at the ends of the pipeline; then, the leak position is calculated based on the information of the pipeline length and the negative pressure wave propagation velocity. Since the change of the information fusion signal induced by a small leak is larger than the change of the sound velocity of the ultrasonic signal and the change of pressure signal, the proposed method can be used to locate a small leak in a pipeline. By analyzing the acquired data of a small leak in an experimental pipeline, the results show that the proposed method can quickly and effectively locate small leaks.

Asynchronous switching between the controller and the active subsystems in multiphase batch processes may cause the systems to be unstable around the switching instants. In view of this, an average dwell-time method-based iterative learning control (ILC) scheme is proposed in this paper. First, the multiphase process is represented as an equivalent closed-loop two-dimensional (2-D) switched system composed of stable and unstable subsystems, based on which new relevant concepts on the stability of the switched system are given. Second, using an average dwell-time method, the ILC law is designed to guarantee the system exponentially stable. Minimum running time for the stable subsystems and maximum running time for the unstable ones are obtained. Lastly, depending on the maximum time for the unstable subsystems, the idea of putting the controller switching step forward is proposed. In this way, the asynchronous switching is removed such that the unstable subsystem can be avoided. The case study on an injection molding process demonstrates the effectiveness and superiority of the proposed method in comparison with the existing 2D-MPC and one-dimensional traditional control methods.

This article considers a multiple leaks' localization method in fluid pipelines based on the change in the sound velocity of an ultrasonic signal. First, the sound velocity of an ultrasonic signal is denoised by wavelet packet analysis (WPA). Second, the mathematical relationship between the position of a leak and the change in the sound velocity of an ultrasonic signal at the ends of a pipeline is established based on the motion equation and the continuity equation in the transient flow equation of a pipeline. As a consequence, the localization of the leakage position of the proposed method depends only on the change in the sound velocity of the ultrasonic signal at the ends of the pipeline rather than the time difference in a negative pressure wave arriving at the ends of the pipeline. Finally, the change in the sound velocity of the ultrasonic signal is used and it is proven to be efficient to locate the actual leak number. The simulation results show that the proposed method can locate multiple leak positions in a pipeline.

A robust fuzzy predictive control (RFPC) based on Takagi-Sugeno fuzzy model is proposed for systems with uncertainties, time-varying delays, unknown disturbances as well as strong nonlinearity. Firstly, T-S fuzzy model is built by a number of linear sub-models and nonlinear membership functions. Then, by introducing the output tracking error to this fuzzy model, the novel augmented state space model is presented to independently regulate the process state variables and output tracking error. The control law of proposed RFPC is further designed based on this extended model, which can guarantee the process state to be fast convergent and make the process output track the set-point well. Moreover, it increases the ability of adjustment for the proposed controller. Utilizing Lyapunov-Krasovskii method, optimized control theory, and H-infinity control method, the stable sufficient conditions are given for the designed control law to make sure the asymptotical stability of the nonlinear uncertain system with time-varying delay and unknown disturbances. The gains of the controller can be obtained by solving these stabilized conditions in form of linear matrix inequality constraints. At last, a case study of continuous stirred tank reactor manifests that the proposed RFPC method can bear the larger range of time delay, overcome the uncertainties and unknown disturbances well and have better tracking performance.