Sampling Control Design And Batch Optimization For Industrial Processes With Time Delay

With the rapid development of digital control system, computer control systems based on sampled data have been increasingly applied to industrial processes. In this thesis, discrete-time domain two-degree-of-freedom (2DOF) control design methods are proposed for stable, integrating and unstable processes with time delay, respectively, based on low-order process models with time delay that are mostly used in the engineering applications. Using a 2DOF control structure recently developed in the literature, both the set-point tracking controller and the closed-loop controller for load disturbance rejection are analytically designed, which can be tuned independently to optimize the set-point tracking response and load disturbance response, respectively. The set-point tracking controller is designed in terms of the H2 optimal control performance index, and the load disturbance rejection controller is inversely derived by proposing the desired closed-loop complementary sensitivity function. An important merit of the proposed control scheme is that the performance specification of the set-point tracking response can be quantitatively tuned by the single adjustable parameter in the set-point tracking controller. For stable and integrating processes, the disturbance rejection controller derived from the desired closed-loop transfer function for load disturbance rejection can be physically realized. However, for an unstable process, internal stability of the closed-loop system cannot be guaranteed due to that there exists implicitly unstable zero-pole cancellation in the desired disturbance rejection controller. A rational Pade approximation is adopted in the thesis to approximate the ideally desired disturbance rejection controller for implementation, so as to facilitate practical application. Concerning the designed closed-loop system stability, sufficient and necessary conditions for holding robust stability of the closed-loop control system are established in terms of the Small Gain Theorem. Graphical and numerical tuning guidelines are given for tuning the single adjustable parameter in the disturbance rejection controller. Illustrative examples from the recent literature are used to demonstrate the effectiveness and merits of the proposed discrete time domain 2DOF controller design algorithms.Based on the above 2DOF control scheme, an iterative learning control (ILC) method is proposed for batch processes with time delay. The key idea of the proposed control method is to use the historical batch operation data to improve the control performance in the current cycle. For this purpose, a'memory'is introduced into the above 2DOF control scheme, which is used to record the measured process output, model output, and the control signal in the historical and current cycles, and provide those of the previous cycle for control the current cycle, therefore facilitating ILC and performance optimization. In practical applications, the initial batch should adopt the above 2DOF control scheme in order to guarantee robust stability of the closed-loop system, and then from the next batch on, an ILC law is implemented to gradually realize perfect tracking of the set-point trajectory. Besides, a filter is introduced in the proposed ILC algorithm to ensure the convergence of iteration error, together with a sufficient condition for the convergence. Finally, an illustrative example is given to demonstrate the feasibility and effectiveness.