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In process industries, cascade control is comprehensively used for disturbance attenuation. This manuscript presents the control of the non-minimum phase (NMP) system with dead time via a series cascade scheme. An improved fractional-filter-based control scheme encompassing inverse and dead time compensators with analytical tuning is proposed. The design hinges on an enhanced Bode's ideal transfer function, which incorporates delay and NMP zero to deal with the system's NMP and dead time. Particle swarm optimization (PSO) is utilized to obtain the optimal assessment of fractional filter-based controller settings by minimizing an objective function. Two benchmark problems are presented to test the efficacy of the recommended controller. The Riemann surface and sensitivity examination are used to realize the stability and robustness of the feedback design. Numerical simulations exhibit the superiority of the suggested controller for closed-loop results. [ABSTRACT FROM AUTHOR]

This paper proposes a cascade series control structure and design for two series processes represented by first-order plus dead-time FOPDT models. The proposed controller uses two series predictors, one for each process, and can deal with stable, unstable, or integrative processes. The design follows similar principles of the simplified filtered Smith Predictor (SFSP) for a single-loop dead-time system. Initially, the primary controller, composed of a set-point static gain and two feedback controllers, is tuned to achieve the desired set-point tracking. Then, the predictor filters are tuned to ensure stability, robustness, and disturbance attenuation. Different from standard cascaded SFSP, one of the feedback controllers, instead of only a static gain, includes a finite time integral. The main advantage of this approach is that disturbances generated in the primary or secondary process can be handled independently by the predictor filters, simplifying the tuning procedure and enhancing the overall control performance. Additionally, for the nominal case, the proposed cascaded controller allows obtaining an ideal set-point tracking and disturbance rejection. After the dead-time effect, the proposed cascade controller achieves the set point exponentially and rejects exponentially step-like disturbances where the user defines the time constants of the exponentials. Simulation results demonstrate the advantages of the proposed controller compared to other recently published approaches, mainly in the inner loop disturbance rejection, which is precisely what is expected from a series cascade controller. • A new time-delay compensator applied to cascade series delayed process is proposed. • The proposed controller can be applied to cascaded open-loop stable, unstable, and integrative processes with time delay. • One can independently tune the disturbance attenuation of the primary and secondary processes without affecting the entire system. • The tuning rules are as simple as in a traditional filtered Smith predictor. • The proposed controller allows the achievement of the ideal setpoint tracking and step-like disturbance rejection. [ABSTRACT FROM AUTHOR]

In industrial unstable processes, disturbance rejection is more challenging task than setpoint tracking. So, cascade control structure is widely used in many chemical processes to reject disturbances. In this work, an advanced dead-time compensator-based series cascade control structure (SCCS) is suggested for unstable processes. The suggested SCCS has three controllers (named as primary, secondary and stabilizing controllers). Both primary and secondary controllers are designed using fractional order-based internal model control (IMC) approach. The stabilizing proportional–derivative controller is designed using maximum sensitivity considerations and Routh–Hurwitz stability criteria. Optimal values of the closed-loop time constants and fractional orders of IMC filters are obtained using constrained artificial bee colony (ABC) algorithm. This ABC algorithm uses a multi-objective function involving minimization of integral of absolute error, integral of time weighted absolute error and integral of squared error. Simulation studies are conducted using some benchmark plant models used in literature for illustrating the advantages of the proposed strategy compared to the state of the art. Moreover, robust stability of the proposed design is analysed and quantitative performance measures are also computed. [ABSTRACT FROM AUTHOR]