Disturbance-observer-based finite time sliding mode controller with unmatched uncertainties utilizing improved cubature Kalman filter

Abstract

Complex reactions are difficult to control as the reactants not only produce desired product but may also further undergo unwanted reactions or the original reactants may degrade through alternate paths. This can be improved by selecting proper measurement and control. In this paper, a robust augmented derivative-free Kalman filter (augmented cubature Kalman filter, ACKF) is propounded for the continuous stirred tank reactor (CSTR) carrying out Van-de-Vusse type complex reactions where the intermediate is the desired product in the midst of consecutive and parallel reactions. Non-isothermal CSTR shows strong non-linearity with inherent challenges as the reaction kinetics depends on process temperature through Arrhenius laws and accompanies non-ideal flow behaviour and unmeasurable disturbances. First, the process exhibits inverse or non-minimum phase behaviour. Second, to control product temperature and concentration, a finite time sliding mode controller (FSMC) is suggested which effectively tracks servo response to the desired set point. Third, a disturbance filter has been proposed in association with FSMC, which constructively eliminates the input disturbances. Realistic simulations for servo-regulatory compliance, elimination of measurement noise, impact on large perturbation, and parametric uncertainty with a state-of-the-art simulator ensure the efficacy of the proposed controller. The results are analysed further with a derivative-free FSMC control approach, considering various performance indices (root mean square error (RMSE), total variation (TV), mean square deviation (MSD)) to assess the goodness of the newly developed control strategy. It has been found that improved control law (improved augmented cubature Kalman filter (IACKF)-FSMC) yields better RMSE (7.2645e–05) than ACKF-FSMC (7.5814e–05).

Parametric Identification of a Countercurrent Aqueous Hydrolysis Process for the Production of Glycerine under Higher Pressure and Temperature

“…5. It is worth noting that the process uncertainty takes place on the regulatory level and, thus, the MSD table was addressed for the disturbance‐elimination phase 40. From the results and their discussion, it was noticed that the MUKF‐PI control scheme promises lesser ISE and MSD values compared to the CA‐PI law.…”

“…5. It is worth noting that the process uncertainty takes place on the regulatory level and, thus, the MSD table was addressed for the disturbance-elimination phase [40].…”

Predictive control scheme by integrating event-triggered mechanism and disturbance observer under actuator failure and sensor fault

“…A set of 2n cubature points, @(i + jji, l), are chosen symmetrically about xm (i + jji) as given below 10,48 @(i + jji) = S(i + jji)c l + xm (i + jji); l = 1, :::, n; j = 0, 1, :::…”

“… S is a lower triangular matrix used for decomposing P . A set of 2 n cubature points, ℵ ( i + j | i, l ) , are chosen symmetrically about x ^ m ( i + j | i ) as given below 10, 48…”

“…A ˚stro¨m et al 8 formulated a mathematical model and used it for controlling liquid level for a quadruple tank system with similar cylindrical storage geometry. Several researchers have investigated different control strategies on interacting tank level processes such as particle swarm optimization-based predictive control method utilizing TS-fuzzy modelling approach, 9 chattering-free sliding mode control scheme on the experimental rigs, 10 the model-based-control system using internal model control scheme implemented on real-time application, 4 adaptive fuzzy control strategy using recursive least square algorithm, 1 fuzzy fractional order Proportional-Integral-Derivative (PID) controller 11 and many others. From the extensive literature study, it has been observed that the variants of conventional/advanced control problems demonstrated on the interacting tank systems are quite effective (from a performance/safety point of view like servo-regulatory compliance, assessing robustness, hazard assessment and evaluation etc.)…”