Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal.The desulphurization control system,however,is subjected to complex reaction mechanisms and severe disturbances,which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness.To address these challenges,a new robust control scheme based on uncertainty and disturbance estimator(UDE)and model predictive control(MPC)is proposed in this paper.The UDE is used to estimate and dynamically compensate acting disturbances,whereas MPC is deployed for optimal feedback regulation of the resultant dynamics.By viewing the system nonlinearities and unknown dynamics as disturbances,the proposed control framework allows to locally treat the considered nonlinear plant as a linear one.The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small,even in the presence of unmodeled dynamics.In the conducted comparison study,the introduced control scheme outperforms both the standard MPC and PID(proportional-integral-derivative)control strategies in terms of transient performance and robustness.Furthermore,the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error.

ADRC in output and error form:connection,equivalence,performance

In this work,we investigate two specific linear ADRC structures,namely output-and error-based.The former is considered a“standard”version of ADRC,a title obtained primarily thanks to its simplicity and effectiveness,which have spurred its adoption across multiple industries.The latter is found to be especially appealing to practitioners as its feedback error-driven structure bares similarities to conventional control solutions,like PI and PID.In this paper,we describe newly found connections between the two considered ADRC structures,which allowed us to formally establish conditions for their equivalence.Furthermore,the conducted comprehensive performance comparison between output-and error-based ADRCs has facilitated the identification of specific modules within them,which can now be conveniently used as building blocks,thus aiding the control designers in customizing ADRC-based solutions and making them most suitable for their applications.

On a novel tracking differentiator design based on iterative learning in a moving window

Differential signals are key in control engineering as they anticipate future behavior of process variables and therefore are critical in formulating control laws such as proportional-integral-derivative(PID).The practical challenge,however,is to extract such signals from noisy measurements and this difficulty is addressed first by J.Han in the form of linear and nonlinear tracking differentiator(TD).While improvements were made,TD did not completely resolve the conflict between the noise sensitivity and the accuracy and timeliness of the differentiation.The two approaches proposed in this paper start with the basic linear TD,but apply iterative learning mechanism to the historical data in a moving window(MW),to form two new iterative learning tracking differentiators(IL-TD):one is a parallel IL-TD using an iterative ladder network structure which is implementable in analog circuits;the other a serial IL-TD which is implementable digitally on any computer platform.Both algorithms are validated in simulations which show that the proposed two IL-TDs have better tracking differentiation and de-noise performance compared to the existing linear TD.

Tuning and implementation variants of discrete-time ADRC

Practical implementations of active disturbance rejection control(ADRC)will almost always take place in discretized form.Since applications may have quite different needs regarding their discrete-time controllers,this article summarizes and extends the available set of ADRC implementations to provide a suitable variant for as many as possible use cases.In doing so,the gap between quasi-continuous and discrete-time controller tuning is closed for applications with low sampling frequencies.The main contribution of this article is the derivation of three different discrete-time implementations of error-based ADRC.It is shown that these are almost one-to-one counterparts of existing output-based implementations,to the point where transfer functions and coefficients can be reused in unaltered form.In this way,error-based implementations become firmly rooted in the established landscape of discrete-time ADRC.Furthermore,it becomes possible to equip error-based variants with windup protection abilities known from output-based ADRC.

Simplifying ADRC design with error-based framework: case study of a DC-DC buck power converter

In this work,the problem of designing a robust control algor ithm for a DC-DC buck power converter is investigated.The applied solution is based on a recenly proposed eror-based version of the active disturbance rejection control(ADRC)scheme,in which the unknown higher-order lerms of the reference signal are treated as additional components of the system"total disturbance".The motivation here is to provide a prac tical following of a reference voltage trajectory for the buck converler in specific cases where neither the analytical form of the desired signal nor its future values are known a priori,hence cannot be directly used for control synthesis.In this work.the application of the error-based ADRC results in a prac-tically appealing control technique,with compact struc ture.simplified control rule,and intwitive tuning(inherited from the conventional output-based ADRC scheme).Theoretical.numerical,and experimental results are shown to validate the efficacy of the error-based ADRC in buck converter control,followed by a discussion about the revealed theoretical and practical limitations of this approach.