Post-combustion CO2 Capture Process Research Articles

Impact of blends of aqueous amines on absorber intercooling for post combustion CO2 capture system

Climate change is the biggest challenge of this century due to the global consequences of human activities on the ecosystem resulting in global warming. The emissions of greenhouse gases, mainly CO2 from the combustion of fossil fuels in the power plant is the main cause of global warming and to mitigate these emissions is the foremost challenge. Nowadays, the most preferred method is post combustion chemical absorption using amine-based solvents. However, high energy requirements for this method restrict its deployment. An efficient approach used for the reduction of the high energy requirement of post combustion CO2 capture process was absorber intercooling. Therefore, this research evaluates the effect of two configurations of intercooled absorber such as “simple” and “advanced” intercoolers for CO2 capture integrated with natural gas combined cycle power plant using aqueous alkanolamines, such as 30 wt.% monoethanolamine and 50 wt.% methyl-diethanolamine and their blends. For pure methyl-diethanolamine case, at lean loading 0.01 intercooling configurations; simple and advanced shows the highest reduction of 21.01% and 22.82% in the specific reboiler duty, respectively in comparison to other blends at the expense of highest liquid solvent flow rate. Simple and advanced intercooling configurations shows optimum results for the case with 40% monoethanolamine and 60% methyl-diethanolamine in a blend with decrease of 9.19% and 17.28% in solvent flow rate and a decrease of 9.42% and 16.83% in specific reboiler duty required for 90% CO2 capture rate, respectively. For pure monoethanolamine case at lean loading 0.2 absorber intercooling does not offer significant results.

Influence of five model parameters on the performance of a CO2 absorber column by a loaded aqueous MEA solution

Rigorous packed-bed absorber modeling and simulation are significant for post-combustion CO2 capture processes design. Hence, a good knowledge and judicious selection of model parameters are essential to ensure reliable predictions. In this paper, the reactive absorption of CO2 into loaded aqueous monoethanolamine solution was modeled, furthermore, the effects of five different parameters (kinetic model, enhancement factor, enthalpy of absorption, CO2 diffusivity, and vapor pressure) were investigated. Finally, this study revealed that some model parameters have a large influence on the column performance, contrary to others. In addition, methods and correlations that generally provide more accurate predictions of the empirical data relative to the other cases involved in this research were determined for each model parameter. It was also found that the model deviation was reduced by 18% and 4% for the liquid temperature and liquids CO2 loading profiles, respectively, while comparing between the worst and the best case.

Results From MEA Testing at the CO <sub>2</sub> Technology Centre Mongstad. Verification of Residual Fluid Catalytic Cracker (RFCC) Baseline Results

Technology Center Mongstad (TCM) houses a pilot-scale test facility for CO2 capture solvents termed the “amine plant”, where multiple test campaigns have been performed on monoethanolamine (MEA). The third MEA test campaign (MEA-3) was conducted in June 2017 and several subsequent tests on MEA (MEA-4 and MEA-5) were performed, through October 2018. MEA-3, MEA-4, and MEA-5 have been the most significant collaborative test campaigns that the owners of TCM, TCM DA, have conducted since its inauguration in 2012. The large number of public, industrial, research, and academic participants involved in these campaigns have enriched the projects and ensured that the significant results will serve a broad audience. The main objective of these campaigns was to produce knowledge that can be used to reduce the cost as well as the technical, environmental, and financial risks for the commercial-scale deployment of post-combustion CO2 capture (PCC). This includes demonstration of a model-based control system, dynamic operation of the amine plant, investigating amine aerosol emissions, establishment of residual fluid catalytic cracker (RFCC) — a flue gas emanating from a nearby Equinor refinery that emulates coal in composition — baseline performance with MEA, and specific tests targeted at reducing CO2 avoided cost. Through the campaigns, both flue gas sources currently available to TCM were used, including the RFCC gas as well as flue gas from a nearby combined-cycle gas turbine (CCGT)-based combined-heat-and-power plant (CHP) that operates off of natural gas. The Electric Power Research Institute, Inc. (EPRI) assessed the performance of the MEA-based process using an independent verification protocol (IVP) previously developed for the CHP flue gas. The IVP provides a structured testing procedure for assessing the thermal and environmental performance of PCC processes under normal operating conditions. Based on this, methodology results were presented by Faramarzi et al. The IVP was updated for use with the RFCC as this gas contains 13–14 vol% CO2 content by volume whereas the CHP flue gas has 3.5 vol% CO2 content. Throughout the RFCC testing, TCM DA manually collected extractive samples from the depleted flue gas and product CO2 outlets sequentially. As part of the IVP, EPRI also assessed critical plant instrumentation at TCM for accuracy and precision error based on a comparative analysis done during testing operations and against calibration checks. The MEA baseline process was evaluated during thirteen individual test periods over four days in May 2018. During the tests, extractive samples were taken to measure process contaminants such as aldehydes, ketones, amines, and ammonia. Sulfur oxides and nitrogen oxides were continuously monitored using Fourier-transform infrared (FTIR) analyzers on the depleted flue gas and product CO2 streams. TCM DA has installed multiple measurements of the CO2 concentration (FTIR, non-dispersive infrared sensor, and gas chromatography) allowing comparative confirmation during the test periods. The capture rate was calculated via four methods. CO2 recovery (overall mass balance) was evaluated and the thermal performance (energy consumption) was assessed based on measured data taken during the tests. The CO2 capture rate achieved during the MEA RFCC testing was close to 90%, with steam reboiler duties of 3.43–3.51 GJ/tonne-CO2, and the CO2 gas mass balance closures were close to 100%. These data and the associated assessments, along with the results of TCM DA sampling during these tests, will be presented in this paper and will provide a new baseline case for 30 wt% MEA solvent in higher concentration flue gas capture cases. Based on this, TCM will now have two baselines covering flue gases with 3.5 vol% CO2 (Faramarzi et al.) and with 13–14 vol% CO2 (this project).

Simultaneous parametric optimization for design and operation of solvent-based post-combustion carbon capture using particle swarm optimization

High investment and operating costs are two barriers hindering the commercial deployment of solvent-based post combustion CO2 capture (PCC) technology in power industry. Since upstream power plants are always in flexible operation, conventional approaches which carry out the design based on a fixed condition fail to achieve the best overall performance. To this end, this paper proposes a simultaneous size and operation parameters optimization strategy for the PCC process, in which the flexible operation of the CFPP is taken into account during the design stage. The technique of particle swarm optimization (PSO) is used in a hierarchical manner to find the design and operating conditions of the PCC with minimal total annualized cost. To further explore the optimization potential, the average CO2 capture level in one day is taken as the environmental constraint rather than the conventional instantaneous one. The proposed approach is tested on the PCC design for an existing 660 MW supercritical coal-fired power plant. The optimization results of four different design approaches are compared with the economic, efficiency and environmental (3E) performance being fully assessed. The simulation results show that by using the proposed optimization method, 14.45% reduction in TAC can be attained compared with the conventional approach.

Nonlinear model predictive control (NMPC) of the solvent-based post-combustion CO2 capture process

The flexible operation capability of solvent-based post-combustion capture (PCC) process is vital to efficiently meet the load variation requirement in the integrated upstream power plant. This can be achieved through the deployment of an appropriate control strategy. In this paper, a nonlinear model predictive control (NMPC) system was developed and analysed for the solvent-based PCC process. The PCC process was represented as a nonlinear autoregressive with exogenous (NARX) inputs model, which was identified through the forward regression with orthogonal least squares (FROLS) algorithm. The FROLS algorithm allows the selection of an accurate model structure that best describes the dynamics of the process. The simulation results showed that the NMPC gave better performance compared with linear MPC (LMPC) with an improvement of 55.3% and 17.86% for CO2 capture level control under the scenarios considered. NMPC also gave a superior performance for reboiler temperature control with the lowest ISE values. The results from this work will support the development and implementation of NMPC strategy on the PCC process with reduced computational time and burden.

Accurately Predicting CO2 Reactive Absorption Properties in Aqueous Alkanolamine Solutions by Molecular Simulation Requiring No Solvent Experimental Data

We present a general atomistic simulation framework for efficient reactive equilibrium calculations in dilute solutions, and its application to CO2 reactive absorption in aqueous alkanolamine solutions. No experimental data of any kind are required for the solvents, and no empirical adjustments are required for its implementation. This hybrid methodology calculates reaction equilibrium constants by combining high-level quantum chemical calculations of ideal-gas standard reaction Gibbs energies (ΔG0) with conventional solvation free energy calculations obtained from classical force field methodology. For these quantities we use explicit solvent molecular dynamics simulations with the General AMBER Force Field (GAFF). The resulting equilibrium constants are then coupled with a macroscopic Henry Law based ideal solution model to calculate the solution speciation and the CO2 partial pressure, PCO2. We show results for seven primary amines: monoethanolamine (MEA), 2-amino-2-methylpropanol (AMP), 1-amino-2-propanol (1-AP), 2-amino-2-methyl-1,3-propanediol (AMPD), 2-aminopropane-1,3-diol (SAPD), 2-(2-aminoethoxy)ethanol or diglycolamine (2-AEE or DGA, respectively), and 2-amino-1-propanol (2-AP). Experimental speciation and PCO2 data for some of these are available, with which we validate our methodology. We predict new results for others in cases when such data are unavailable, and provide explanations for the experimental inability to detect carbamate solution species in relevant cases. Our results for the pK value of the carbamate reversion reaction are within the chemical accuracy limit of 218.546/T units (corresponding to 1 kcal·mol–1 in the corresponding free energy change) in comparison with experimental results when such data exist, which at 298.15 K corresponds to 0.73 pK units. The precision of our pK predictions is comparable to that which can be obtained from conventional experimental methodologies for these quantities. Our results suggest that the presented molecular simulation methodology may provide a robust and cost-efficient tool for solvent screening in the design of post-combustion CO2 capture processes.

Technical-economic analysis of [Bmim][BF4] for the post-combustion CO2 capture at ”Termocentro” thermoelectric plant, Colombia

In the present work, steady-state simulations of the natural gas combined cycle (NGCC) and the post-combustion CO2 capture (PCC) processes have been modelled in Aspen Plus® environment. The capture plan model was validated with data from the Colombian power plant "Termocentro" at 300MWe. A techno-economical evaluation study has been performed for both a combined cycle (gas and steam) and the PCC process. The PCC process was based on the solvent 30% (w/w) MEA-H2O and on the solvent H2O-30% (w/w)-MEA-5% (w/w))-[Bmim][Bf4]. Sensitivity analysis was carried out, giving as a result an optimum concentration of 5% (w/w) for the 1-butyl-3-methylimidazolium tetrafluoroborate ionic liquid ([Bmim] [BF4]) solvent. The study indicates how with efficient operation conditions of solvent regeneration, [Bmim][Bf4] may be used for CO2 capture plans on the future.

Experimental evaluation of CO2 capture with an amine impregnated sorbent in dual circulating fluidized bed process

Carbon Capture and Sequestration (CCS) technology to slow global warming is a challenge to be solved worldwide. In this study, a dual circulating fluidized bed process using a solid-sorbent was developed for the post-combustion CO2 capture process from a pulverized coal power plant. This solid-sorbent-based CO2 capture process consists of absorber, regenerator, and standpipes in between them. An amine-functionalized silica was utilized as a solid-sorbent, and a bench-scale facility capable of treating flue gas of 20 Nm3/hr was constructed for the performance verification. As a result, when the sorbent to CO2 ratio was 24.6 wt/wt%, a CO2 capture efficiency of 80% or more was obtained, and the maximum CO2 working capacity was 4.5 wt%. A long-term stability was verified in the bench-scale facility and, as a result, the sorption capacity decreased by 5% for about 800 cycles. In addition, a solid-solid indirect heat exchanger was applied at the upper part of the absorber to partially recover solid sensible energy to reduce the regeneration energy. The sorbent loading inside the tube affects the heat transfer efficiency, and the heat transfer coefficient ranges from 8 to 10.5 W/m2-K.

Sequential Combustion in Steam Methane Reformers for Hydrogen and Power Production With CCUS in Decarbonized Industrial Clusters

In future energy supply systems, hydrogen and electricity may be generated in decarbonized industrial clusters using a common infrastructure for natural gas supply, electricity grid and transport and geological storage of CO2. The novel contribution of this article consists of using sequential combustion in a steam methane reforming (SMR) hydrogen plant to allow for capital and operating cost reduction by using a single post-combustion carbon capture system for both the hydrogen process and the combined cycle gas turbine (CCGT) power plant, plus appropriate integration for this new equipment combination. The concept would be widely applied to any post-combustion CO2 capture process. A newly developed, rigorous, gPROMs model of two hydrogen production technologies, covering a wide range of hydrogen production capacities, thermodynamically integrated with commercially available gas turbine engines quantifies the step change in thermal efficiency and hydrogen production efficiency. It includes a generic post-combustion capture technology – a conventional 30%wt MEA process - to quantify the reduction in size of CO2 absorber columns, the most capital intensive part of solvent-based capture systems. For a conventional SMR located downstream of an H-class gas turbine engine, followed by a three-pressure level HRSG and a capture plant with two absorbers, the integrated system produces ca. 696,400 Nm3/h of H2 with a net power output of 651 MWe at a net thermal efficiency of 38.9%LHV. This corresponds to 34 MWe of additional power, increasing efficiency by 4.9% points, and makes one absorber redundant compared to the equivalent non-integrated system producing the same volume of H2. For a dedicated gas heated reformer (GHR) located downstream of an aeroderivative gas turbine engine, followed by a two-pressure level HRSG and a capture plant with one absorber, the integrated system produces ca. 80,750 Nm3/h of H2 with a net power output of 73 MWe and a net thermal efficiency of 54.7%LHV. This corresponds to 13 MWe of additional power output, increasing efficiency by 13.5% points and also makes one absorber redundant. The article also presents new insights for the design and operation of reformers integrated with gas turbines and with CO2 capture.

Optimization of energy requirements for CO2 post-combustion capture process through advanced thermal integration

The energy optimization modeling work described here was performed to determine efficiency improvements that could be achieved for existing coal-fired power plants to retrofit a partial CO2 capture from the post-combustion flue gas for carbon sequestration through thermal integration. The work presented includes optimization of the mono-ethanol amine (MEA)-based post-combustion CO2 capture to reduce energy requirements that could be achieved at existing power plants by thermal integration of the steam turbine cycle, boiler, CO2 compression train and post-combustion CO2 capture process to offset efficiency and capacity losses that would be incurred by retrofit or implementation of post-combustion CO2 capture. Partial CO2 capture, involving treatment of less than 100% of the flue gas leaving the plant and modular design of the CO2 scrubbing system, was also investigated. Thermal integration of the steam turbine cycle with boiler and CO2 compression train improved cycle and plant performance and offset, in part, the negative effects of post-combustion CO2 capture. The best-analyzed integration options improved gross power output by 5% and net unit efficiency by 1.57%, relative to the conventional MEA process. Operating with 40% CO2 capture increased gross power output by 11.6–14% (depending on the MEA thermal integration option), relative to the conventional MEA integration and 90% CO2 capture. The improvement in net unit performance is larger compared to the improvement in turbine cycle performance because of the CO2 compression work, which is also reduced by partial CO2 capture.

Environmental, health and safety assessment of post-combustion CO2 capture processes with phase-change solvents

A class of solvents for chemisorption-based CO2 capture, phase-change solvents, promises significant energy reductions due to liquid-liquid phase separation and partial solvent recycling before CO2 desorption. Although energy consumption is a critical aspect of the CO2 capture process sustainability, a holistic evaluation of health, safety, and environmental impacts is required to confirm the beneficial performance of processes employing phase-change solvents compared to conventional alternatives. This study outlines a method for combining the life cycle and environmental, health and safety hazard assessment. The method is applied for the first time on processes employing two different exemplary phase-change solvents, a reference aqueous solution of methylcyclohexylamine (MCA) and a novel mixture of cyclohexylpropane-1,3-diamine (S1N) and dimethylcyclohexylamine (DMCA). The results show that phase-change solvents have the potential to be a better alternative to conventional amine (i.e., MEA) solvent systems due to the reduced reboiler duty and lower impact on the environment. However, additional care might need to be taken to prevent the potential accumulation of the carcinogenic nitrosamines in the system.

Post-combustion CO2 capture process in a circulated fluidized bed reactor using 200 kg potassium-based sorbent: The optimization of regeneration condition

Abstract The Potassium-based dry sorbent CO2 capture process can selectively capture CO2 from flue gas without toxicity. In this study, the optimization of regeneration condition was investigated to pursue economical CO2 capture process in a circulated fluidized bed reactor as most energy for CO2 capture is consumed in the sorbent regeneration. One important part for CO2 capture process is to produce highly concentrated CO2 during the sorbent regeneration in the conditions of CO2 rich with a presence of H2O, which thermodynamically reduces the sorbent regeneration efficiency at low temperature. This could be overcome by increasing the regeneration temperature although the sorbent regeneration energy increases. The dry sorbent performance in the carbonator was evaluated by changing the temperature, CO2 and H2O concentration in the regenerator, which showed about 88% CO2 removal efficiency and 5.6 wt% dynamic sorption capacity. The dry sorbent was sampled at each operating condition to confirm the dry sorbent performance, evaluated over CO2 concentration. The optimal regeneration condition was obtained by considering CO2 removal efficiency, dynamic sorption capacity and regeneration energy. Finally, the optimal regenerator temperature was determined to be approximately 468 K where the CO2 capture process in the circulated fluidized bed reactor showed 95% for CO2 purity.

Dynamic analysis and linear model predictive control for operational flexibility of post-combustion CO2 capture processes

A key feature of amine-based post-combustion CO2 capture process is a wide operating range induced by periodic load changes in power plants, which necessitates flexible operation. One possible approach to enhance the operational flexibility is to design a reliable controller that can effectively regulate the process over the operating range. To this end, in this study, a robust model predictive controller is designed by analyzing the dynamic characteristics of a post-combustion CO2 capture process. Specifically, gap metric analysis is performed to analyze the sensitivity of the process. From this analysis, optimal operating conditions are identified by evaluating similarity among the dynamics around different operating conditions. Then, a single linear model predictive controller is designed on the basis of the linear approximation of the original nonlinear model at the chosen conditions. Finally, the effectiveness of the controller is illustrated through a case study on an example CO2 capture process.

Modeling temperature dependent and absolute carbamate stability constants of amines for CO2 capture

Thermodynamic properties and carbamate stability constants (Kc) for a dataset of 25 amines and alkanolamines, with desirable post combustion CO2 capture (PCC) solvent properties, have been studied extensively employing various gaseous phase calculations and solvation models. A comprehensive study of gaseous phase free energy and enthalpy is carried out using density functional methods [B3LYP/6-311++G(d,p)], and composite methods (G3MP2B3, G3MP2, G4MP2 and CBS-QB3). Implicit solvation models (PCM, SM8T and DivCon) and the Explicit Solvation Shell Model (ESS) were used to study solvation free energy of various neutral and ionic species present in the amine-carbamate formation reaction. Temperature dependent carbamate stability constants are calculated for the carbamate formation reaction of amines and alkanolamines to better understand the effect of temperature on temperature swing absorption-desorption PCC processes. The temperature dependency of Kc was compared against available experimental data.

Artificial Neural Networks (ANNs) for Density and Viscosity Predictions of CO2 Loaded Alkanolamine + H2O Mixtures

The physical properties, like density and viscosity, of alkanolamine + H2O (water) + CO2 (carbon dioxide) mixtures receive a significant amount of attention as they are essential in equipment sizing, mathematical modelling and simulations of amine-based post-combustion CO2 capture processes. Non-linear models based on artificial neural networks (ANNs) were trained to correlate measured densities and viscosities of monoethanol amine (MEA) + H2O, MEA + H2O + CO2, and 2-amino-2-methyl-1-propanol (AMP) + MEA + H2O + CO2 mixtures and results were compared with conventional correlations found in literature. For CO2-loaded aqueous amine mixtures, results from the ANN models are in good agreement with measured properties with less than 1% average absolute relative deviation (AARD). The ANN-based methodology shows much better agreement (R2 > 0.99) between calculated and measured values than conventional correlations.

An update of the benchmark post-combustion CO2-capture technology

This study provides a description of a new benchmark post-combustion CO2 capture (PCC) technology reflecting the publicly reported performances by various technology suppliers. To achieve this several amines and amine formulations have been considered using a process model developed in ProTreat®. A 40 wt% formulation of PZ (piperazine)/AMP (amino-methyl-propanol) in a 1:2 M ratio was selected as the most representative of the current state of the art.A PCC process configuration with absorber intercooling and rich split flow was selected to reflect the fact that the technology suppliers use a variety of process designs to optimize the process performance.The techno-economic performances were further detailed for the PCC process integrated with an ultra-supercritical coal fired power station and a natural gas fired combined-cycle.The techno-economic evaluation of the PCC process indicated that the costs of capture with respect to 30 wt% MEA for the coal-fired power station were reduced by 22% and for the natural gas fired combined-cycle by 15%.

Carbon-rich solvent regeneration in solvent-based post-combustion CO2 capture process (PCCC): Process intensification by megasonics

Global greenhouse gas emanations from fossil-fuel combusting for power-generation alone contribute 9.795 gigatonnes (Gt) in 2014. There is a tremendous focus on global carbon capture researchers to cut down these emissions significantly. Chemical absorption is widely used and the use of monoethanolamine (MEA) was generally preferred. However, MEA solutions were not without problems. For example, equipment deterioration due to O2 presence, high energy for solvent-regeneration, solvent degradation and formation of undesired harmful by-products inhibits the solvent's cyclic capacity. To address these issues megasonics-assisted (1 MHz - tank-type) solvent regeneration process had been investigated experimentally. The results revealed that low regeneration temperature (<45 °C), less condenser duty, the potential for sensible heat saving, no reboiler is required facilitates capital and maintenance saving, no significant colour change after regeneration and loss of absorption capacity after regeneration was 3.7 times lower than the conventional. In addition, similar regeneration energy (20.20 KJ/mol CO2) but with 3.5 times lower nominal power input than the conventional regeneration method. Furthermore, physicochemical characterization of the solvent before and after absorption and regeneration followed by 13C NMR spectra analysis was also discussed.

Physical Properties of MEA + Water + CO2 Mixtures in Postcombustion CO2 Capture: A Review of Correlations and Experimental Studies

The knowledge of physicochemical properties of a mixture of amine, water, and CO2 is beneficial in evaluating the postcombustion CO2 capture process and process equipment design. This study reviews the literature of density, viscosity, and surface tension measurements with the evaluated measurement uncertainties and proposed correlations for monoethanol amine (MEA), water, and CO2 mixtures. Adequate research has been performed to measure and develop correlations for pure MEA and aqueous MEA mixtures, but further studies are required for CO2-loaded aqueous MEA mixtures. The correlations fit measured properties with an acceptable accuracy, and they are recommended to use in process equipment design, mathematical modelling, and simulations of absorption and desorption.

Intelligent predictive control of large-scale solvent-based CO2 capture plant using artificial neural network and particle swarm optimization

This paper develops an intelligent predictive controller (IPC) for a large-scale solvent-based post-combustion CO2 capture (PCC) process. An artificial neural network (NN) model is trained to represent the dynamics of the PCC process based on an in-depth behavior investigation of the process under different operating conditions. The resulting NN model can portray the PCC characteristics very well in terms of dynamic trend, response time and steady-state gain. An intelligent predictive controller is thus developed based on the NN model to track the desired CO2 capture level and maintain the given re-boiler temperature, in which the particle swarm optimization (PSO) algorithm is applied to find the best future control sequence for the PCC process. A warm start scheme is proposed in the IPC to improve the quality of initial swarm in the PSO. Dynamic simulations to change CO2 capture level set-point and flue gas flow rate are carried out on the PCC process. The results show that the IPC can adjust CO2 capture level fast and significantly reduce the fluctuations in re-boiler temperature. It is concluded that the proposed IPC is helpful for flexible operation of the solvent-based PCC process.

A robust nonlinear model predictive controller for a post-combustion CO2 capture absorber unit

This study presents the design of a robust nonlinear model predictive controller (NMPC) for the absorber unit of a post-combustion CO2 capture process operating downstream from a coal-fired power plant. The controller employs a dynamic mechanistic model for this process, which allows for a precise treatment of the sources of uncertainty. In the case of the absorber, the model enables explicit consideration of uncertainty in the process operating conditions dictated by upstream units and in physical property parameters associated with phenomenological descriptions of the process. Using the multi-scenario approach, discrete realizations of the uncertain parameters inside a given uncertainty region can be incorporated into the controller to produce control actions that result in a robust operation in closed-loop. The multi-scenario controller was tested under several disturbance rejection scenarios of varying complexity and their performance was assessed against that of single-scenario NMPCs. The benefits of the robust NMPC approach were most evident for longer simulations and, considering the continuous nature of a power plant and its emissions, make the robust NMPC approach suitable for the operation of this process in the presence of uncertainty and disturbances.