Solving nonlinear optimal control problems using a hybrid IPSO-SQP algorithm

A hybrid algorithm by integrating an improved particle swarm optimization (IPSO) with successive quadratic programming (SQP), namely IPSO-SQP, is proposed for solving nonlinear optimal control problems. The particle swarm optimization (PSO) is showed to converge rapidly to a near optimum solution, but the search process will become very slow around global optimum. On the contrary, the ability of SQP is weak to escape local optimum but can achieve faster convergent speed around global optimum and the convergent accuracy can be higher. Hence, in the proposed method, at the beginning stage of search process, a PSO algorithm is employed to find a near optimum solution. In this case, an improved PSO (IPSO) algorithm is used to enhance global search ability and convergence speed of algorithm. When the change in fitness value is smaller than a predefined value, the searching process is switched to SQP to accelerate the search process and find an accurate solution. In this way, this hybrid algorithm may find an optimum solution more accurately. To validate the performance of the proposed IPSO-SQP approach, it is evaluated on two optimal control problems. Results show that the performance of the proposed algorithm is satisfactory.     

Mortality response of folate receptor-activated,PEG–functionalized TiO2 nanoparticles for doxorubicin loading with and without ultraviolet irradiation

TiO₂ nanoparticles (NPs) were synthesized by hydrothermal assisted sol–gel technique. In the next step, as-synthesized NPs were modified by poly ethylene glycol (PEG). Then, folic acid (FA) was conjugated to TiO₂–PEG. Finally, Doxorubicin (Dox) as an anticancer drug was loaded on as-prepared TiO₂–PEG–FA nanocarrier. The optimization of TiO₂ and FA concentration and the influence of ultraviolet (UV) irradiation on photocatalytic activity of nanocarrier and Dox loaded carrier were assessed by utilizing the 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltetrazolium bromide (MTT)-assay method.     

A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China

Bulletin of Engineering Geology and the Environment - The main objective of the current study is to apply a random forest (RF) data-driven model and prioritization of landslide conditioning factors...     

Observer‐based adaptive optimal output containment control problem of linear heterogeneous Multiagent systems with relative output measurements

This paper develops a relative output‐feedback–based solution to the containment control of linear heterogeneous multiagent systems. A distributed optimal control protocol is presented for the followers to not only assure that their outputs fall into the convex hull of the leaders' output but also optimizes their transient performance. The proposed optimal solution is composed of a feedback part, depending of the followers' state, and a feed‐forward part, depending on the convex hull of the leaders' state. To comply with most real‐world applications, the feedback and feed‐forward states are assumed to be unavailable and are estimated using two distributed observers. That is, a distributed observer is designed to measure each agent's states using only its relative output measurements and the information that it receives by its neighbors. Another adaptive distributed observer is designed, which uses exchange of information between followers over a communication network to estimate the convex hull of the leaders' state. The proposed observer relaxes the restrictive requirement of having access to the complete knowledge of the leaders' dynamics by all the followers. An off‐policy reinforcement learning algorithm on an actor‐critic structure is next developed to solve the optimal containment control problem online, using relative output measurements and without requiring the leaders' dynamics. Finally, the theoretical results are verified by numerical simulations.     

Recovery of15N from ammonium nitrate and algal biomass-amended soil

A greenhouse experiment was conducted to compare the effectiveness of blue-green algae (Anabaena flos aquae) produced in a simulated inorganic-wastewater medium and NH₄NO₃ as sources of N for bermudagrass (Cynodon dactylon L.) on a Decatur silt loam soil (clayey, kaolinitic, thermic Rhodic Paleudult).¹⁵N-labeled blue-green algae and¹⁵N-labeled NH₄NO₃ were used as N sources to supply up to 300 mg N per pot (3 kg of soil). Bermudagrass was clipped at 42, 63, and 102 d after planting and dry matter yield, total, and¹⁵N were determined at each clipping. Results indicated a highly significant increase in total dry matter (shoots and roots) and N uptake over the control for both algae and NH₄NO₃ treatments at all N rates. There were no significant effects of N source on bermudagrass yields, but total N uptake was significantly higher with NH₄NO₃. The net mineralization of N from blue-green algal biomass ranged from 36 to 59% of the total N applied and the corresponding net release for NH₄NO₃ ranged from 65 to 86%. From 29 to 54% of the total N applied as blue-green algal biomass and from 50 to 75% of the N applied as NH₄NO₃ were assimilated by bermudagrass plants. For N rates above 100 mg N pot^–1, higher proportions of the labeled N in the shoots of the third harvest were derived from algal biomass than from NH₄NO₃. A large portion of the labeled N remained undecomposed or immobilized in the algae treated soil (41–64%) as compared to NH₄NO₃ treated soil (14–35%). More loss of N occurred in the NH₄NO₃ treatments from 3 to 15%, while the corresponding figures for algae treated soil were 2 to 8%.     

Soil nutrient evaluation from swine effluent application to five forage-system practices

Many contract swine producers are located in the southeastern U.S. In this region almost all of the swine effluent from swine production is applied to warm-season perennial species such as bermudagrass [Cynodon dactylon (L.) Pers.] which is widely grown for summer grazing and hay production. A 3-yr study was conducted to investigate the impact of forage double-cropping on nutrient accumulation and leaching in Mantachie fine loam soil fertilized with swine (Sus scrofa domesticus) lagoon effluent as the source of plant nutrients. Plots of previously established Tifton 44 bermudagrass were overseeded in the fall with one of four winter annuals: berseem clover (Trifolium alexandrinum L.); crimson clover (T. incarnatum L.); ryegrass (Lolium multiflorum L.); or wheat (Triticum aestivum L.). Four plots of bermudagrass were not overseeded and considered as control. Plots were harvested in spring for cool-season annual hay and in summer for bermudagrass hay. Swine effluent was applied during spring and summer on a need base. Suction lysimeters were installed in selected plots at two depths to monitor nutrient leaching. Surface soil samples were taken to determine baseline nutrient contents, followed by three other sampling dates during the study. Bermudagrass dry matter production (3-yr average = 9.8 Mg ha⁻¹) was not adversely affected by the overseeding treatments. Greatest dry matter production was achieved with bermudagrass overseeded with ryegrass (3-yr average  = 11.3 Mg ha⁻¹). Soil pH decreased by almost one unit by the end of the study. While total P (TP) did not change much, Mehlich-3 P (M3-P), K, Cu, and Zn increased significantly, Mg and Mn concentrations decreased by 2002 compared to the baseline levels. Soil P, Mg, K, Fe, Mn, and Zn accumulation were greater under bermudagrass/wheat combination. In general, the influence of double cropping on soil nutrient accumulation was not conclusive, however, this practice provides the year-round green forage for grazing and haying. Nutrient concentrations in soil and lysimeter leachate were directly related to the quantity of effluent applied. Results also demonstrated that effluent application must be coordinated with the nutrient requirements of the growing forages in order to minimize accumulation and leaching.     

Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems

In this paper, an integral reinforcement learning (IRL) algorithm on an actor–critic structure is developed to learn online the solution to the Hamilton–Jacobi–Bellman equation for partially-unknown constrained-input systems. The technique of experience replay is used to update the critic weights to solve an IRL Bellman equation. This means, unlike existing reinforcement learning algorithms, recorded past experiences are used concurrently with current data for adaptation of the critic weights. It is shown that using this technique, instead of the traditional persistence of excitation condition which is often difficult or impossible to verify online, an easy-to-check condition on the richness of the recorded data is sufficient to guarantee convergence to a near-optimal control law. Stability of the proposed feedback control law is shown and the effectiveness of the proposed method is illustrated with simulation examples.     

Artificial neural network–genetic algorithm for estimation of crop evapotranspiration in a semi-arid region of Iran

This study compares the daily potato crop evapotranspiration (ET_C) estimated by artificial neural network (ANN), neural network–genetic algorithm (NNGA) and multivariate nonlinear regression (MNLR) methods. Using a 6-year (2000–2005) daily meteorological data recorded at Tabriz synoptic station and the Penman–Monteith FAO 56 standard approach (PMF-56), the daily ET_C was determined during the growing season (April–September). Air temperature, wind speed at 2 m height, net solar radiation, air pressure, relative humidity and crop coefficient for every day of the growing season were selected as the input of ANN models. In this study, the genetic algorithm was applied for optimization of the parameters used in ANN approach. It was found that the optimization of the ANN parameters did not improve the performance of ANN method. The results indicated that MNLR, ANN and NNGA methods were able to predict potato ET_C at desirable level of accuracy. However, the MNLR method with highest coefficient of determination (R ² > 0.96, P value < 0.05) and minimum errors provided superior performance among the other methods.     

Investigation on mechanochemical synthesis of Al2O3/BN nanocomposite by aluminothermic reaction

Alpha-alumina–boron nitride (α-Al₂O₃–BN) nanocomposite was synthesized using mixtures of aluminum nitride, boron oxide and pure aluminum as raw materials via mechanochemical process under a low pressure of nitrogen gas (0.5 MPa). The phase transformation and structural evaluation during mechanochemical process were investigated by X-ray diffractometry (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and differential thermal analysis (DTA) techniques. The results indicated that high exothermic reaction of Al–B₂O₃ systems under the nitrogen pressure produced alumina, aluminum nitride (AlN), and aluminum oxynitride (Al₅O₆N) depending on the Al value and milling time, but no trace of boron nitride (BN) phases could be identified. On the other hand, AlN addition as a solid nitrogen source was effective in fabricating in-situ BN phase after 4 h milling process. In Al–B₂O₃–AlN system, the aluminothermic reaction provided sufficient heat for activating reaction between B₂O₃ and AlN to form BN compound. DTA analysis results showed that by increasing the activation time to 3 h, the temperature of both thermite and synthesis reactions significantly decreased and occurred as a one-step reaction. SEM and TEM observations confirmed that the range of particle size was within 100 nm.     

Synthesis and characterisation of iron oxide nanoparticles conjugated with epidermal growth factor receptor (EGFR) monoclonal antibody as MRI contrast agent for cancer detection

The aim of this study is to synthesise superparamagnetic iron oxide nanoparticles conjugated with anti‐epidermal growth factor receptor monoclonal antibody (ANTI‐EGFR‐SPION) and investigate its physicochemical characterisation and biocompatibility as a targeted magnetic resonance imaging (MRI) contrast agent for the EGFR‐specific detection in EGFR expressing tumour cells. These particles employed biocompatible polymers, poly(D,L‐lactide‐co‐glycolide) (PLGA) and polyethylene glycol aldehyde (PEG‐aldehyde), to increase the half‐life of particles in circulation and reduce their side effects. The Fe₃ O₄ ‐loaded PLGA‐PEG‐aldehyde nanoparticles were prepared by a modified water‐in‐oil‐in‐water double emulsion method. The EGFR antibody was conjugated to the surface of SPIONs using the aldehyde‐amine reaction. Synthesised conjugates (nanoprobes) were characterised using Fourier transform infrared spectrophotometry, dynamic light scattering, transmission electron microscopy images, and vibrating‐sample magnetometery, and the results showed that the conjugation was successful. The mean diameter of nanoprobes was about 25 nm. These nanoprobes exhibited excellent water‐solubility, stability, and biocompatibility. Meanwhile, MR susceptibility test proved that synthesised nanoprobes can be managed for negative contrast enhancement. The results of this study suggested the potential use of these nanoprobes for non‐invasive molecular MRI in EGFR detection in the future.Inspec keywords: solubility, nanomedicine, cancer, spectrophotometry, emulsions, biomedical MRI, nanomagnetics, nanofabrication, tumours, nanoparticles, magnetic particles, molecular biophysics, light scattering, proteins, cellular biophysics, Fourier transform spectra, superparamagnetism, polymers, transmission electron microscopy, iron compoundsOther keywords: physicochemical characterisation, superparamagnetic iron oxide nanoparticles, novel targeting cancer detection, anti‐epidermal growth factor receptor monoclonal antibody, ANTI‐EGFR‐SPION, biocompatibility, targeted magnetic resonance imaging contrast agent, EGFR‐specific detection, EGFR expressing tumour cells, biocompatible polymers, PLGA‐PEG‐aldehyde nanoparticles, modified water‐in‐oil‐in‐water double emulsion method, EGFR antibody, aldehyde‐amine reaction, synthesised conjugates were characterised using Fourier, transmission electron microscopy images, synthesised nanoprobes, EGFR detection, size 25.0 nm, Fe₃ O₄