Applying variable dissolved oxygen set point in a two level hierarchical control structure to a wastewater treatment process

This paper presents a two-level hierarchical control structure for biological wastewater treatment plants, with the goal of improving effluent quality and reducing operational costs. The Benchmark Simulation Model No. 1 is used as working scenario. The hierarchical structure allows to adjust the dissolved oxygen in the fifth tank (S_O,5) according with the working conditions, instead of keeping it in a fixed value. Model Predictive Control (MPC) with inlet flow rate feedforward control (MPC + FF) is proposed for the lower level to control nitrate nitrogen concentration of the second tank and S_O,5. MPC, Affine Function and fuzzy controller are tested for the higher level to adjust the S_O,5 set point of the lower level based on the ammonium and ammonia nitrogen concentration in the fifth tank. Modifying the tuning parameters of the higher level, a tuning region is determined, in which the effluent quality and operational costs are simultaneously improved.     

Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times

In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modelled by using fuzzy logic and statistical method. This is an experimental study conducted using statistics and fuzzy logic methods. In order to investigate the Marshall Stability of asphalt concrete based on exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30, 40 and 50 °C were selected. The MS of the asphalt concrete at 17 °C (in laboratory environment temperature) was used as reference. The results showed that the MS of the asphalt core samples decreased 40.16% at 30 °C after 1.5 h and 62.39% after 6 h. At 40 °C the decrease was 74.31% after 1.5 h, and 78.10% after 6 h. At 50 °C the stability of the asphalt decreased 83.22% after 1.5 h, 88.66% after 6 h. The relationships between experimental results, fuzzy logic model and statistical results exhibited good correlation. The correlation coefficient was R = 0.99 for fuzzy logic model and R² = 0.9 for statistical method. Based on the results of the study, it could be said that both the fuzzy logic method and statistical methods could be used for modelling of the stability of asphalt concrete under varying temperature and exposure time.     

Experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning

In this paper, we consider the problem of finding decentralized controllers for heavy-duty vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control design methodology. We present a linear quadratic control framework for the design of a high-level cooperative platooning controller suitable for modern HDVs. A nonlinear low-level dynamical model is utilized, where realistic response delays in certain modes of operation are considered. The controller performance is evaluated through numerical and experimental studies. It is concluded that the proposed controller behaves well in the sense that experiments show that it allows for short time headways to achieve fuel efficiency, without compromising safety. Simulation results indicate that the model mimics real life behavior. Experiment results show that the dynamic behavior of the platooning vehicles depends strongly on the gear switching logic, which is confirmed by the simulation model. Both simulation and experiment results show that the third vehicle never displays a bigger undershoot than its preceding vehicle. The spacing errors stay bounded within 6.8 m in the simulation results and 7.2 m in the experiment results for varying transient responses. Furthermore, a minimum spacing of −0.6 m and −1.9 m during braking is observed in simulations and experiments, respectively. The results indicate that HDV platooning can be conducted at close spacings with standardized sensors and control units that are already present on commercial HDVs today.     

Robust microscale grasping through a multimodel design: synthesis and real time implementation

This paper deals with robust force control at the microscale for safe manipulation of deformable soft materials. Since mechanical properties of micrometer sized objects are highly uncertain, instability often occurs during a gripping task. This leads to object damage or destruction due to excessive gripping force. In this paper we propose the design of a robust dynamic output feedback controller that is able to insure desired performances for a set of 65 soft and resilient microspheres whose diameter ranges from 40 μm to 80 μm and stiffness varies from 2.8 N/m to 15.7 N/m. The degrees of freedom of the controller are managed by the use of a set of elementary observers. Robustness with respect to parametric uncertainties is satisfied thanks to an iterative procedure alternating between multimodel closed loop eigenstructure assignment and worst case analysis. The developed controller is of low order and can be implemented in real time. Robust gripping force control is for the first time demonstrated experimentally when dealing with the manipulation of a large number of variable deformable soft materials at the microscale. Both simulations and experimental results validate the interest of such control design approach.     

Fuzzy model tuning using simulated annealing

This paper presents the use of simulated annealing metaheuristic for tuning Mamdani type fuzzy models. Structure of the Mamdani fuzzy model is learned from input–output data pairs using Wang and Mendel’s method and fuzzy c-means clustering algorithm. Then, parameters of the fuzzy system are tuned through simulated annealing. In this paper, we perform experiments to examine effects of (a) initial solution generated by Wang and Mendel’s method and fuzzy c-means clustering method, (b) membership function update procedure, (c) probability parameter for the calculation of the initial temperature, (d) temperature update coefficient used for cooling schedule, and (e) randomness level in the disturbance mechanism used in simulated annealing algorithm on the tuning of Mamdani type fuzzy models. Experiments are performed with Mackey–Glass chaotic time series. The results indicate that Wang and Mendel’s method provides better starting configuration for simulated annealing compared to fuzzy c-means clustering method, and for the membership function update parameter, MFChangeRate ∈  (0, 1], and the probability parameter for the calculation of the initial temperature, P₀ ∈  (0, 1), values close to zero produced better results.     

Using of hydrogen ion-selective poly(vinyl chloride) membrane electrode based on calix[4]arene as thiocyanate ion-selective electrode

A hydrogen ion-selective electrode (ISE) is prepared by using 5,11,17,23-tetra-tert-butyl-25,26,27,28-tetracyanometoxy-calix[4]arene and an investigation about whether it could be used as a thiocyanate ion-selective electrode is made by using its characteristic of becoming thiocyanate sensitive in acidic regions. The electrode of the optimum characteristic has a composition of 1% ionophore, 66% 2-NPOE and 33% poly(vinyl chloride) (PVC). This electrode exhibits a linear response over the range 1.0 × 10⁻¹ to 3.0 × 10⁻⁵ M of thiocyanate with a slope of 52.0 ± 0.2 mV/pSCN. The effects of the pH and the membrane composition are also investigated. The lifetime of the electrode is at least 4 months and its response time is found to be 10–15 s. The selectivity coefficients of some anions are calculated by using mixed solution interference method. Application of the electrode to the potentiometric titration of thiocyanate ion with silver nitrate is reported. There is a good agreement between the results obtained by the proposed electrode and the Mohr method at 95% confidence level.     

Simulation and experiment research on vaporizing liquid micro-thruster

In the present work, a micro-thruster chip with dimension of 19.5 mm × 9.5 mm was fabricated with MEMS technologies for the experiment study of vaporizing liquid micro-thruster. In addition, a full 3D computational model was constructed to simulate the aft section of a vaporizing liquid micro-thruster for investigating flow characteristics. The results show that there were four distinct flow patterns observed in this study including snake flow, vapor-droplet flow, vapor-droplet-jet flow, and vapor flow. To prevent the failure of micro-thruster chip from generating of snake flow, the heating treatment of an empty micro-thruster chip at 300 °C for 2 h was the key factor. The generation of vapor flow preliminarily proved that the concept of vaporizing liquid micro-thruster chip was feasible. Furthermore, the numerical model in this study successfully provided the thrust estimation. The channel cross-section of 1 mm × 100 μm designed in this study was fit for developing a micro-thruster of O(mN) (ranging from 1 to 6 mN approximately). The numerical simulation could match better with the experiment results for the vapor flow cases if the flow oscillation was taken into consideration, and the heating channel of micro-thruster was lengthened to completely vaporize the liquid water.     

Advanced control with parameter estimation of batch transesterification reactor

The objective of this work is to enhance the economic performance of a batch transesterification reactor producing biodiesel by implementing advanced, model based control strategies. To achieve this goal, a dynamic model of the batch reactor system is first developed by considering reaction kinetics, mass balances and heat balances. The possible plant-model mismatch due to inaccurate or uncertain model parameter values can adversely affect model based control strategies. Therefore, an evolutionary algorithm to estimate the uncertain parameters is proposed. It is shown that the system is not observable with the available measurements, and hence a closed loop model predictive control cannot be implemented on a real system. Therefore, the productivity of the reactor is increased by first solving an open-loop optimal control problem. The objective function for this purpose optimizes the concentration of biodiesel, the batch time and the heating and cooling rates to the reactor. Subsequently, a closed-loop nonlinear model predictive control strategy is presented in order to take disturbances and model uncertainties into account. The controller, designed with a reduced model, tracks an offline determined set-point reactor temperature trajectory by manipulating the heating and cooling mass flows to the reactor. Several operational scenarios are simulated and the results are discussed in view of a real application. With the proposed optimization and control strategy and no parameter mismatch, a revenue of 2.76 $ min⁻¹ can be achieved from the batch reactor. Even with a minor parameter mismatch, the revenue is still 2.01 $ min⁻¹. While these values are comparable to those reported in the literature, this work also accounts for the cost of energy. Moreover, this approach results in a control strategy that can be implemented on a real system with limited online measurements.     

Piezoelectric unimorph valve assembled on an LTCC substrate

In this paper a piezoelectric initially open valve was designed in low temperature co-fired ceramic (LTCC), manufactured using standard processes, and tested with integrated gas channels inside the LTCC module. Actuation of the valve was based on a piezoelectric unimorph with a diameter of 15 mm and thickness of 0.35 mm glued onto the fired LTCC substrate. Subsequently, a series of tests, including flow, displacement and switching time measurements, was carried out. Measurements of the valve revealed a flow of 143 ml/min under 1 bar pressure, leakage levels of 4%, valve displacement of 1.3 μm, and closing times less than 30 ms. Additional miniaturization and integration of an embedded valve in the LTCC will be pursued, enabling improved manufacturing as a batch process and micro- and nano-litre fluid management for various applications.     

Active noise control in a forced-air cooling system

This paper discusses the design methodology for the active noise control of sound disturbances in a forced-air cooling system. The active sound cancellation algorithm uses the framework of output-error based optimization of a linearly parametrized filter for feedforward sound compensation to select microphone location and demonstrate the effectiveness of active noise cancellation in a small portable data projector. Successful implementation of the feedforward based active noise controller on a NEC LT170 data projector shows a 20–40 dB reduction per frequency point in the spectrum of external noise of the forced-air cooling system can be obtained over a broad frequency range from 1 to 5 kHz. A total noise reduction (unweighted) of 9.3 dB is achieved.     

Development of a piezoelectric lead titanate thin film process on silicon substrates by high rate gas flow sputtering

Polycrystalline lead titanate (PT) thin films in the range of 3–6 μm were crack and void free deposited on silicon substrates in a high rate gas flow sputtering process. Gas flow sputtering uses the hollow cathode effect which results into high deposition rates of about 120 nm/min. (1 1 1) Textured platinum was used as bottom electrode to assist the nucleation of PT.Material properties of the PT thin films as well as the Pt bottom electrode like topography, morphology, chemical composition, and structure are evaluated. The sputtered PT layers show clearly Perovskite traces in XRD patterns, even the (1 1 1) texture of the Pt is partial transferred. The most difficult part is to fulfil the empirical formula PbTiO₃. This problem is solved by stabilising the process parameters. It was shown that the temperature has got enormous influence at the stoichiometry.     

Predictive functional control of an axis positioning system with an estimator-based internal model

This paper deals with an application of the predictive functional control with a state estimator-based internal model (PFC_ EBIM). The PFC_ EBIM has been shown to be effective in simulation. However, neither detailed experimental validation nor comparison with other controllers has been reported thus far. Here, the PFC_ EBIM is implemented in a single-axis positioning system, and a few experimental tests are conducted. Tracking performance of the PFC_ EBIM, standard PFC, and P – PI control for both smooth and non-smooth reference signals are compared. The experimental results prove the effectiveness of the PFC_ EBIM.     

Fuzzy modeling and stable model predictive tracking control of large-scale power plants

This paper develops a stable model predictive tracking controller (SMPTC) for coordinated control of a large-scale power plant. First, a Takagi–Sugeno (TS) fuzzy model is established to approximate the behavior of the boiler–turbine coordinated control system (CCS) using fuzzy clustering and subspace identification (SID). Then, an SMPTC is designed based on the fuzzy model to track the power and pressure set-points while guaranteeing the input-to-state stability and the input constraints of the system. An output-based objective function is adopted for the proposed SMPTC so that the controller could be directly applicable for the data-driven model. Moreover, the effect of modeling mismatches and unknown plant variations has been overcome by the use of a disturbance term and steady-state target calculator (SSTC). Simulation results for a 600 MW power plant show that an off-set free tracking performance can be achieved over a wide range load variation.     

Perchlorate-selective polymeric membrane electrode based on a cobaloxime as a suitable carrier

A cobaloxime ([chlorobis(dimethylglyoximeato)(triphenylphosphine)] cobalt (III), [Co(dmgH)₂pph₃Cl]) incorporated in a plasticized poly(vinyl chloride) membrane was used to develop a perchlorate-selective electrode. The influence of membrane composition on the electrode response was studied. The electrode exhibits a Nernstian response over the perchlorate concentration range 1.0 × 10⁻⁶ to 1 × 10⁻¹ mol l⁻¹ with a slope of −56.8 ± 0.7 mV per decade of concentration, a detection limit of 8.3 × 10⁻⁷, a wide working pH range (3–10) and a fast response time (<15 s). The electrode shows excellent selectivity towards perchlorate with respect to many common anions. The electrode was used to determine perchlorate in water and human urine.     

An automated signalized junction controller that learns strategies by temporal difference reinforcement learning

This paper shows how temporal difference learning can be used to build a signalized junction controller that will learn its own strategies through experience. Simulation tests detailed here show that the learned strategies can have high performance. This work builds upon previous work where a neural network based junction controller that can learn strategies from a human expert was developed (Box and Waterson, 2012). In the simulations presented, vehicles are assumed to be broadcasting their position over WiFi giving the junction controller rich information. The vehicle's position data are pre-processed to describe a simplified state. The state-space is classified into regions associated with junction control decisions using a neural network. This classification is the strategy and is parametrized by the weights of the neural network. The weights can be learned either through supervised learning with a human trainer or reinforcement learning by temporal difference (TD). Tests on a model of an isolated T junction show an average delay of 14.12 s and 14.36 s respectively for the human trained and TD trained networks. Tests on a model of a pair of closely spaced junctions show 17.44 s and 20.82 s respectively. Both methods of training produced strategies that were approximately equivalent in their equitable treatment of vehicles, defined here as the variance over the journey time distributions.     

On active acceleration control of vibration isolation systems

Active vibration isolation systems (VIS) have been widely used from the space shuttle applications to the ground vehicle suspensions. The main control objective is to achieve the minimum vibrations at the flotor for given vibrations at the stator. With respect to a fundamental limitation of using the PD type flotor acceleration controller, an I (integral) and II (double integral) type flotor acceleration controller is proposed in this paper. By incorporating the feedforward compensation of the umbilical dynamics, the proposed acceleration controller is able to experimentally push down the lowest isolation frequency from 1.4 Hz (when PID control is used) to 0.03 Hz with a sufficiently improved vibration isolation performance up to 10 Hz, with respect to a MIM (Microgravity Vibration Isolation Mount) system tested on the ground. A unique frequency selective filter (FSF) is also proposed, which experimentally suppresses a fixed-frequency umbilical resonant mode at 22.2 Hz with an attenuation of 20 dB.     

Thick film sensors based on laccases from different sources immobilized in polyaniline matrix

Thick film electrode based biosensors containing Trametes versicolor (TvL) and Aspergillus niger (AnL) laccases and Agaricus bisporus tissues (AbT) were developed for the determination of phenolic compounds and the measurement was based on oxygen consumption in relation to analyte oxidation. The electrodeposited organic polymer; polyaniline was used as a matrix for the immobilization in the preparation of thick film sensors. The systems were calibrated for different phenolic substances. A linearity was obtained in concentration range between 0.4 and 6.0 μM phenol, 0.2 and 1.0 μM catechol, 2.0 and 20.0 μM l-DOPA for TvL based biosensor; for AnL based enzyme electrode 0.4 and 4.0 μM phenol, 0.4 and 15 μM catechol, 0.4 and 6.0 μM l-DOPA; for AbT electrode 1.0 and 10 μM phenol, 0.4 and 1.6 μM catechol, 1.0 and 10 μM l-DOPA, respectively, in the response time of 300 s. Furthermore, as well as sample application and accuracy, optimum pH, temperature and thermal stabilities of the proposed systems were also detected.     

Fuzzy measurable house of quality and quality function deployment for fuzzy regression estimation problem

In present competitive environment, it is necessary for companies to evaluate design time and effort at the early stage of product development. However, there is somewhat lacking in systemic analytical methods for product design time (PDT). For this end, this paper explores an intelligent method to evaluate the PDT. At the early development stage, designers are short of sufficient product information and have difficulty in determining PDT by subjective evaluation. Thus, a fuzzy measurable house of quality (FM-HOQ) model is proposed to provide measurable engineering information. Quality function deployment (QFD) is combined with a mapping pattern of “function → principle → structure” to extract product characteristics from customer demands. Then, a fuzzy support vector regression machine (FSVRM) model is built to fuse data and realize the estimation of PDT, which makes use of fuzzy comprehensive evaluation to simplify structure. In a word, the whole estimation method consists of four steps: time factors identification, product characteristics extraction by QFD and function mapping pattern, FSVRM learning, and PDT estimation. Finally, to illustrate the procedure of the estimation method, the case of injection mold design is studied. The results of experiments show that the fuzzy method is feasible and effective.     

Modeling of steady state hot flow behavior of API-X70 microalloyed steel using genetic algorithm and design of experiments

API-X70 microalloyed steel is one of the most conventional materials that has been used to produce the pipelines used in oil and gas industry. This steel is produced by thermo mechanical processing (TMP). Prediction of steady state hot flow behavior of metals during TMP, for design of its forming process is of great importance. In this research, flow curves of API-X70 were obtained using hot torsion test at temperature range of 950–1150 °C and strain rates of 0.001–3 s⁻¹. Genetic algorithm (GA) was used to find parameters of steady state stress semi-empirical model in the way that minimizing the difference between experimental data and model output. The optimal combination of GA parameters were chosen by Taguchi design of experiments(DOE) method in order to increase efficiency of GA. Accuracy of developed model to predict flow stress in steady state region was evaluated through statistical methods. Results showed a good agreement between developed model and experimental data with R² = 0.99 and this model can predict steady state flow stress well.