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This article develops an evolving type-2 quantum fuzzy neural network (eT2QFNN) control scheme for achieving trajectory tracking with unmanned aerial vehicles (UAVs). The proposed approach involves quantum membership functions, automatic rule growing process, and parameter adjustment learning scenario to deal with the problems of inadequacy, uncertainties, and noise in conventional control techniques. Furthermore, the proposed approach is operated in a parallel structure with the proportional derivative (PD) controller to compensate the transients in performance and learn the dynamic characteristics of the system. Besides, a sliding theory-based adaptive law is equipped with the control approach to compensate for the nonlinearity of the UAV. To assess the performance, numerical simulations and real-time experiments are carried for pitch and yaw axes control of two degrees of freedom (2DoF) helicopter test rig with the proposed approach. The simulations and experiments are aimed at achieving an offline path tracking with an objective to minimize the deviation error and improve the time response characteristics of the UAVs. The results depict the robustness of the proposed approach in terms of integral time absolute error for a helicopter following various trajectories.

Given the scope of its consequences, it's no wonder that violence against women is recognized as a major public health issue. When women are assaulted in many rural areas of India, no reports are filed. The study's goal is to quantify the frequency with which women in eastern India fall victim to their male partners, accounting for relevant socioeconomic factors. Through a multistage sample technique, there were a total of 1718 married women and 1715 married men surveyed across three of Eastern India's four states. Women (victimization) and men (non-victimization) were interviewed using two different sets of piloted, structured questionnaires (perpetration). Participants in a recent study were asked about their own personal experiences with domestic violence. Men's involvement in relationship violence was also investigated through survey responses. Through a structured set of questions, we were able to establish that the three most prevalent injuries resulting from domestic abuse are physical violence, psychological trauma, and sexual assault. Moreover, socioeconomic, and demographic data were collected. In addition to descriptive statistics, we also ran bivariate and multivariate analyses. Of the women in Eastern India who responded to a survey about their experiences with violence, 56% said they had been the victims of physical abuse, 52% said they had been the victims of psychological violence, 25% said they had been the victims of sexual violence, and 18% said they had never been the victims of any kind of violence. When comparing to men, the percentages were 22%, 59%, 17%, and 59.5%. It was men who were more likely to report experiencing violence in any form other than sexual assault. Wives typically pointed the finger at their husbands, but mothers and fathers were also sometimes blamed. Many women who have experienced violence have said that the traumatic effects of that experience lingered for years after the abuse stopped. A woman's socioeconomic level is a significant predictor of whether she would be the victim of domestic violence, and this association may be quantified using a variety of indicators. You are more likely to be a victim of domestic violence if you are male, of lower socioeconomic status, of older age, and have a lower level of education. Multivariate logistic regression analyses have found associations between physical assault and demographic characteristics like state, location (rural vs. urban), age, and women's employment status, as well as household income on a monthly basis. Researchers have found that the same factors associated with sexual assault, such as the victim's location, age, level of education, occupation, and family's average monthly income, are also associated with psychological abuse against women. It is true that domestic violence is a worldwide issue, but Eastern India's data show that it is significantly more prevalent there than in the rest of the country. Every primary care clinic in India should regularly assess and treat victims of violence and their injuries. These results have substantial ramifications for public health and for informing policymakers about the need for laws to prevent violence against women.

This article presents a reinforcement learning (RL) algorithm for achieving model-free control of robotic applications. The RL functions are adapted with the least-square temporal difference (LSTD) learning algorithms to develop a model-free state feedback controller by establishing linear quadratic regulator (LQR) as a baseline controller. The classical least-square policy iteration technique is adapted to establish the boundary conditions for complexities incurred by the learning algorithm. Furthermore, the use of exact and approximate policy iterations estimates the parameters of the learning functions for a feedback policy. To assess the operation of the proposed controller, the trajectory tracking and balancing control problems of unmanned helicopters and balancer robotic applications are solved for real-time experiment. The results showed the robustness of the proposed approach in achieving trajectory tracking and balancing control.

This article proposes the idea of fault classification-based control for the steady-state operation of unmanned surface vehicles (USVs). The idea of fault classification is achieved with the help of wavelet transforms and support vector machines, and the control is performed using a wavelet fuzzy controller. Initially, a brief idea of faults that affect the stable operation of USVs is identified. Furthermore, the surge and sway translational motion of USVs are realized with the help of a ball balancer setup. The fault data are measured in terms of plate angle, ball position, and motor operating voltage for developing the fault classifier. The proposed algorithm depicted improved classification accuracy when compared with conventional methods. To accommodate the operation of the system as per the operating state, a wavelet-based fuzzy controller is proposed. The proposed controller solves the problem of position tracking and balancing for ball and plate system with high precision, hence achieving the stable operation.

The steady-state operation and controlled position tracking in ball balancer applications are largely affected due to their nonlinear and underactuated behavior. To overcome these drawbacks, this paper develops a wavelet-based fuzzy controller which operates in closed loop with the system by measuring the ball position and the plate angle. The proposed approach adapts discrete wavelet transform for denoising the error signal and tuning the weights of the fuzzy controller. To test the effectiveness of the proposed approach, numerical simulations are performed by modeling a two degree of freedom ball balancer system. The eminence of the controller is assessed by comparing its operation on the modeled system with conventional fuzzy logic controller and by calculating the root mean square error, and time response analysis. The results showed a steady and precise response of the proposed approach to the framework of positioning ball on the plate.

This article proposes a fault-tolerant control (FTC) algorithm to monitor the anomalies and control them for unmanned helicopters. This overcomes the drawbacks due to heteroscedasticity and restrictions on the input variables in conventional FTCs and improves the training and testing efficiencies with enhanced control. This is achieved by adopting the support vector data descriptor (SVDD) to learn the operating states of the unmanned helicopter during normal and motor fault operations. Furthermore, a neural integrated fuzzy (NiF) controller is trained to cope up with the states classified by the developed classifier. To realize the development of the proposed control algorithm, the motor faults in the unmanned helicopter are developed by observing the pitch and yaw motor operation of unmanned helicopters. A two-class classification is developed using SVDD for identifying the motor faults and the NiF is trained for controlling the plant during the anomaly. The results depicted 98.6% training accuracy and 98.96% prediction accuracy along with efficient control when tested for a faulty condition on a helicopter test rig.

The balancer systems represent feedback in loop-based underactuated system which is electromechanical, multivariate, and nonlinear. This paper develops a self-balancing controller using an improved ant colony optimization (ACO) to optimize the proportional integral derivative controller (PID) controller. The proposed controller achieves self-balancing control for a ball on the plate by controlling the plate inclination angle. Initially, the modelling of the ball balancer system is achieved with the help of a two degree of freedom (2DoF) ball balancer system controlled by a PID controller. Further, ACO is employed to autonomously evaluate the condition of a process and find the optimal tuning parameters for the PID controller. The transition probability of the ACO is revised to improve the response and convergence speed of the algorithm resulting in an improved ACO. The developed control schemes were applied with the 2DoF ball balancer model both in simulation as well as for the real-time operation. The results depicted the performance of the proposed control scheme by analysing the characteristics such as transient response and steady-state error. Further, stability analysis has been done for the developed control schemes using describing function method for multiple frequencies. The results depicted the superiority of the improved ACO based PID controller over the conventional PID controller.

Summary Fault detection and diagnosis (FDD) plays an essential role in identifying and isolating various faults in a system. In general, fault detection is attained by monitoring the extent of matc...

The trend of electrification within the automotive industry has resulted in the development of electric vehicles (EVs) due to their sustainable and environment-friendly feature. One of the major components of these cars is their energy storage device, as its performance is very crucial for the success of the EV. But the major concern is the properties of the energy storage or battery change with time and usage. Therefore, the degradation of battery properties is interesting, especially the capacity decline. To understand and counter this degradation, it must be measured with high precision. This paper develops a data-driven approach to estimate the health of the batteries by using the support vector machine model. The proposed method identifies the keen points of the operation of an EV battery under aging conditions by performing accelerated aging and trains them with the adapted data-driven approach. To access the aging conditions, an equivalent electrical model of a cell of EV battery is simulated and operated for various current pulses. Further, when tested with unkown operation of a battery, the developed estimator predicted its health with an accuracy of 96.25%. The results depicted that the proposed concept gives an improved measure of the battery state and a pattern on how the capacity degradation occurs with time.

This paper develops a fault classification algorithm using support vectors for monitoring operation anomalies and early fault detection in unmanned helicopters. In general, a fault classifier identifies the operating state of the system which can be further monitored by developing a necessary control action. Hence, to achieve the fault detection, the data between normal operating condition and faulty conditions is monitored. In this paper, a two-class classification method is developed using support vector data description for identifying the motor faults in unmanned helicopter system. The algorithm is developed by observing the data of pitch and yaw motors of a 2DoF helicopter. Further, the action of SVDDs during unknown faults is observed by developing a residual generator which improves the functioning of classifier. The results depicted 98.2% training accuracy and efficient results when tested with a faulty condition.

This paper addresses the problem of positioning control for unmanned surface vehicles (USVs) using proportional–integral–derivative (PID) controller. As the performance of the PID controller greatly depends on the gain values, it is important to select them effectively. However, the adjustment of these gains is a difficult process, so there has been a considerable interest in stochastic optimization methods. Hence, to address the gain adjustment problem of PID, in this paper, we adapt a simultaneous perturbation stochastic approximation (SPSA) method to obtain the values of \(K_{p}\), \(K_{i}\) and \(K_{d}\). The developed SPSA-based PID control strategy is applied for a two-degree-of-freedom (DOF) ball balancer model, which resembles the operation of a USV and is highly nonlinear and unstable system. The experimental results substantiate that the PID gains optimized using SPSA, compared to standard PID and result in not only reduced position error but also improved balancing response with reduced oscillations.

This paper presents the design, control, and validation of two degrees of freedom Ball Balancer system. The ball and plate system is a nonlinear, electromechanical, multivariable, closed-loop unstable system on which study is carried out to control the position of ball and plate angle. The model of the system is developed using MATLAB/Simulink, and neural integrated fuzzy and its hybridization with PID have been implemented. The performance of each controller is evaluated in terms of time response analysis and steady-state error. Comparative study of simulation and real-time control results show that by using the neural integrated fuzzy controller and neural integrated fuzzy with proportional-integral-derivative Controller, the peak overshoot is reduced as compared with the PID controller and lead the system prone to appropriate balancing. These control techniques provide a stable and controlled output to the system for ball balancing and plate angle control.

The key role of fault detection and diagnosis in the nonlinear system is to maintain safety, reliability, and survivability in case of system failure during a fault. The main idea behind this paper is to explore unmanned surface vehicles (USVs) performance under faulty conditions. K-Nearest Neighbour method has been chosen for faults detection, identification, and classification. A ball balancer system, which is a laboratory setup, has been considered for analysis of faults occur. The translational motion-related control of USVs is represented by ball movement on a plate in the x-y direction. The sway motion of USVs corresponds to x-axis movement of the ball while surge represents the y-axis motion of the ball on a plate. For algorithm implementation, the necessary fault data has been taken from the position of the ball, plate angle, and motor input voltage after inserting the fault in the system. For performance analysis, the results of Simulink and hardware has been validated.

Boiler systems face many parametric issues due to inconsistency with grid integrated renewable power generation systems and varying load conditions. In order to achieve an efficient operation of boiler systems, varying conditions such as steam temperature, drum pressure along with drum water level must be controlled. In this paper, a nonlinear model of boiler system is simulated, with feed-water flow and fuel mass rates as the system inputs. A model-free sliding mode controller (MFSMC) is implemented with the simulated model to control the parametric uncertainties. It is observed that the implemented controller improved the performance and robustness of the system irrespective of the perturbations. With the application of the MFSM controller, the system tracks down the desired reference inputs in comparatively lesser time, resulting in smoother responses. The final simulation and results were depicted, discussed, and compared with the fuzzy control system for a better understanding of the developed phenomenon.

This paper proposes intelligent techniques to control the strong nonlinear coupling between the motor rotors and achieve stability during the operation of two degree of freedom (2DoF) helicopter system. Initially, a brief study is carried out to compare the operation of various controllers on the helicopter system. The observations depicted that, the response of the classical controllers is limited in terms of various performance characteristics, especially when subjected to helicopter balancing. Hence, this paper develops a fuzzy logic controller and a fuzzy-PID controller which controls the pitch and yaw motion of the system. The pitch and yaw angle control results has been validated on Simulink and on a test rig. The performance of the controllers is measured in terms of peak overshoot, steady-state error, settling time.

The paper presents designing and control of two-degree-of-freedom helicopter system, with two degrees of freedom. The helicopter is a combination of rotor motors which helps to lift the body of system. This is a nonlinear and unstable system in nature. The control techniques focused are adaptive neuro-fuzzy inference-PID and fuzzy-PID. Helicopter system has been analysed using MATLAB software and analysed in terms of transient response, root-mean-square error, steady-state error and total harmonic distortion analysis for performance assessment. The controllers have been designed with and without integral action.

This paper aims at the development of a randomized algorithm based probabilistic analysis approach for parametric uncertainties in unmanned helicopter systems. The proposed approach is developed considering the stochastic characterization of bounded uncertainty in the system assuming that the plant dynamics are exactly known. This provides a new paradigm for synthesizing the controller gain to solve the problem of trajectory tracking for unmanned. Further, to assess the operation of the proposed randomization algorithm-based probabilistic controller and achieve the controller synthesis, a two degrees of freedom (2DoF) helicopter system is modelled and operated with uncertainties for different trajectories. Besides, the robustness of the controller operating under uncertainties is verified with reachability analysis developed on reach tubes and reach sets of the ellipsoidal method. The results identified the efficiency of the proposed approach with time domain characteristics for both simulation and real-time experiments. Moreover, a comparative assessment of the projected approach with conventional techniques is carried out to validate the controller response on the helicopter model.

This paper develops an intelligent control approach for achieving the non-linear control of a two degrees of freedom (2DoF) ball balancer system. The ball balancer system provides an example of an ...

This paper focuses on the development of approaches to design hybrid power systems for the needs of energy management and power quality. It develops an algorithm for determining an optimal structure of power supply system taking into account technical, environmental and social aspects. This research aims at achieving a regulatory for power management in a PV Wind hybrid power system based on simulated intellect practices. To safeguard efficient optimization of sources, Fuzzy Inference System approach is engaged to accomplish the Maximum Power Point for photovoltaic panels and wind turbine. In addition, the power quality aspects are studied and with the use of UPFC which improves the voltage and current regulations. The Total Harmonic Distortions of the Voltages and currents in the simulated system under different load conditions were analysed with IEEE Standards 519-2014. The whole system is analysed through simulation in MATLAB / Simulink environment.

Various components of Wind energy system included in pitch control where explained in this paper. Pitch angle control design was described and wind velocity variation of pitch controller response is discussed. Large output power and settling time are the results of the pitch control system. The control over the mechanical power is obtained by pitch function and it is the most common method applicable for wind turbine speed variables. In conditions when the value of wind speed may be below the rated power of the generator, the pitch angle is observed to be at its maximum and its value can be lowered in order to help the turbine to accelerate faster. By the reduction of angle of blades the generated power is kept below the rated power for pitch angle controlling in case of power above the rated wind speed. The implementation of pitch control system is easy, but the slow response and large varying output power are its two disadvantages. In this work we present an interface which integrates multiple AI and signal processing techniques for pitch angle control and overcome the various setbacks interrupting smooth performance in a very short span of time. We demonstrate the thought process, simulation, final software interface and test results to confirm its effectiveness.

The paper depicts the reviews on evolution of a cube shaped device called the Cubli, which has the ability to leap up, create equilibrium on different angles and edges. The study is focussed upon the control techniques when there is a sudden brake on high angular velocity rotation of reaction wheels, which are seated on the surface of Cubli, allowing the Cubli to leap up, first to its edge, and then to its corner without any extrinsic control. As the cubli obtains a balancing position, Model predictive control was implemented for overall effective controlling by analyzing future state.

A poly(vinyl chloride)-based membrane of 3,4:12,13-dibenzo-1,6,10,15-tetraazacyclooctadecane with sodium tetraphenyl borate (NaTPB) as an anion excluder and dibutylphthalate (DBP), dibutylbutylphosphonate (DBBP), tris(2-ethylhexyl) phosphate (TEHP) and tributyl phosphate (TBP) as plasticizing solvent mediator was prepared and investigated as a Ni(II)-selective electrode. The best performance was observed with the membrane having the ligand-PVC-TEHP-NaTPB composition 1:4:1:1, which worked well over a wide concentration range (2.82 ×10−6−1.00 × 10−1 M) with a Nernstian slope of 30.5 mV per decade of activity between pH 2.5–7.5. This electrode showed a fast response time of 18 s and was used over a period of 4 months with good reproducibility (S=0.4 mV). The selectivity coefficient over mono-, di- and trivalent cations indicate excellent selectivity for Ni (II) ions over a large number of cations. Anions such as Cl− and NO 3 − do not interfere and the electrode also works satisfactorily in a partially non-aqueous medium. It has been used successfully for determination of Ni (II) in real samples.

A poly (vinyl chloride)-based membrane of 2,3,4-pyridine-1,3,5,7,12-pentaazacyclopentadeca-3-ene with sodium tetraphenylborate(NaTPB) as an anion excluder and dioctyl phthalate (DOP) as plasticizer was prepared and investigated as a Ba(II)-selective electrode. The best performance was observed with the membrane having the ligand–PVC–DOP–NaTPB composition 1:4:1:1, which worked well over a wide concentration range (1.41 × 10−6–1.0 × 10−1 mol L−1) with a Nernstian slope of 30.0 mV per decade of activity between pH 2.5 and 7.0. This electrode showed a fast response time of 18 s and was used over a period of 3 months with good reproducibility (S = 0.4 mV). The selectivity coefficient for mono-, di- and trivalent cations indicates excellent selectivity for Ba(II) ions over a large number of cations. Electrode works satisfactorily in methanolic and ethanolic content up to a maximum of 30%. The sensor has been used as an indicator electrode in potentiometric titration of Ba(II) with EDTA.

Polystyrene-based membrane of 2,3,4,9,10,11-dipyridine-3,10-diaza-1,5,8,12-tetrathiacyclotetradeca-2,9-diene with sodium tetraphenyl borate (STB) and dibutyl phthalate (DBP) as anion excluder and plasticizing agent was prepared and investigated as Hg(II)-selective electrode. The best performance was observed with the membrane having the ligand–polystyrene–DBP–STB composition 1:4:1:1 with a Nernstian slope of 30.0 mV per decade of concentration between pH 2.5 and 5.0. This electrode has been found to be chemically inert and of adequate stability with a response time of 18 s and was used over a period of 120 days with good reproducibility (S=0.3 mV). The membrane works satisfactorily in a partially non-aqueous medium up to a maximum 30% (v/v) content of methanol and ethanol. The practical utility of the proposed chemical sensor has been observed by using it as an end-point indicator in the titration of Hg(II) ions with EDTA. The potentiometric selectivity coefficient values indicate that the membrane sensor is highly selective for Hg(II) ions over a number of monovalent, divalent and trivalent cations.

A poly(vinyl chloride) based membrane based on neutral macrocyclic ionophore: 2,3,4:10,11,12-dipyridine-3,11-diaza-1,5,9,13-tetrathiacyclohexadeca-2,10-diene with sodium tetraphenyl borate (STB) as an anion excluder and dibutylphthalate (DBP) and dioctylphthalate (DOP) as plasticizing solvent mediator was prepared and investigated as a Ag(I)-selective electrode. The best performance was observed with the membrane having the ligand-PVC-DBP-STB composition 1:6:1:2, which worked well over a wide concentration range (3.98 × 10−6 mol L−1−1.00 × 10−1 mol L−1) with a Nernstian slope of 55.3 mV per decade of activity between pH 3.0–7.0. This electrode showed a fast response time of 15 s and was used over a period of three months with good reproducibility (S = 0.3 mV). The selectivity coefficient for mono-, di-, and trivalent cations indicate excellent selectivity for Ag(I) ions over a large number of cations. Anions such as and do not interfere and the electrode also works satisfactorily in a partially n...

A poly(vinyl chloride)-based membrane of 2,9-dimethyl-4,11-diphenyl-1,5,8,12-tetraazacyclotetradeca-1,4,8,11-tetraene with sodium tetraphenylborate (STB) as an anion excluder and dibutyl phthalate (DBP), tris(2-ethylhexyl) phosphate (TEP), dibutyl butylphosphonate (DBBP), and tributyl phosphate (TBP) as plasticizing solvent mediators was prepared and investigated as a Sr(II)-selective electrode. The best performance was observed with the membrane having the ligand-PVC-DBP-STB composition 1:4 : 1:1, which worked well over a wide concentration range (1.4 × 10−6−0.1 mol L−1) with a Nernstian slope of 28.6 mV per decade of concentration between pH 4.0 and 10.0. This electrode showed a fast response time of 12 s and was used over a period of 100 d with good reproducibility (s= 0.3 mV). The selectivity coefficients for monovalent, divalent and trivalent cations indicate excellent selectivity of Sr(II) ions over a large number of cations including Ca(II) and Ba(II). Anions such as Cl− and SO4 2 do not interfere ...

A poly(vinyl chloride)-based membrane of 3,4:11,12-dibenzo-1,6,9,14-tetraazacyclohexadecane with sodium tetraphenyl borate (NaTPB) as an anion excluder and dibutylphthalate (DBP), dibutyl(butyl)phosphonate (DBBP), tris(2-ethylhexyl)phosphate (TEHP) and tributyl phosphate (TBP) as a plasticizing solvent mediator was prepared and investigated as a Cd2+-selective electrode. The best performance was observed with the membrane having a ligand-PVC-DBP-NaTPB composition of 2:25:60:1, which worked well over a wide concentration range (1.6 x 10(-6) - 1.0 x 10(-1) M) with a Nernstian slope of 29.5 mV per decade of activity between pH 2.0 - 6.0. This electrode showed a fast response time of 13 s and was used over a period of 4 months with good reproducibility (S = 0.4 mV). The selectivity coefficient for mono-, di- and trivalent cations indicated excellent selectivity for Cd2+ ions over a large number of cations. Anions such as NO3- and SO4(2-) , did not interfere. The membrane sensor has been successfully used to determine Cd2+ in real samples.

A new 14-membered macrocyclic ligand, 5,7,12,14-dibenzo-2,3,9,10-tetraoxa-1,4,8,11-tetraazacyclotetradecane and a 16-membered ligand, 6,8,14,16-dibenzo-4,12-dimethyl-2,10-diphenyl-1,5,9,13-tetraazacyclohexadeca-1,5,9,12-tetra-ene and their transition metal complexes were prepared by the template method and characterized on the basis of elemental analysis, i.r., 1H-n.m.r., electronic spectral studies, conductivity and magnetic susceptibility measurements.

Template condensation of benzidine, formaldehyde, ethylenediamine or 1,3-diaminopropane, metal salt and 1-phenyl-1,3-butanedione or 2,3-butanedione in a 1:4:2:2 molar ratio results in the formation of two new series of binuclear pentaaza macrocyclic complexes: dichloro[1,1′-phenylbis(7-methyl-9-phenyl-1,3,6,10,13-pentaazacyclotetradeca-6,9-diene) metal(II)], [M2LCl4] (M = CoII, CuII, FeIII and ZnII) and dichloro[1,1′-phenylbis(8,9-dimethyl-1,3,7,10,14-pentaazacyclopentadeca-7,9-diene) metal(II)], [M2L′Cl4] (M = NiII, CoII, CuII and CdII). Both series were characterized by i.r., 1H-n.m.r., u.v.–vis. spectral studies, conductivity and magnetic susceptibility measurements.

A polystyrene-based membrane of 2,10-dimethyl-4,12-diphenyl-1,5,9,13-tetraazacyclohexadeca-1,4,9,12-tetraene macrocyclic ionophore was prepared and investigated as Cr(III)-selective electrode. The best performance was observed with the membrane having the polystyrene-ligand-dibutylphthalate-sodiumtetraphenyl borate composition 1:4:1:1 with a Nernstian slope of 19.0 mV per decade of concentration between pH 3.0 and 6.5. This electrode has been found to be chemically inert and of adequate stability with a response time of 20 s and was used over a period of 100 d with good reproducibility (S= 0.3 mV). The membrane works satisfactorily in a partially non-aqueous medium up to a maximum 30% (v/v) content of methanol and ethanol. The potentiometric selectivity coefficient values indicate that the membrane sensor is highly selective for Cr(III) ions over a number of monovalent, divalent and trivalent cations. The membrane electrode has also been successfully used to determine Cr3+ in various food materials.

A new tetradentate dihydrogen perchlorate macrocyclic ligand (2,4,9,11-tetraphenyl-1,5,8,12-tetraazacyclotetradeca-1,4,8,11-tetraene dihydrogen perchlorate) was prepared and characterised. The macrocycle behaves as a selective chelating ion-exchanger for some metal ions. The polystyrene-based membrane electrode is found to exhibit quite promising selectivity for Cr3+ ions. It can be used to estimate chromium concentrations in the range 3.16x 10(-6)-1.00x10(-1) M with a near-Nernstian slope of 17.5 mV per decade of concentration between pH 3.0 to 6.5. The electrode is found to possess a fast response time of 15 s and was used over a period of three months with good reproducibility (s = +/- 0.3 mV). The selectivity coefficient values for mono-, di- and trivalent cations indicate excellent selectivity for Cr3+ ions over a large number of other cations. Anions such as Cl- and SO4(2-) do not interfere and the electrode also works satisfactorily in a mixed organic-water solution. The sensor has been used as an indicator electrode for the potentiometric titration of Cr3+ with EDTA. The practical utility of the membrane sensor has also been demonstrated in solutions contaminated with detergents (CTAB and SDS). Above all, the membrane sensor has been very successfully used to determine Cr3+ in some foods.

Department of Chemistry, Indian Institute of Technology - Roorkee, Roorkee-24 7 667, India E-mail : wordgfcy@iitr.ernet.in Manuscript received 2 September 2002, accepted 25 November 2002 The aminolysis reactions of O-(2',4'-dinitrophenyl)-2-naphthol (DNPN), O-(2',4'-dinitrophenyl)indanoneoxime (DNPIO), and O-(2,4-dinitrophenyl)propanoneoxime (DNPPO) have been carried out with n-butylamine in acetonitrile at 35 ± 0.1º. The coloured product obtained in each case was N-(2,4-dinitrophenyl)butylamine, in addition, in the case of DNPN, 2-naphthol was also obtained in quantitative yield. Second order rate constant, kA increases linearly with increase in the base concentration. Mild catalysis has been observed during the reaction of n-butylamine with DNPN while no catalysis has been observed in the case of DNPIO and DNPPO. The observed order of reactivity is : DNPN > DNPIO > DNPPO. Mechanistic interpretation is given.

Department of Chemistry, Indian Institute of Technology-Roorkee, Roorkee-24 7 667, India E-mail: wordgfcy@iitr.ernet.in Manuscript received 14 January 2003, revised 23 April 2003, accepted 4 July 2003 The kinetics of the reactions of O-(2',4'-dinitrophenyl)-4-phenyl-3-buten-2-one oxime have been studied with piperidine, cyclohexylamine, n-butylamine and pyrrolidine in acetonitrile at 35 ± 0.1º. Base catalysis has been observed with piperidine and pyrrolidine. Mechanistic interpretation is given.