Fuzzy adaptive Kalman filter for indoor mobile target positioning with INS/WSN integrated method

Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.     

Novel scheme of high precision inertial measurement for high-speed rotating carriers

In order to satisfy the requirement of high precision measurement in a high dynamic environment, a kind of gyro aided multi-accelerometer inertial measurement unit (GAMA-IMU) with six accelerometers and two gyros (6A2G) was proposed in this paper. The available configurations have the problem of low measurement precision in a high dynamic environment due to channel coupling. The three channels were decoupled when calculating the angular velocity in the proposed configuration. The yawing and pitching angular velocity were directly measured by gyros, while only the rolling angular velocity was obtained by the GAMA-IMU indirectly from the rolling angular acceleration and quadratic component of rolling angular velocity. Then a single channel rolling angular velocity calculation model was established and the extended Kalman filter (EKF) was used to do state estimation. Simulations were carried out and results indicated that the calculation precision of the proposed 6A2G configuration could meet the demand of high precision measurement for a high-speed rotating carrier.     

Approach of simultaneous localization and mapping based on local maps for robot

An extended Kalman filter approach of simultaneous localization and mapping（SLAM） was proposed based on local maps A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.     

Autonomous determination of orbit for probe around asteroids using unscented Kalman filter

The observed images of the asteroid and the asteroid reference images are used to obtain the probe-to-asteroid direction and the location of the limb features of the asteroid in the inertial coordinate. These information in combination with the shape model of the asteroid and, attitude information of the probe are utilized to obtain the position of the probe. The position information is then input to the UKF which determines the real-time orbit of the probe. Finally, the autonomous orbit determination algorithm is validated using digital simulation. The determination of orbit Using UKF is compared with that using extended Kalman filter (EKF), and the result shows that UKF is superior to EKF.     

Application of Adaptive Reduced Sigma Points Unscented Kalman Filter to the Tracking of Maneuvering Target

Based on the principle of statistical linear regression, a set of n 2 sigma points instead of 2n 1 sigma points used in the unscented Kalman filter (UKF), is constructed to approximate the system state. And filter accuracy is second order. Real-time of modified UKF is improved. In order to describe accurately the maneuvering target, the "current" statistical model is used. And the equation of acceleration error covariance is modified at every sample time of the filter. The modified adaptive UKF is presented for estimating the position, velocity and acceleration of maneuvering target. Monte Carlo simulations show the modified adaptive UKF acquires good performance for tracking position of maneuvering target. The modified adaptive UKF has better computational efficiency than UKF.     

Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements

A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements. The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution, the commonest cases in engineering, such that the expectation of the measurements could be utilized during the iteration process. To consider the uncertainties in the system model, an upper-bound for the estimation error covariance was obtained since its real value was unaccessible. Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided. Simulations are presented to illustrate the effectiveness of the proposed approach.     

A stealthy method to determine the relative position and velocity for satellite formation flying

To achieve the satellite formation control and the succeed formation missions, we present a new stealthy method to determine the relative states between formation satellites. In this method, the combination of a CCD camera and laser radar is used as the relative measure sensors. To reduce electromagnetic radiation, the laser radar works intermittently to minimize the probability of being discovered. And an unscented Kalman filter (UKF) is applied to estimate the relative states. The observability of this method is analyzed. The validity and effectiveness of the method is demonstrated in a typical application of formation relative navigation.     

Particle filter with importance density function generated by updated system equation

The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.     

Mechanism of Surface Modification for Sericite

Surface modification of sericite by wet method was conducted with the addition of 1.0 % （w/w） silane. The resulting wetting contact angle and activity ratio of sericite were 130° and 98% respectively. Good pre-evaluation indexes of oil value （40.8%） and dispersivity （14.0 mL） were obtained. When 30 % of sericite was filled into acrylonitrile butadiene styrene（ABS） plastic, the bending strength and tensile strength of the composite material were reduced by 7% and 14.3% in comparison to those of pure ABS plastic, while the rigidity was increased by 3 times, and the impact strength and breaking elongation were reduced significantly. The mechanism of surface modification was investigated and the configuration of silane coupling agent on the surface of sericite was given. Infrared （IR） spectroscopic analysis indicates that the adsorption of silane on the surface of sericite belongs to chemical adsorption.     

Dynamic assets allocation based on market microstructure model with variable-intensity jumps简

In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump intensity was introduced to the existing discrete microstructure model to denote large price fluctuations. The nonparametric method of LEE was used for detecting jumps. Further, the extended Kalman filter and the maximum likelihood method were applied to discrete microstructure modeling and the estimation of two market potential variables： market excess demand and liquidity. At last, based on the estimated variables, an assets allocation strategy using evolutionary algorithm was designed to control the weight of each asset dynamically. Case studies on IBM Stock show that jumps with variable intensity are detected successfully, and the assets allocation strategy may effectively keep the total assets growth or prevent assets loss at the stochastic financial market.     

Free clustering optimal particle probability hypothesis density（PHD） filter

As to the fact that it is difficult to obtain analytical form of optimal sampling density and tracking performance of standard particle probability hypothesis density（P-PHD） filter would decline when clustering algorithm is used to extract target states,a free clustering optimal P-PHD（FCO-P-PHD） filter is proposed.This method can lead to obtainment of analytical form of optimal sampling density of P-PHD filter and realization of optimal P-PHD filter without use of clustering algorithms in extraction target states.Besides,as sate extraction method in FCO-P-PHD filter is coupled with the process of obtaining analytical form for optimal sampling density,through decoupling process,a new single-sensor free clustering state extraction method is proposed.By combining this method with standard P-PHD filter,FC-P-PHD filter can be obtained,which significantly improves the tracking performance of P-PHD filter.In the end,the effectiveness of proposed algorithms and their advantages over other algorithms are validated through several simulation experiments.     

Coordination of multiple grid-connected inverters for harmonic compensation

For multiple grid-connected inverters with active filter function, it makes sense to regulate every unit to output maximum active power from photovoltaic arrays, as well as eliminate the harmonic due to the non-linear loads connected to the electric networks. Naturally, a centralized control coordination strategy was proposed for the purpose of high facility utilization, good harmonic compensation ability and unwanted overcompensation condition. Based on a vector decoupling control scheme and generalized instantaneous reactive power theory, the solution was to allocate the harmonic eliminating task for every inverter according to the instantaneous power margin of each. The grid current always keeps sinusoidal in spite of non-linear load change and output active power change for any inverter. The simulation results validate the efficacy of the proposed coordination strategy.     

An optimal method for prediction and adjustment on gasholder level and self-provided power plant gas supply in steel works

An optimal method for prediction and adjustment on byproduct gasholder level and self-provided power plant gas supply was proposed.This work raises the HP-ENN-LSSVM model based on the Hodrick-Prescott filter,Elman neural network and least squares support vector machines.Then,according to the prediction,the optimal adjustment process came up by a novel reasoning method to sustain the gasholder within safety zone and the self-provided power plant boilers in economic operation,and prevent unfavorable byproduct gas emission and equipment trip as well.The experiments using the practical production data show that the proposed method achieves high accurate predictions and the optimal byproduct gas distribution,which provides a remarkable guidance for reasonable scheduling of byproduct gas.     

A novel robust approach for SLAM of mobile robot

The task of simultaneous localization and mapping （SLAM） is to build environmental map and locate the position of mobile robot at the same time. FastSLAM 2.0 is one of powerful techniques to solve the SLAM problem. However, there are two obvious limitations in FastSLAM 2.0, one is the linear approximations of nonlinear functions which would cause the filter inconsistent and the other is the ＂particle depletion＂ phenomenon. A kind of PSO ＆ Hjj-based FastSLAM 2.0 algorithm is proposed. For maintaining the estimation accuracy, H~ filter is used instead of EKF for overcoming the inaccuracy caused by the linear approximations of nonlinear functions. The unreasonable proposal distribution of particle greatly influences the pose state estimation of robot. A new sampling strategy based on PSO （particle swarm optimization） is presented to solve the ＂particle depletion＂ phenomenon and improve the accuracy of pose state estimation. The proposed approach overcomes the obvious drawbacks of standard FastSLAM 2.0 algorithm and enhances the robustness and efficiency in the parts of consistency of filter and accuracy of state estimation in SLAM. Simulation results demonstrate the superiority of the proposed approach.     

Norton equivalent circuit for current control loop of grid-connected system

Modeling method for the current control loop of a grid-connected PWM inverter with the LCL output filter was discussed. Firstly, the current control loop with the LCL inverter-side current as feedback was established. Then, parameters of PI controller were calculated on the basis of an equivalent controlled object. Finally, Norton equivalent circuit for the current control loop of grid-connected system was derived by integrating one control equation, which connected the PWM inverter output voltage and the LCL inverter-side current, with two circuit equations, separately using the LCL inverter-side current and the injected current as loop currents. With the induced Norton equivalent circuit, system-level resonant and unstable issues on real grid-connected system applied in weak distributed power systems can be easily analyzed. The validity of substituting Norton equivalent circuit for grid-connected system is verified by simulation and experiment.     

Decoupling control and zero dynamics stabilization for shunt hybrid active power filter

An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.     

A unified approach of observability analysis for airborne SLAM

An unmanned aerial vehicle （UAV） is arranged to explore an unknown environment and to map the features it finds when GPS is denied.It navigates using a statistical estimation technique known as simultaneous localization and mapping （SLAM） which allows for the simultaneous estimation of the location of the UAV as well as the location of the features it sees.Obscrvability is a key aspect of the state estimation problem of SLAM.However,the dimension and variables of SLAM system might be changed with new features.To solve this issue,a unified approach of observability analysis for SLAM system is provided,through reorganizing the system model.The dimension and variables of SLAM system keep steady,then the PWCS theory can be used to analyze the local or total observability,and under special maneuver,some system states,such as the yaw angle,become observable.Simulation results validate the proposed method.     

Performance assisted enhancement based on change point detection and Kalman filtering

A performance assisted enhancement Kalman filtering algorithm （PAE-KF） for GPS/INS integration navigation in urban areas was presented in this work. The aim of this PAE-KF algorithm was to prevent ＂deep contamination＂ caused by error GPS data. This filtering algorithm effectively combined fault estimation of raw GPS data and nonholonomic constraint of vehicle. In fault estimation, a change point detection algorithm based on abrupt change model was proposed. Statistical tool was then used to infer the future bound of GPS data, which can detect faults in GPS raw data. If any kinds of faults were detected, dead reckoning mechanism begins to compute current position. Nonholonomic constraint condition of vehicle was used to estimate velocity of vehicle and change point detection was added into classic Kalman filtering structure. Experiment on vehicle shows that even when the GPS signals are unavailable for a period of time, this method can also output high accuracy data.     

Effects of magnetic fields on Fe-Si composite electrodeposition

Coatings containing Fe-Si particles were electrodeposited on 3.0wt% Si steel sheets under magnetic fields. The effects of magnetic flux density （MFD）, electrode arrangement and current density on the surface morphology, the silicon content in the coatings and the cathode current efficiency were investigated. When a magnetic field was applied parallel to the current and when the MFD was less than 0.5 T, numerous needle-like structures appeared on the coating surface. With increasing MFD, the needle-like structures weakened and were transformed into dome-shaped structures. Meanwhile, compared to results obtained in the absence of a magnetic field, the silicon content in the coatings significantly increased as the MFD was increased for all of the samples obtained using a vertical electrode system. However, in the case of an aclinic electrode system, the silicon content decreased. Furthermore, the cathode current efficiency was considerably diminished when a magnetic field was applied. A possible mechanism for these phenomena was discussed.     

Desulfurization ability of refining slag with medium basicity

The desulfurization ability of refining slag with relative lower basicity （B） and Al2O3 content （B = 3.5-5.0; 20wt%-25wt% Al2O3） was studied. Firstly, the component activities and sulfide capacity （Cs） of the slag were calculated. Then slag-metal equilibrium experiments were carried out to measure the equilibrium sulfur distribution （Ls）. Based on the laboratorial experiments, slag composition was optimized for a better desulfurization ability, which was verified by industrial trials in a steel plant. The obtained results indicated that an MgO-saturated CaO-Al2O3-SiO2-MgO system with the basicity of about 3.5-5.0 and the Al2O3 content in the range of 20wt%-25wt% has high activity of CaO （αCaO）, with no deterioration of Cs compared with conventional desulfurization slag. The measured Ls between high-strength low-alloyed （HSLA） steel and slag with a basicity of about 3.5 and an Al2O3 content of about 20wt% and between HSLA steel and slag with a basicity of about 5.0 and an Al2O3 content of about 25wt% is 350 and 275, respectively. The new slag with a basicity of about 3.5-5.0 and an Al2O3 content of about 20wt% has strong desulfurization ability. In particular, the key for high-efficiency desulfurization is to keep oxygen potential in the reaction system as low as possible, which was also verified by industrial trials.