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Land-use regression (LUR) models have been used to estimate particle mass concentration (PMC), but few studies apply it to predict particle number concentration (PNC) at different sizes. This study aimed to determine both PMC and PNC throughout one year to establish predictive models in Taichung, Taiwan. The annual averages of PM10, PM2.5, and PM1 were 71 ± 46 μg/m3, 44 ± 35 μg/m3, and 32 ± 28 μg/m3, respectively. The PNC at size ranges of

This paper presents a nonlinear adaptive aggressive controller to provide the small scale helicopter with full authority of a variety of flight conditions. Adaptive backstepping technique is employed to systematically synthesize the proposed controller with the online parameter adaptation rule to the vehicle mass variations and with the recurrent neural network (RNN) approximation to the coupling effect between the force and moment controls. This single and systematic design methodology is shown to achieve the semi-global ultimate boundedness of the closed-loop helicopter dynamics and accommodate the aggressive control of flight maneuvers from hovering to trajectory tracking. The high-fidelity and well-validated nonlinear model of a small scale helicopter incorporating with unmodeled dynamics and measurement uncertainties is adopted in the numerical simulations. The performance and merits of the proposed controller are exemplified by conducting three simulation scenarios including the slalom maneuver described in the ADS33.

This paper presents an analysis and measurement method for studying lateral elliptic motion effect of an asymmetric disc-type ultrasonic motor whose stator is a circular disc with a bonded PZT plate serving as a drive. At the edge of the stator with a simple, fixed three-point support of a 120°–90°–150° configuration, there exists a coupled vibration wave with lateral elliptical motion so as to generate a driving force between the stator and the rotor. The equations of the lateral elliptic motion and the driving force are analytically formulated based on the wave equation on the circular plate, thereby obtaining the driving frequency and the revolution speed of the motor. The relationship between the ultrasonic stator and its boundary condition is investigated as well. The analysis shows that the circumferential edge with a 90° included angle is an optimal contact section for the placement of the rotor. Experiments using the laser vibrometer and photodetector are used to show the validity of the proposed analysis method.

This paper presents pragmatic techniques for mechatronic design and injection speed control of an ultra high-speed plastic injection molding machine. Practical rules are proposed to select specifications of key mechatronic components in the hydraulic servo system, in order to efficiently construct an industry-level machine. With reasonable assumptions, a mathematical model of the injection speed control system is established and open-loop experimental data are then employed to validate the system model. By the model, a gain-scheduling PI controller and a fuzzy PI controller are presented, compared and then implemented into a digital signal processor (DSP) using standard C programming techniques. Experimental results are conducted to show that the two proposed controllers are capable of achieving satisfactory speed tracking performance. These developed techniques may provide useful references for engineers and practitioners attempting to design pragmatic, low-cost but high-performance ultra high-injection speed controllers.

This paper presents techniques for design and control of a brushless direct-current (DC) limited-angle torque motor (LATM) with its application to fuel control of gas turbine engines. Given the desired specifications, a two-pole brushless DC LATM with a toroidally wound armature is designed using selected ferromagnetic material and rare-earth permanent magnets; its electromagnetic characteristics is then computationally found and well tuned using the finite element method (FEM) in order to ensure whether the design meets the performance specifications. To achieve the simple and inexpensive semi-closed-loop fuel control, a robust position controller (including a proportional-integral-derivative (PID) controller with a prefilter) is synthesized for providing the required positioning performance for the developed motor, thereby achieving an inexpensive semi-closed-loop fuel control. A closed-loop fuel controller associated with the proposed position controller and a flow meter is then proposed based on multi-loop control structure in order to achieve required linear input–output relationship. All the proposed fuel control laws were implemented using a stand-alone single-chip digital signal processor (DSP). Experimental results are conducted to show the efficacy and usefulness of the developed limited-angle torque motor with its application to an experimental gas turbine fuel control test platform.

This paper presents a stochastic model reference predictive control (SMRPC) approach to achieving accurate temperature control for an industrial oil-cooling process, which is experimentally modeled as a simple first-order system model with given long time delay. Based on this model, the stochastic model reference predictive controller with control weighting and integral action is derived based on the minimization of an expected generalized predictive control (GPC) performance criteria. A real-time adaptive SMRPC algorithm is proposed and then implemented into a stand-alone digital signal processor (DSP). Experimental results show that the proposed control method is capable of giving accurate and satisfactory control performance under set-point changes, fixed load and load changes.

This paper presents a systematical design and characteristic evaluation approach for constructing a one-wheeled actuator driven by one piezoelectric element. Such an actuator is of quite simple construction and equipped with a beam and one movable piezodisc, thereby giving a direct drive which can be particularly useful in applications for micro motion devices. A theoretical model of the actuator is derived based on the lateral elliptical motion, in order to predict driving frequencies of the actuator. Finite element analysis (FEA) modal patterns are employed to investigate dynamic vibration modes, driving frequencies and characteristics of the actuator. Experimental results are conducted for illustration of validity of the proposed design and analysis method, and for verification of characteristics of the one-wheeled actuator.

This paper presents an adaptive backstepping control method for trajectory tracking and stabilization of an omnidirectional wheeled mobile robot with parameter variations and uncertainties caused by friction and slip. The dynamic model of the robot with three independent driving omnidirectional wheels equally spaced at 120 degrees from one another is briefly introduced. With the dynamic model, the adaptive controller to achieve both trajectory tracking and stabilization is synthesized via adaptive backstepping approach. Experimental results are conducted to show the merit of the proposed control method.

This paper presents a design methodology for predictive control of industrial processes via recurrent fuzzy neural networks (RFNNs). A discrete-time mathematical model using RFNN is constructed and a learning algorithm adopting a recursive least squares (RLS) approach is employed to identify the unknown parameters in the model. A generalized predictive control (GPC) law with integral action is derived based on the minimization of a modified predictive performance criterion. The stability and steady-state performance of the resulting control system are studied as well. Two examples including the control of a nonlinear process and the control of a physical variable-frequency oil-cooling machine are used to demonstrate the effectiveness of the proposed method. Both results from numerical simulations and experiments show that the proposed method is capable of controlling industrial processes with satisfactory performance under setpoint and load changes.

In order to achieve good handling (or flying) qualities in longitudinal axis for all flight conditions, an adaptive backstepping flight control law is presented. With the backstepping technique, an adaptive controller is synthesized for the purpose of accomplishing desired responses under a wide range of flight envelope. The specification assignments for flying qualities are used for selecting essential parameters of the proposed adaptive controller for all flight conditions. In comparison with other conventional control methods, the proposed adaptive control law is much simpler and easier to construct and implement. Simulation results show that the proposed method is capable of giving desired closed-loop dynamic performance and robustness against uncertainties within the subsonic and supersonic flight conditions

This paper develops methodology and technique for pose tracking of an autonomous mobile robot (AMR) using a laser scanner. A low-complexity and accurate pose-tracking EKF-based algorithm is proposed using a simple rectangular model and a 2-D laser scanner. By continuously updating the robot's pose and matching the laser data with the environmental model, we find that the outliers can be filtered out effectively by validation gate. Moreover, a Range-Weighted Hough Transform (RWHT) is used to extract the modeled lines from the clutter data. Numerous simulations and experimental results are provided to verify the feasibility and effectiveness of the proposed pose-tracking method.

This paper develops methodologies for an adaptive robust path tracking control of a nonholonomic Wheeled Mobile Robot (WMR) with nonlinear driving characteristics and unknown dynamic parameters. To solve the problem of position/orientation tracking control of WMR, a novel robust kinematics control law is developed to steer the vehicle to asymptotically follow the desired trajectories. To compensate for dynamic effects associated with the dynamic models, an adaptive backstepping path tracking control law with robustness is designed to ensure asymptotic path tracking for the vehicle with unknown dynamic parameters and changeable time-varying payload. Simulation results are included to illustrate feasibility and effectiveness of the proposed control laws.