Motor Angular Velocity Research Articles

Lyapunov-based estimation and control of velocity and load in rotating machines via Luenberger globally-convergent observer

This paper presents the design of a Lyapunov-based Luenberger-like observer to simultaneously estimate the non-available angular velocity and the unknown constant load torque of rotating machines. This proposal assumes that the only measurable output is the rotor angle, which is considered to be defined in the circle, its natural topology. This provides nonlinear dynamics where the Lyapunov-based Luenberger-like observer globally converges. Moreover, a trajectory tracking controller for the motor angular velocity is also designed by feeding back the observer estimations. Convergence analysis of the observer-controller system is performed using Lyapunov-like theory. The effectiveness and performance of the system are validated through tests performed on an experimental platform.

Mode decomposed passivity-based speed control of DC drive with bidirectional Zeta-SEPIC DC-DC converter for light electric vehicles

Currently, light electric vehicles are rapidly developing in various kinds. To power these vehicles with batteries, the simplest electric drive system is a DC motor controlled by a DC-DC converter. This work utilizes a bidirectional Zeta-SEPIC DC-DC converter with an integrated DC motor. This implementation enables control of motor speed and torque in traction and regenerative braking modes. Additionally, it allows for the use of a lower voltage battery compared to the motor's rated voltage, reducing battery weight and increasing safety. In this work, a decomposition approach is applied. Two separate port-controlled Hamiltonian subsystems are obtained to adjust the motor angular velocity in the traction (Zeta) and braking (SEPIC) modes of the DC-DC converter. The Passivity-Based Control (PBC) method is used to synthesize the drive control subsystems in these modes. This method is based on the energy laws of processes in systems and provides asymptotic stability of nonlinear systems, in this case, two fourth-order subsystems for speed control. Two third-order current control subsystems synthesized by the PBC were used to limit the motor current at a given level. The synthesis resulted in sets of possible structures of control influence formers (CIFs) for all PBC subsystems using Zeta and SEPIC DC-DC converters. The study analyzed the operation of the obtained structures of the CIFs, selected the most effective ones, and determined the laws of adaptation of their parameters to the value of the motor angular velocity through computer simulation in Matlab/Simulink. The results of the simulation showed that the drive operated well in both static and dynamic modes.

Study of a wall-climbing robot based on chain feet with negative pressure adhesion

In this paper, a wall-climbing robot based on chain feet with negative pressure adhesion is designed. The robot uses chain feet with negative pressure adhesion as the motion units and has the characteristics of adhesion and barrier crossing. Analyzing the power consumption is an important aspect of robot design. The influences of robot design parameters on mechanical characteristics are analyzed with the kinetic method. The robot power model is constructed by combining the energy model of the drive motor and the power model of the transmission system. The relationship between the key parameters and robot power consumption is established by discussing the effects of the robot load, motor angular velocity, and other related design parameters on the robot power consumption. Simulations and experiments show that the established robot power model can be used as a theoretical basis for the optimal design of robots and provides a reference for establishing an optimal model for the motion control of robots.

Fault estimation and active fault‐tolerant control for a class of nonlinear systems with actuator and sensor faults based on unknown input iterative learning

AbstractIn this paper, fault estimation and active fault‐tolerant control are studied for a class of nonlinear systems with simultaneous actuator and sensor faults, as well as unknown external disturbances. Firstly, the state equation of a class of nonlinear systems is transformed into an augmented system state equation by extending the sensor fault as an auxiliary state. Then, a novel fault estimation observer based on iterative learning with unknown inputs is designed to estimate the system state, as well as actuator and sensor faults. Subsequently, by using the fault estimation information, a dynamic output feedback active fault‐tolerant control scheme is proposed to compensate for the influence of faults on the system. Lyapunov stability theory is used to prove the stability of the closed‐loop system and the convergence of the fault estimation observer. The gain matrices of the fault estimation observer and fault‐tolerant controller are obtained by solving linear matrix inequalities. Furthermore, the paper avoids the use of the norm in the convergence proof of the conventional iterative learning algorithm, which reduces the amount of calculation in the derivation process. Finally, the effectiveness and accuracy of the proposed method are verified through simulation of the DC motor angular velocity system.

Hierarchical mixture of experts for autonomous unmanned aerial vehicles utilizing thrust models and acoustics

Accurate position, velocity, attitude, and angular velocity state estimation is crucial for unmanned aerial vehicles, especially in enabling them with autonomous capabilities. It is necessary to adequately model and account for all the environmental and dynamic flight parameters. A hierarchical mixture of experts (HME) framework has been viable in improving state estimation accuracy in interplanetary orbit determination problems, and this paper proposes an extension for quadcopters. It is shown that the state and motor angular velocity estimation accuracy can be significantly improved by processing different thrust models, and acoustic parameters have an important, previously unreported, role in this improvement. Higher motor angular velocities produce higher noise levels, and thus, the relationships of the onboard acoustic measurements to the vehicle state parameters play an essential part in estimation. The motor angular velocities’ estimations depend on the extended Kalman filter solutions or an acoustic curve fit. The experts in the HME framework utilize the state estimation solutions from the extended Kalman filters and the motor angular velocity estimations to compare against the telemetry data as truth. The overall HME solution is compared against a non-acoustic static thrust model. Illustrative examples and analysis presented in this paper reveal that the proposed estimation solutions can also apply to other flight vehicles for onboard real-time implementation to leverage autonomy.

Mixture of Experts for Unmanned Aerial Vehicle Motor Thrust Models

AbstractThis study aims to analyze three unmanned aerial vehicles’ static and dynamic motor thrust models and to compare them with flight test telemetry motor angular velocity data as ground truth. This comparison determines which model is the most accurate based on the root mean square of the difference between the motor models and the telemetry data values. The Burgers and Staples models are dynamic thrust models with nonlinear drag, while the Gibiansky model is a static thrust model with linear drag. The mixture of experts (MoE) architecture assigns weights to each thrust model through a gating network such that higher weights map to the more accurate models. Flight tests include two maneuvers: triangle and shoelace loop. The triangle maneuver uses the cornering option to stop and turn at each waypoint. In contrast, the shoelace loop maneuver uses the curved option to fly smooth curves at waypoints instead of stopping and turning at each waypoint. Simulation results of the motor thrust models use the telemetry data to compute the motor angular velocities with tuned model parameters tailored to the type of maneuver. Regarding motor angular velocity estimation, the Gibiansky and Burgers models tend to overestimate, while the Staples model tends to underestimate. The combination of the simulation results of the models with the mixture of experts allows us to achieve higher accuracy than any of the individual models.

Modelling and Simulation Hydrodynamics Processes in Liquefied Natural Gas Transportation Systems

Global natural gas resources are growing and are increasingly geographically diverse. A Floating Storage and Regasification Unit (FSRU) is one of the most commonly used vessel types in the global ship fleet due to the possibility of storage, reloading to another ship, and regasifying it for re-injection into the natural gas grid. It is important to control system parameters for reliable technological processes such as tank hydrostatic pressure, vapor pressure, LNG density, LNG temperature, and phase changes between liquid and gas states. Additionally, pressure monitoring is important to control during transit in port and bunkering to prevent the pressure in the tanks from exceeding the tank design pressure. In this research study, a comprehensive hydrodynamic model for an LNG storage tank in a real-life regasification terminal (Floating Storage and Regasification Unit, LNG Terminal of Klaipeda City, Lithuania), operating in transportation mode to the regasification unit, was created. For this research, LNG is investigated as a compressible liquid and the speed of sound in LNG is evaluated. A complex mathematical model of the system allows the analysis of high-speed hydrodynamic and dynamic processes at cryogenic temperature (110 K) and evaluates the geometric parameters (tank geometry, electric motors and pumps, pipe geometric parameters, and roughness of internal surfaces) and the characteristics of pumps and electric motors. The complex mathematical model of the system was implemented using Fortran programing language and MATLAB R28a. It determined the parameters (pressure, velocity, liquid level of LNG in the tanks, electric motor angular velocity, torques, hydraulic energy losses, etc.) of the system during its start-up mode (until 5 s). It was found that hydraulic energy losses in all pipes contain 1.7% of the whole system power (the total power of the electric motors is 3132 kW). In case of increasing energy costs, this model could be used to control energy losses during the operation of the FSRU in various technological modes.

Floating Microdisks Rotated by Molecular Motors

AbstractA possibility of utilization of molecular motors for creation of unidirectional rotation of tiny disks floating on a surface is considered theoretically. The bottom side of the disk is covered with grafted motors combined with flat blades submerges into a viscous liquid for torque generation. When exposes to UV‐light, the motors start to rotate all in the same direction, and they transfer their rotation to the blades creating a mechanical torque that turns the disk. The disk angular velocity scales as ω ∼ Ω L/R where Ω is motor angular velocity, L is the length of the oars, R is the micro‐disk size. A competition between directional ballistic‐type rotation and rotative diffusion is considered. The setup can be used for evaluation of the primary motor parameters: the motor rotation speed Ω = 2πf, and the maximum motor torque load Mmax.

Opening and Closing Positioning Control of the Seedling Picking-Up Mechanism Based on Fuzzy-PID Control Algorithm

The success rate of automatic transplanter seedling picking is affected by the harsh operating environment of the transplanter and the reduced output accuracy of the opening and closing positioning of the seedling-picking mechanism due to the interference of the external environment. To solve such problems, the paper proposes to use an adaptive fuzzy PID control algorithm as the opening and closing positioning-control system of the seedling-picking mechanism. Based on the theoretical analysis and calculation of the positioning accuracy of the seedling-picking mechanism, a mathematical model of stepper motor angular velocity control was established, and a stepper motor angular velocity control model based on fuzzy PID (conventional PID) control was established in MATLAB/Simulink. In order to further simulate the actual working condition of the seedling-picking mechanism, a simulation model of stepper motor control with disturbance was built, and the response results showed that the fuzzy PID control system could get rid of the disturbance faster under the action of external disturbance signals. The results of the opening and closing positioning test of the seedling-picking mechanism showed that the fuzzy PID control system has higher control accuracy and more stable control performance than the PID control system, which meets the design requirements.

Postfault Direct Field-Oriented Control of Induction Motor Drive Using Adaptive Virtual Current Sensor

Electric drives immune to failures of selected elements of the power system or measuring sensors have been the subject of research in recent years, due to the growing interest in systems with an increased level of safety. This article concerns the analysis of the direct field-oriented control induction motor drive after the failure of all stator current sensors. An adaptive virtual current sensor (AVCS) was used to estimate the stator current, based on the measurement of the motor angular velocity and the voltage in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{DC}\ (u_{\text{DC}})$</tex-math></inline-formula> of the voltage-source inverter. This article presents the possibility of improving the accuracy of stator current estimation using the original approximation of changes in rotor resistance depending on the drive operating point when the measurement information about the stator current has been lost. This approximation was determined experimentally during the normal operation of the drive using a rotor resistance estimator. The determined approximate lookup functions were used to adapt the rotor resistance in the AVCS during the drive system operation in a postfault mode. This approach has made it possible to significantly improve the accuracy of the stator current reconstruction, especially under low speeds and load torques, which was demonstrated in experimental studies <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">.</b>

Smart Anti-Pinch Window Simulation Using H-/H∞ Criterion and MOPSO

Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption, the speed and the position of DC motors. In this research, a speed-based method is used to detect the obstacles. In order to secure the anti-pinch window, an optimal algorithm based on a fault detection observer is suggested. In the residual design, the proposed fault detection algorithm uses the DC motor angular velocity rate. Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm. Finally, an optimal filter for solving the fault problem is designed using the method. The results show that the simulated anti-pinch window is pretty sensitive to the fault, in the sense that it can detect the obstacle in 50 ms after the fault occurrence.

Balancing inverted pendulum cart on inclines using accelerometers

Abstract The balance of inverted pendulum on inclined surfaces is the precursor to their control in unstructured environments. Researchers have devised control algorithms with feedback from contact (encoders - placed at the pendulum joint) and non-contact (gyroscopes, tilt) sensors. We present feedback control of Inverted Pendulum Cart (IPC) on variable inclines using non-contact sensors and a modified error function. The system is in the state of equilibrium when it is not accelerating and not falling over (rotational equilibrium). This is achieved when the pendulum is aligned along the gravity vector. The control feedback is obtained from non-contact sensors comprising of a pair of accelerometers placed on the inverted pendulum and one on the cart. The proposed modified error function is composed of the dynamic (non-gravity) acceleration of the pendulum and the velocity of the cart. We prove that the system is in equilibrium when the modified error is zero. We present algorithm to calculate the dynamic acceleration and angle of the pendulum, and incline angle using accelerometer readings. Here, the cart velocity and acceleration are assumed to be proportional to the motor angular velocity and acceleration. Thereafter, we perform simulation using noisy sensors to illustrate the balance of IPC on surfaces with unknown inclination angles using PID feedback controller with saturated motor torque, including valley profile that resembles a downhill, flat and uphill combination. The successful control of the system using the proposed modified error function and accelerometer feedback argues for future design of controllers for unstructured and unknown environments using all-accelerometer feedback.

Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation

Proton exchange membrane fuel cell (PEMFC), according to its merits of high energy density, zero emission, and low noise, has been widely applied in industrial appliances. A full bridge converter is used to implement PEMFC-powered DC motor bidirectional rotation in this paper. For the sake of the regulations of DC motor angular velocity as well as bus voltage, an adaptive backstepping sliding-mode control (ABSMC) technique integrated with Chebyshev neural network (CNN) is proposed. Based on the equivalent-circuit method, the control-oriented model of the PEMFC-powered motor system is structured. By constructing Lyapunov function, the adaptive laws and control laws can be obtained to achieve bus voltage and angular velocity regulations simultaneously. Moreover, the proposed neural network is applied to estimate the uncertainties of the system through orthogonal basis Chebyshev polynomials. To highlight the advantages of proposed technique, a proportional-integral (PI) control was introduced subsequently and two controllers were compared via numerical simulations. The simulation results demonstrate that CNN estimation method in conjunction with backstepping sliding-mode shows fast and accurate response even though the existence of system uncertainties and external disturbances.

A Rotor Flux Observer of Permanent Magnet Synchronous Motors With Adaptive Flux Compensation

Due to the influence of current sampling and current reconstruction deviation, non-linearity of the inverters and parameter variation of the motors, DC offset component and high-order harmonic components exist in flux model, which makes the estimation of traditional rotor flux observer inaccurate and even divergent. In this paper, a rotor flux observer of permanent magnet synchronous motors (PMSM) with adaptive flux compensation is proposed. The DC offset component and the high-order harmonic components with the flux integrator observer can be eliminated by fed them back to the input of the flux integrator through PI regulator, so that the output of the flux integrator observer only contains the fundamental component, thus the rotor flux can be accurately estimated. Since the parameters of PI regulator are related with the estimated motor angular velocity, the control system has good robustness in a wide speed range. The flux observer is based on the voltage model in stationary coordinate system, so it is suitable for both surface and interior PMSMs. Moreover, the control method of the whole system has less computational complexity and fewer variables, it is easy to implement on a low-cost hardware platform. Finally, the experimental results verify that the flux observer has superior performance.

PSO Fined-tuned Model-Free PID Controller with Derivative Filter for Buck-Converter Driven DC Motor

Traditionally, the PID controller parameters are tuned heuristically based on time response behavior of the system. This method is tiresome job and can cause undesirable system response. Therefore, this research suggests the tuning method of a model-free PID controller with derivative filter (PIDF) by implementing Particle Swarm Optimization (PSO). This tuning method is applied to buck-converter driven DC motor control. The speed of DC motor is controlled by PIDF controller. The parameters of PIDF controller are fine-tuned by implementing PSO algorithms. The fitness functions of the algorithm are evaluated based on Sum Square Error (SSE) and Sum Absolute Error (SAE). The state-space representation of buck-converter/DC motor is considered to confirm the design of the control method. The results of the proposed tuning method are compared with PI controller and PIDF controller tuned by PID Tuner Simulink. The time response specifications of angular velocity, armature current and duty cycle input energy are considered as a control scheme performance. Finally, the suggested tuning technique promises a very minimum duty cycle energy and a fast input tracking of DC motor angular velocity.

Advantages of fiber Bragg gratings for measuring electric motor loadings in aerospace application.

Electric motors are being investigated in-depth for their application in aerospace. Part of this investigation is the characterization of the loadings from the propulsion devices, in a stationary setup, usually accomplished through the utilization of load cells. The majority of the load cells used in this application are designed around a resistance-based strain gauge. However, electric motors radiate electromagnetic interference (EMI) when in operation, which degrades the signal retrieved through the strain gauge, due to the gauge's metallic construction acting as an antenna for the EMI. To demonstrate the advantage of fiber Bragg gratings (FBGs), with their immunity to EMI, a load cell implementing both sensor technologies was designed and subjected to the same mechanical loading and EMI, with a flywheel coupled to a brushless DC motor. The load cell had a sensitivity of 8.59 ± 0.18 N and 2.49 ± 2.49 N through the strain gauge and FBG system, respectively. The strain gauge signal contained the mechanical loading signal embedded in wideband noise and spikes (that increased linearly with motor angular velocity), while the FBG signal did not, with little noise. The raw strain gauge signal, at a maximum, had a signal power ratio (mechanical signal power divided by the overall signal power mean) of 21.06 at 104.72 rad/s; the FBG signal, at a minimum, had a signal power ratio of 40.09 at 52.36 rad/s. Therefore, on the basis of the mechanical tests performed in this work, the recommended sensor of choice for electric propulsion in aerospace applications is the FBG.

Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators

In this contribution, a gain adaptation for sliding mode control (SMC) is proposed that uses both linear model predictive control (LMPC) and an estimator-based disturbance compensation. Its application is demonstrated with an electromagnetic actuator. The SMC is based on a second-order model of the electric actuator, a direct current (DC) drive, where the current dynamics and the dynamics of the motor angular velocity are addressed. The error dynamics of the SMC are stabilized by a moving horizon MPC and a Kalman filter (KF) that estimates a lumped disturbance variable. In the application under consideration, this lumped disturbance variable accounts for nonlinear friction as well as model uncertainty. Simulation results point out the benefits regarding a reduction of chattering and a high control accuracy.

Propeller arc: design and basic characteristics

A new atmospheric pressure non-equilibrium plasma source named the ‘Propeller Arc’ (PA) is developed using the concept of rotating electrodes. The PA device consists of a rotating cathode, driven by a motor, with one or more fixed anodes. Plasma is ignited at or near the narrowest gap as the rotating cathode passes by the anode and then it is extended up to a length of ∼66 mm or longer depending on the supplied power. This allows for efficient ignition, followed by a quick increase in plasma volume. The PA is similar to the widely used gliding arc (GA); however, unlike the GA, PA does not require imposed gas flow, and the PA discharge frequency can be easily controlled by the motor angular velocity. In this paper, the basic characteristics of PA are investigated using two different operation modes: pulse modulation and DC power. Discharge properties including electrical characteristics, time-resolved optical emission images, plasma electrical properties such as resistance and average electric field (discharge voltage divided by gap distance) and plasma power consumption are reported. Use of multiple anodes to increase the plasma volume is also demonstrated. As the PA has a compact design and is relatively easy to stabilize and control without the need for applied gas flow, it has potential to be adapted for many different applications such as nitrogen fixation, fuel and carbon dioxide conversion, waste, odor and hydrogen sulfide treatment, etc.

A New “DC/DC Buck-Boost Converter‑DC Motor” System: Modeling and Experimental Validation

This work presents the modeling and validation of a bidirectional “DC/DC Buck-Boost converter‑DC motor” system. This configuration allows the change of rotation in both directions on the motor shaft. The experimental validation of the model is accomplished for time-varying duty cycles. This allows solving the trajectory tracking task in open-loop of the system. On the one hand, applying the Kirchhoff's laws along with the model of a DC motor, the mathematical model is obtained. While, the trajectory planning is carried out by expressing the system states and duty cycles in terms of the converter voltage and motor angular velocity. The validation of the deduced model is performed via Matlab‑Simulink and a DS1104 board in a laboratory prototype of the system.

Modeling and Experimental Validation of a Bidirectional DC/DC Buck Power Electronic Converter‑DC Motor System

This paper presents the modeling and experimental validation of a new topology for the DC/DC Buck power converter‑DC motor system. The main objective of this topology is to achieve a bidirectional rotation on the DC motor shaft by using a DC/DC power converter. As a result of applying Kirchhoff's current and voltage laws the system mathematical model is obtained. Also, an analysis in steady-state of the system is presented. While, the reference trajectory generation associated to the states and controls of the system (expressed in terms of the voltage converter and motor angular velocity) is performed via differential flatness, which allows a trajectory tracking control in open-loop. The experimental validation of the herein presented model is carried out by means of Matlab-Simulink, ControlDesk, and a DS1104 from dSPACE. The experimental results confirm the validity of the mathematical model, for the general case, i.e., the time-varying trajectory tracking and not only the constant trajectories case.