A Simulation and Experimental Study on Identification of an Electromechanical System

The current applications in electromechanical energy conversion demand highly accurate speed and position control. For this purpose, a better understanding of the motion characteristics and dynamic behavior of electromechanical systems including nonlinear effects is needed. In this paper, a suitable model of Permanent Magnet Direct Current (PMDC) motor rotating in two directions is developed for identification purposes. Model is parameterized and identified via simulation and using real experimental data. Linear and nonlinear models for the system are built for identification, and the effective nonlinearities in the system, which are Coulomb friction and dead zone, are integrated into the nonlinear model. A Weiner- Hammerstein nonlinear system description is used for identification of the model. MATLAB is selected as the investigating tool, and a simulation model is used to observe the error between the simulated and estimated outputs. Identification of the linear and nonlinear system models using experimental data is performed using the least squares (LS) and recursive least squares (RLS) methods. Performance of the model and identification method with the real time experiments are presented numerically and graphically, revealing the advantages of the proposed nonlinear identification approach.

Effects of Barrier Stiffness on Debris Flow Dynamic Impact—I: Laboratory Flume Test

Debris flows often cause local damage to engineering structures by exerting destructive impact forces. The debris-flow–deformable-barrier interaction is a significant issue in engineering design. In this study, a large physical flume model test device was independently designed to repeatedly reproduce the flow and impact process of debris flow. Three physical flume tests were performed to investigate the effect of barrier stiffness on the debris flow impact. The flow kinematics of debris flow with three barrier stiffness values are essentially consistent with the process of impact–run-up–falling–pile-up. The development of a dead zone provided a cushion to diminish the impact of the follow-up debris flow on the barrier. The peak impact forces were attenuated as the barrier stiffness decreased. The slight deflections of a deformable barrier were sufficiently effective for peak load attenuation by up to 30%. It showed that the decrease of the barrier stiffness had a buffer effect on the debris flow impact and attenuated the peak impact force. And with the decrease of the barrier stiffness, when the barrier was impacted by the same soil types, the recoverable elastic strain will be larger, and the strain peak will be more obvious.

Command-Filtered Adaptive Neural Network Backstepping Quantized Control for Fractional-order Nonlinear Systems with Asymmetric Actuator Dead-zone via Disturbance Observer

An adaptive neural network (NN) backstepping quantized control based on command filter and disturbance observer is proposed for fractional-order nonlinear systems with asymmetric actuator dead-zone and unknown external disturbance in this paper. An adaptive NN mechanism is designed to estimate unknown functions, and a command filter is introduced to estimate the virtual control variable as well as its derivative, so the ``explosion of complexity" issue can be avoided existed in the classical backstepping method. To handle the unknown external disturbance, a fractional-order disturbance observer is developed. Moreover, a hysteresis-type quantizer is used to quantify the final input signal to overcome the system performance damage caused by the actuator dead-zone. The quantized input signal can ensure that all the involved signals keep bounded and the tracking error converges to an arbitrarily small region of the origin. Finally, two examples are presented to verify the effectiveness of the proposed method.

Numerical analysis and optimization of key parts in the stirred tank based on solid-liquid flow field

In order to further improve the mixing performance of the mixing device, the structure of the agitator was optimized, and the effects of the diameter and pitch of the agitator on the solid-liquid suspension characteristics were analyzed by single factor method. Multiple reference frame (MRF), computational fluid dynamics, Euler multiphase flow model and standard K- ε turbulence model were used to investigate the effect of the height from the bottom of the agitator on the suspension characteristics of particles in the agitator was studied. The results show that reducing the height from the bottom of the agitator can promote the suspension of particles at the bottom of the tank, but too low height from the bottom will easily produce mixing dead zone at the bottom of the tank, and cause the accumulation of particles. Reducing the height of the agitator from the bottom will enlarge the clear liquid area of the flow field, cause uneven particle distribution and increase the stirring torque. With the increase of agitator diameter, the critical suspension speed of the flow field decrease, but the stirring power required by the flow field increase. Increasing the blade spacing in a certain range can promote the suspension of particles and make the distribution of particles in the flow field more uniform. Therefore, the mixing power and the uniformity of particle concentration distribution need to be considered together in order to make the mixing device more efficient and energy-saving.

Enhancement of the Moving Horizon Estimation Performance Based on an Adaptive Estimation Algorithm

Although moving horizon estimation (MHE) is a very efficient technique for estimating parameters and states of constrained dynamical systems, however, the approximation of the arrival cost remains a major challenge and therefore a popular research topic. The importance of the arrival cost is such that it allows information from past measurements to be introduced into current estimates. In this paper, using an adaptive estimation algorithm, we approximate and update the parameters of the arrival cost of the moving horizon estimator. The proposed method is based on the least-squares algorithm but includes a variable forgetting factor which is based on the constant information principle and a dead zone which ensures robustness. We show by this method that a fairly good approximation of the arrival cost guarantees the convergence and stability of estimates. Some simulations are made to show and demonstrate the effectiveness of the proposed method and to compare it with the classical MHE.

Sliding Mode Control for a DC Motor System with Dead-Zone

Due to the simple structure of DC motors, the natural decoupling between torque and speed, and its low cost the DC motors have been widely used in electromechanical systems, the paper deals with the experimental method of DC motor Coulomb friction identification that caused the dead nonlinear zone and proposed a nonlinear model of the DC motor, then a sliding mode strategy is developed to control the DC motor in high and low speed for bidirectional operation, The experimental implementation using Dspace 1104 demonstrate that the proposed sliding mode control can achieve favorable tracking performance against non-linearities for a DC motor.

Improved Nonlinear Extended State Observer-Based Sliding-Mode Rotary Control for the Rotation System of a Hydraulic Roofbolter

This paper develops a sliding-mode control with an improved nonlinear extended state observer (SMC-INESO) for the rotation system of a hydraulic roofbolter with dead-zones, uncertain gain, and disturbances, with the purpose of improving tracking performance. Firstly, the rotation system is modeled to compensate for dead-zone nonlinearity. Then, we present an improved nonlinear extended state observer to estimate disturbances of the rotation system in real time. Moreover, a proportional-integral-differential sliding-mode surface is introduced and an improved sliding-mode reaching law is designed. Based on this, a sliding-mode control law is developed. In order to eliminate the influence of estimation error and uncertain gain, we design two adaptation laws based on the sliding-mode surface and the estimated states. Finally, the effectiveness of the proposed SMC-INESO is verified through comparative simulation studies.

Trajectory Tracking of Autonomous Ground Vehicles with Actuator Dead Zones

This paper investigates the trajectory tracking problem of autonomous ground vehicles (AGVs). The dynamics considered feature external disturbances, model uncertainties, and actuator dead zones. First, a novel time-varying yaw guidance law is proposed based on the line of sight method. By a state transformation, the AGV is proved to realize trajectory tracking control under the premise of eliminating guidance deviation. Second, a fixed time dead zone compensation control method is introduced to ensure the yaw angle tracking of the presented guidance. Furthermore, an improved fixed-time disturbance observer is proposed to compensate for the influence of the actuator dead zone on disturbance observation. Finally, the trajectory tracking control strategy is designed, and simulation comparison shows the effectiveness of the compensate method. The CarSim–MATLAB cosimulation shows that the proposed control strategy effectively makes the AGV follow the reference trajectory.

Subcritical and supercritical granular flow around an obstacle on a rough inclined plane

A blunt obstacle in the path of a rapid granular avalanche generates a bow shock (a jump in the avalanche thickness and velocity), a region of static grains upstream of the obstacle, and a grain-free region downstream. Here, it is shown that this interaction is qualitatively altered if the incline on which the avalanche is flowing is changed from smooth to rough. On a rough incline, the friction between the grains and the incline depends on the flow thickness and speed, which allows both rapid (supercritical) and slow (subcritical) steady uniform avalanches. For supercritical experimental flows, the material is diverted around a blunt obstacle by the formation of a bow shock and a static dead zone upstream of the obstacle. Downslope, a grain-free vacuum region forms, but, in contrast to flows on smooth beds, static levees form at the boundary between the vacuum region and the flow. In slower, subcritical, flows the flow is diverted smoothly around the dead zone and the obstacle without forming a bow shock. After the avalanche stops, signatures of the dead zone, levees and (in subcritical flows) a deeper region upslope of the obstacle are frozen into the deposit. To capture this behaviour, numerical simulations are performed with a depth-averaged avalanche model that includes frictional hysteresis and depth-averaged viscous terms, which are needed to accurately model the flowing and deposited regions. These results may be directly relevant to geophysical mass flows and snow avalanches, which flow over rough terrain and may impact barriers or other infrastructure.