Time Of Transition Process Research Articles

Most probable path of an active Brownian particle.

In this study, we investigate the transition path of a free active Brownian particle (ABP) on a two-dimensional plane between two given states. The extremum conditions for the most probable path connecting the two states are derived using the Onsager-Machlup integral and its variational principle. We provide explicit solutions to these extremum conditions and demonstrate their nonuniqueness through an analogy with the pendulum equationindicating possible multiple paths. The pendulum analogy is also employed to characterize the shape of the globally most probable path obtained by explicitly calculating the path probability for multiple solutions. We comprehensively examine a translation process of an ABP to the front as a prototypical example. Interestingly, the numerical and theoretical analyses reveal that the shape of the most probable path changes from an I to a U shape and to the ℓ shape with an increase in the transition process time. The Langevin simulation also confirms this shape transition. We also discuss further method applications for evaluating a transition path in rare events in active matter.

Electronic Expansion Valve Experimental System Debugging Solution Based on PI Control Algorithm on Single-Tube Heat Exchange Experimental Platform

In this paper, the electronic expansion valve (EXV) on the single-tube heat exchange experimental platform was used as a research object. Firstly, the EXVs were selected according to the experimental requirements, and the functional parameters were set. Subsequently, the effective opening ranges of the EXVs were determined by manual control, and the control effects of the EXVs installed at the front and back ends of the test section were compared. Finally, by self-tuning and optimizing the best response curves, the proportional and integral coefficients suitable for the experimental platform were obtained; thus, the automatic intelligent control of EXV based on the proportional integral (PI) control algorithm was realized. From setting EXV functional parameters to realizing PI control, an appropriate experimental system-debugging solution for the whole process could be obtained. Based on the solution, the system stability could be improved, and the transition process time could be shortened. Furthermore, the solution also provided a method to guarantee the accuracy of experimental data and could be applied to the debugging of similar experimental systems.

NUMERICAL METHOD FOR CONTROLLING THE DYNAMICS OF ROTATION MOTION OF A MULTIROTOR UNMANNED AERIAL VEHICLE

There is a numerical method presented that makes it possible to ensure the smoothness of the forming function defining the rotational motion of a multirotor unmanned aerial vehicle. Behavior of the generating function at the final integration step is investigated. The proposed method provides the formation of a rotational motion limited by the value of angular velocity with specified angular acceleration parameters. The numerical method was simulated when forming a virtual control signal for back-stepping control. The results of simulating the response to a step signal showed a decrease in consumed energy, an effective limitation of angular velocity and a significant decrease in the peak power consumption compared to the original back-stepping method with a slight increase in the transition process time. The values of virtual control parameters which ensure the formation of specified dynamic characteristics of the rotational motion of multirotor unmanned aerial vehicle were selected.

Fuzziy Digital Filter for Robotic Manipulator Operation

In this article it is described the operation principle of a robotic manipulator ARMino device and the connection diagram of its electrical components. The device includes: An Arduino Mega control board, four servos, four potentiometers, a prototyping board, a computer. Turning the shafts on the potentiometer adjusts the position of the servo spindles. When the voltage on the potentiometer’s pin changes, the voltage at the analog inputs of the microcontroller changes. Then, in the microcontroller, the voltage is scaled to the value of the servo rotation angle. After that, the joints of the robotic manipulator are rotated. During the operation of the ARMino robotiсarm, a contact bounce problem appeared, significantly reducing the accuracy of positioning and the smooth movement of the ARMino joints. To solve this problem, a digital filter was developed. This article describes the digital filter working algorithm, which consists of four steps. One of the steps consists on finding the digital filter coefficients, which regulate the signal voltage level transmitted to the servo motors, and its transition process time which forms the signal edge. The main problem developing a digital filter is that the standard procedure of finding the digital filter coefficients, the coefficients are given by a recommended range of values, which complicates choosing from this range, a single value and transmitting it to the servos. To solve this problem, a fuzzy digital filter was developed, the algorithm of which consists of six steps. The first step determines the input variables degree of truth. The second step is to calculate the degrees of truth of the fuzzy rules preconditions. The third step is to calculate the degrees of truth of the fuzzy rules conclusions by using the process of finding the maximum values. The fourth step is the defuzzification stage in which a precise value of the fuzzy digital filter coefficient is calculated. The fifth step is the output voltage transmitted to the servos. In the sixth step, the output voltage in the microcontroller is converted to the angle value and the servo is given the command to rotate. This article presents numerical simulation of the fuzzy digital filter algorithm, using as an example the servo responsible of the ARMino base rotation. Experimental studies on the functioning of the fuzzy digital filter have been carried out, confirming the expediency of its use. The graphics of the transition process of the robotic manipulator base movement without and with the use of a digital filter are given.

Suboptimal Control of Nonlinear Dynamic System with Unlimited Transition Process Time

Abstract In this paper, we consider the issue of synthesizing optimal control of nonlinear dynamic systems in case of a problem with an unspecified time of the transition process. To solve this problem, an algorithmic method for constructing a suboptimal control is suggested. The basis of this method is the behavior of the Hamiltonian on the optimal trajectory, which corresponds to the required condition of the optimal system. For the synthesis of suboptimal control, the original nonlinear model is replaced by an equivalent model with a linear structure with state-dependent parameters. The use of the quadratic quality functional allows to make the transition from solving the Hamilton-Jacobi-Bellman equation to the Riccati-type equation with state-dependent parameters. A computer simulation of a simple nonlinear system, for which the Riccati equation with state-dependent parameters can be solved, has been carried out. Also, for this system a suboptimal control was created with the use of a new algorithmic parametric optimization method. The simulation results confirm the effectiveness of the method. In addition, the constructed suboptimal control is close to the control obtained by solving the Riccati equation.

Recurrence network analysis for uncovering dynamic transition of thermo-acoustic instability of supercritical hydrocarbon fuel flow

Characterizing the transition of thermo-acoustic instability of supercritical hydrocarbon fuel flow is a fundamental problem eliciting a great deal of attention from different disciplines. We experimentally and theoretically investigate the transition process between thermo-acoustic stability and instability. The method of recurrence network is applied to analyze the pressure time series of supercritical hydrocarbon fuel flow. As a result, we can distinguish a thermo-acoustic transition process from normal signals by real-time detecting the complexity variation of pressure signals of fuel in cooling channels with the recurrence network method. Then, we construct the recurrence network from experimental data under the stable, transition and unstable states, and investigate the degree distribution and motifs distribution. We find that the degree distribution and motifs distribution allow quantitatively uncovering the complexity dynamic process. We investigate the during time of transition process, and find that the mass flow rate and the inlet pressure will make an influence on the transition time. These findings present a first step towards an improved understanding on the transition of thermo-acoustic instability from a complex network perspective. Moreover, the investigation on the transition of thermo-acoustic instability under supercritical pressure condition offers guidance on the control of scramjet fuel supply, which can secure stable fuel flowing in regenerative cooling system.

Applying a neural tuner of the PI­controller parameters to control gas heating furnaces

In order to optimize the quality of transition processes on a heating object of control, it is proposed to apply a neural-network tuner, which changes parameters of the PI-controller in real time. The aim of present study is to determine effectiveness of application of the tuner using a model of the heating furnace, containing a gas supply control circuit and a controlling element of this circuit. Simulation was performed on the model of a gas furnace obtained through recalculation of thermal power from the model of an electric furnace. The study confirms the capability of the proposed adaptive system to effectively execute adaptation of parameters of the controller in the presence of a controlling mechanism whose dynamics may negatively affect the quality of control.The result of applying the tuner is a decrease in the time of transition process by 25.8 % and a reduction in the total controlling influence by 22.85 %. The presence of the controlling element in this case had no significant effect on the work of a neural-network tuner. The result of research makes it possible to extend the class of objects for which a neural-network tuner can be applied. Previously, the tuner demonstrated its effectiveness only for electric furnaces where influence of the controlling element is minimal. Result of the present study makes it possible to scale up the solution for gas thermal furnaces despite a markedly greater influence of the controlling element

Study on maintaining formations during satellite formation flying based on SDRE and LQR

Abstract Due to the influence of various perturbations of space, satellites flying in formation cannot maintain specific configurations for long durations [1, 2]. In order to ensure that formation configurations are able to meet the requirements of space missions, it is important to maintain control of formation configurations. This is an urgent problem to be solved. The traditional control method for controlling formations is based on the average orbit element, and uses the assumption that the average orbit element deviation and the instantaneous orbit element deviation are approximately equal. However, the continuous control system is more difficult to achieve in engineering practice. Using a LQR (linear quadratic regulator) optimal control algorithm and SDRE (state-dependent Riccati equation) optimal control algorithm to maintain the formation flying [3, 4]. Through simulation, it was found that when using the SDRE controller in the system transition process time is shorter than when the LQR controller is used, and fuel consumption is less for the SDRE controller than for the LQR controller.

Synthesis of searchless adaptive system based on lyapunov function using state observer

Searchless adaptive control system was studied and synthesized based on a Lyapunov function by a transient object under noisiness of measured values using state observer. The system adapts to the control object, regardless of whether the control object has static or dynamic characteristics. Additionally, the noise effect on the adaptive system behavior in the long run was investigated. The designed adaptive inference correction controller allows to adjust the control object inference and eliminates the static error of inference. State observer, which is based on the reference model restores the control object state vector. Even with significant object root deviations and random variables, adaptive system adapts the control action values and sets the control object inference to the desired value with the desired transition process time. The model was developed in the MATLAB/Simulink software package. Based on simulation, study of efficiency of the proposed model with different changes in the control object parameters was carried out.

Research on Control of Heat Flux Environment Simulation for High-Speed Aircraft

The characteristics of the transient heating control process of aerodynamic simulation experiments are complicated, transient, highly nonlinear, and strongly coupled, which make it difficult or impossible to develop a mathematical model. By using the fuzzy control method, many good qualities (such as robustness, high adaptability to changing parameters, and a short transition process time) can be obtained. Based on the fuzzy control method, a transient aerodynamic heating simulation control system for missiles was established. It was demonstrated that quick dynamic control of the aerodynamic simulation heating process according to the transient and continual change in heat flow on the surface of high-speed aircrafts can be completed by using this control system.