Adaptive Control Technology Research Articles

Research and Field Application of Adaptive Inflow Control Technology

In view of conventional inflow control completion technique can not control water directly, the valid production period is relatively short, the control water effect become worse after bottom water breakthrough, easily lead to reservior second damage. Based on problem above, this paper presents an adaptive inflow control well completion technology, that uses adaptive inflow control device and precision sand filtering net control water screen, realizing to adjust the resistance of oil and water automaticlly, improving infow profile and oil well recovery, moreover, the adaptive inflow control well completion technology has the features of simple construction, high reliability and strong adaptability. Therefore, from the technological principle and characteristics, key implemental technology, the tool of adaptive inflow control device and screen, construction technology and other aspects of adaptive inflow control well completion technology, adaptive inflow control well completion technology were studied. The technology was applied in horizontal well completion in the B oilfield. After application, the oil production increased by 5 times, the oil production period of low water content was prolonged 400 days, a good effect of controlling water coning and increasing oil was acheved. The application suggests that adaptive infow control well completion technology can improve the effect of inflow control screen well completion that could be applied in the wells to increase the oil production.

Crash severity effects of adaptive signal control technology: An empirical assessment with insights from Pennsylvania and Virginia

Adaptive signal control technology (ASCT) is an intelligent transportation systems (ITS) technology that optimizes signal timings in real time to improve corridor flow. While a few past studies have examined the impact of ASCT on crash frequency, little is known about its effect on injury severity outcomes. Similarly, the impact of different types of ASCTs deployed across different states is also uncertain. This paper therefore, used ordered probit models with random parameters to estimate the injury severity outcomes resulting from ASCT deployment across Pennsylvania and Virginia. Two disparate systems deployed across the two different states were analyzed to assess whether they had similar impacts on injury severity, although signal timings are optimized using different algorithms by both systems. The estimation results revealed that both ASCT systems were associated with reductions in injury severity levels. Marginal effects showed that Type A ASCT systems reduced the propensity of severe plus moderate and minor injury crashes by 11.70% and 10.36% while type B ASCT reduced the propensity of severe plus moderate and minor injury crashes by 4.39% and 6.92%. Similarly, the ASCTs deployed across the two states were also observed to reduce injury severities. The combined best fit model also revealed a similar trend towards reductions in severe plus moderate and minor injury crashes by 5.24% and 9.91%. This model performed well on validation data with a low forecast error of 0.301 and was also observed to be spatially transferable. These results encourage the consideration of ASCT deployments at intersections with high crash severities and have practical implications for aiding agencies in making future deployment decisions about ASCT.

ADAPTIVE CONTROL OF PERSONNEL RESERVE TRAINING IN INSTITUTION OF HIGHER EDUCATION

The article reveals the essence and peculiarities of the personnel reserve formation in the institution of higher education. The functionality of the personnel reserve of the modern higher school is analyzed from two viewpoints: the viewpoint of an institution of higher education (functions are information, personnel planning, resource saving, anti-crisis, regulatory) and the viewpoint of a reservist (career-orientation, motivational, developmental functions). The personnel reserve management is represented by several approaches: classical (training is tied to the competence of a particular position); the personnel reserve management in the context of the concept of talent management (development on the grounds of needs and deficits in the competence of succession pool members); synthetic (the personnel reserve is a self-organized community and a training program). The best thing is to use adaptive control technology in order to regulate relationships between members of the personnel reserve, and assist them in the implementation of professional self-development and self-improvement. Adaptive control is founded on the acme-synergic principles, as it provides favorable conditions for selforganization, self-knowledge, self-understanding, self-determination, self-prediction and self-design, self-actualization and self-realization of a person as a subject of professional activity. Main lines of work of the acme-synergic service are informational-analytical (general department); organizational-designing (prognostic department); acmeologicaltechnological (technological department); psychological (department of acme-synergic support); research (analytical department).

Overview of Model Free Adaptive (MFA) Control Technology

Model-Free Adaptive (MFA) control is a technology that has made a major impact on the automatic control industry. MFA control users have successfully solved many industry-wide control problems in various applications and achieved significant economic benefits. Now, the challenge is extending the many advantages of MFA control technology to diverse and fragmented markets, which could benefit from its unique capabilities. Since single-loop MFA controllers can directly replace legacy PID controllers without the need for "system" redesign (plugand play), they are readily embeddable in various instruments, equipment, and smart control valves. This alleviates concerns relative to cost of change and also makes MFA an appealing tool for OEM applications on a large scale.

Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data

While the operational and crash reduction benefits of adaptive signal control technology (ASCT) have long been investigated, the impact of this technology on driver behavior and stress is still uncertain. This study evaluated the impact of ASCT on driver behavior and stress in a real-world environment. Participants travelled through two arterial corridors, one equipped with ASCT and the other having traditional time-of-day coordinated signals. Driver stress was measured using a heart rate detector and a perceived stress scale while driver behavior was examined using vehicular trajectory data. Overall, driving behavior improved on the ASCT as compared to the non-ASCT corridor, as indicated by higher speeds and a fewer number of stops on the ASCT corridor relative to the non-ASCT corridor. Repeated measures ANOVA showed a statistically significant reduction in driver heart rate by −10 beats per minute over the ASCT corridor. A similar trend was observed for drivers’ perceived stress, analyzed by Wilcoxon sign ranked test. Driving behavior also showed significant improvement with ASCT presence, and speed was found to be negatively correlated with stress. Furthermore, the participants’ speed was controlled by the two systems i.e. ASCT and non-ASCT as expected. This study provides a significant proof of concept that ASCT can create positive improvements in driver stress and behavior that can be further investigated in the future.

Group multiple lags consensus of fractional-order nonlinear leader-following multi-agent systems via adaptive control

In this paper, group multiple lags consensus of fractional-order leader-following multi-agent systems with nonlinear dynamics are investigated, in which two kinds of lag consensus are considered. One is said to be outergroup lag consensus, which means that different group leaders reach lag consensus. The other one is called innergroup lag consensus, that is to say, the followers will reach lag consensus with their own group leader. Based on Mittag–Leffler stability for fractional-order systems, algebraic graph theory, a class of novel control protocols is designed and the corresponding sufficient conditions are derived to guarantee the achievement of group multiple lags consensus. Furthermore, considering parametric uncertainties, an adaptive control technology is employed to solve the group multiple lags consensus for fractional order multi-agent systems, and the corresponding adaptive control protocols and sufficient conditions are proposed. Finally, numerical simulations are given to demonstrate the effectiveness of the obtained results.

Performance of Two Advanced Rainwater Harvesting Systems in Washington DC

Combined sewer overflows (CSOs) are a concern for many cities managing stormwater through combined sewer systems, including the District of Columbia (DC). Advanced rainwater harvesting (ARH) is an innovative approach to managing stormwater and has the potential to minimize CSOs and maximize water conservation. ARH systems use continuous monitoring and adaptive control (CMAC) technology to store or release water from a rainwater harvesting cistern. This study assessed the efficacy of ARH systems to mitigate wet weather discharges at two firehouses in DC. Continuous monitoring data was collected over a period of three years for the systems that were installed in 2012. The collected data indicates that the systems were effective at mitigating wet weather discharges, with average event harvesting rates greater than 95%. These results suggest that if implemented on a larger scale, ARH systems would be a valuable tool in effectively managing stormwater.

High Precision Man-machine Collaborative Assembly System

A high precision man-machine collaborative assembly system is designed by combining the high precision detection technology, the high precision displacement technology and the adaptive control technology. It mainly consists of the assembly execution subsystem, the precise adjustment subsystem, the visual alignment subsystem, the sensor monitoring subsystem, the clamping subsystem and the auxiliary subsystem. The assembly experiment of the shaft and hole with only 3.2μm assembly gap has proved that the assembly system can accomplish the high precision assembly under the part clearances of 2-3μm. It can liberate the labor force and improve the automation of production assembly.

Estimating safety effects of adaptive signal control technology using the Empirical Bayes method

IntroductionAdaptive signal control technology (ASCT) has long been investigated for its operational benefits, but the safety impacts of this technology are still unclear. The main purpose of this study was to determine the safety effect of ASCT at urban/suburban intersections by assessing two different systems. MethodCrash data for 41 intersections from the Pennsylvania Department of Transportation (PennDOT), along with crash frequencies computed through Safety Performance Functions (SPFs), were used to perform the Empirical Bayes (E-B) method to develop crash modification factors (CMF) for ASCT. Moreover, a crash type analysis was conducted to examine the safety impact of ASCT on a regional scale and the variation of safety among type of crashes observed. ResultsThe results from this study indicated the potential of ASCT to reduce crashes since the Crash Modification Factor (CMF) values for both ASCT systems (SURTRAC and InSync) showed significant reductions in crashes. Average CMF values of 0.87 and 0.64 were observed for total and fatal and injury crash categories at a 95% confidence level, and results were consistent between systems. While a reduction in the proportion of rear end crashes was observed, the change was not determined to be statistically significant. The overall distribution of crash types did not change significantly when ASCT was deployed. Conclusion and practical applicationThe results indicate that safety benefits of ASCT were generally consistent across systems, which should aid agencies in making future deployment decisions on ASCT.

Active torque control for gear dynamic load suppression in a drum shearer cutting transmission system under impact loads

In order to suppress the impact of a loads-induced gear dynamic load of a drum shearer cutting transmission system, an active torque compensation control method is proposed in this paper based on the active disturbance rejection and adaptive neuro-fuzzy control technologies. Using the speed difference between the motor rotor and the first stage gear as a feedback state variable, an active disturbance rejection torque compensation controller is firstly designed for suppressing the dynamic load of the electromechanical transmission system. The controller uses the speed difference as the tracking control target and sets it to a zero value, thereby transforming the dynamic load suppressing problem into a trajectory tracking problem. Secondly, the active disturbance rejection controller parameters are tuned based on the adaptive neuro-fuzzy control technology. Therefore, the torque compensation can be realized adaptively in accordance with the various cutting conditions. Finally, the suppression effect on the dynamic load of the transmission system under continuous impact conditions with different load mutation rates is analyzed based on the proposed control method. Simulation results indicate that the proposed method exhibits a good control effect in suppressing the dynamic load and an improved adaptive ability to the complex and changeable working conditions. The proposed method also can be useful for the electromechanical transmission systems with similar structure applied in other areas.

Adaptive chaos control of the fractional-order arch MEMS resonator

This paper addresses adaptive chaos control issue for the fractional-order arch MEMS resonator with fully unknown function, chaotic vibration and time delay under distributed electrostatic actuation. The phase diagrams and time histories are presented to investigate characteristic of chaotic attractor for the fractional-order arch MEMS resonator. In the process of controller design, the Chebyshev neural network with a weight and fractional-order adaptive law is employed to approximate complicated unknown function. In view of more advantages in modeling the behavior of the arch MEMS resonator in contrast to integer-order calculus, the fractional-order adaptive chaos control technology by merging Chebyshev neural network and backstepping is presented to guarantee the stability based on the fractional-order Lyapunov stability criterion. Finally, simulation studies are presented to illustrate feasibility of the proposed scheme.

Adaptive finite-time outer synchronization between two complex dynamical networks with noise perturbation

In this paper, the finite-time outer synchronization between two complex dynamical networks with noise perturbation is considered. Combing the adaptive and finite-time control technologies, a novel adaptive finite-time controller is designed. Based on the finite-time stability theory of stochastic differential equations, sufficient conditions for the finite-time stochastic outer synchronization between two complex networks with identical as well as nonidentical configurations are obtained, respectively. Finally, numerical examples are examined to illustrate the effectiveness and feasibility of the theoretical results.

The application research on improvement of genetic algorithm in linear CCD detection

When the linear array image sensor (CCD) is used for spot detection, the optimization of the detection signal is usually one of the problems that plague the user. In linear array imaging sensor (CCD) detection applications, optimization of the detection signal is usually one of the problems with the user. Based on the characteristics of linear array CCD detection signal, a genetic algorithm (GA) is established to solve the problem of mathematical model. In this paper, a new adaptive genetic algorithm (IGA) with directional adaptive guidance and adaptive control technology and threshold constraint technology are proposed for the lack of local optimization ability of the standard genetic algorithm (SGA), premature convergence and low accuracy. By applying IGA to the actual detection data, it is proved that IGA has certain advantages in solving the problem of linear CCD detection signal optimization. In the end of this paper, the performance of IGA, SGA and peak finding algorithm (SP) are analyzed and compared, which fully demonstrates the advantages of IGA in solving such problems.

Improved I/O Data-Based Model-Free Adaptive Control Technology in MIMO Discrete-Time Systems

As one of I/O data-based model-free adaptive controllers, the conventional MFAC controllers only with zero-order output information of the system are widely used around the world. With the NARX model of the discrete-time system, the conventional MFAC controllers are reviewed based on some assumptions together with matrix-inversion-lemma and extreme value theory, parameter estimation method mathematically. On account of one-order output and a new weighted one-step-ahead control input cost function including one-order output, the new D-MFAC controller is obtained and its convergence is improved accordingly. Meanwhile, some simulations are made between the conventional MFAC controller and the D-MFAC controller with the same initial parameters in this paper. In result, the robust is proved and some conclusions are drawn

Research on the intelligent control technology of the uneven road omni-directional mobile robot

For the omni-directional mobile robot on uneven pavement, its variants and mutations movement control have been puzzling the researchers. An adaptive extension intelligent control technology, which combines the high precision of the adaptive control technology, fast reaction rate of the extension control technology, is used to study the three wheeled omni-directional mobile robot on uneven pavement in this paper. Through the research, the three wheeled omni-directional mobile robot’s kinematics and dynamics model have been constructed firstly. Then a kind of adaptive extension intelligent control method has been built. At last the adaptive extension intelligent controller has been designed and the experimental results have been given accordingly. The experimental results show that the three wheeled omni-directional mobile robot which has the ability of high precision, fast reaction rate, self-organizing and self-learning using adaptive extension intelligent control technology is better than using adaptive control technology. This technology can meet the requirements of three wheeled omni-directional mobile robot.

Synchronization of uncertain fractional-order chaotic systems with time delay based on adaptive neural network control

Time delay frequently appears in many phenomena of real life and the presence of time delay in a chaotic system leads to its complexity. It is of great practical significance to study the synchronization control of fractional-order chaotic systems with time delay. This is because it is closer to the real life and its dynamical behavior is more complex. However, the chaotic system is usually uncertain or unknown, and may also be affected by external disturbances, which cannot make the ideal model accurately describe the actual system. Moreover, in most of existing researches, they are difficult to realize the synchronization control of fractional-order time delay chaotic systems with unknown terms. In this paper, for the synchronization problems of the different structural fractional-order time delay chaotic systems with completely unknown nonlinear uncertain terms and external disturbances, based on Lyapunov stability theory, an adaptive radial basis function (RBF) neural network controller, which is accompanied by integer-order adaptive laws of parameters, is established. The controller combines RBF neural network and adaptive control technology, the RBF neural network is employed to approximate the unknown nonlinear functions, and the adaptive laws are used to adjust corresponding parameters of the controller. The system stability is analyzed by constructing a quadratic Lyapunov function. This method not only avoids the fractional derivative of the quadratic Lyapunov function, but also ensures that the adaptive laws are integer-order. Based on Barbalat lemma, it is proved that the synchronization error tends to zero asymptotically. In the numerical simulation, the uncertain fractional-order Liu chaotic system with time delay is chosen as the driving system, and the uncertain fractional-order Chen chaotic system with time delay is used as the response system. The simulation results show that the controller can realize the synchronization control of the different structural fractional-order chaotic systems with time delay, and has the advantages of fast response speed, good control effect, and strong anti-interference ability. From the perspective of long-term application, the synchronization of different structures has greater research significance and more development prospect than self synchronization. Therefore, the results of this study have great theoretical significance, and have a great application value in the field of secure communication.

A Review on In-situ Monitoring and Adaptive Control Technology for Laser Cladding Remanufacturing

The repair technology of metal parts is one of the important parts in remanufacturing industry, which has been recognized as playing a key role in improving manufacturing sustainability. As an effective repair technology, laser cladding remanufacturing (LCR) has been researched actively for several decades. In the meantime, the quality and repeatability of the cladding layers are still the key issues in LCR technology. This is particularly true in the remanufacturing of high-end and high-value equipment such as aircraft engines and large-scale compressors. With the development of the sensing and control system, in-situ monitoring and adaptive control (IMAC) technology has recently been received increasing attention to enhance parts quality and repeatability as a high priority research goal. This work intends to review the significant signals that can be in-situ gathered and have been published in the literatures for IMAC such as visual signal, temperature signal, acoustical signal and spectrum signal. The in-situ control methods are also discussed in the paper.

Robust cooperative path tracking control algorithm for multi-vessel

The issue of distributed cooperative path tracking control for multi-vessel in the presence of ocean currents has addressed in this article. The proposed cooperative control approach is achieved by designing the guidance system and the control system. In order to achieve the multi-vessel’s coordination with the desired spatial formation, the guidance system is designed based on the strategy of virtual leader for supplying the desire path and relevant parameters for each vessel. In addition, a robust cooperative path tracking controller is designed to reject the disturbance of unknown ocean currents using the backstepping method and the adaptive control technology. The synchronization between all the vessels is achieved by defining same path parameter and same speed along the path through the guidance system. Global asymptotic stability is guaranteed by Lyapunov-based technique for the whole control system. The effectiveness of the proposed cooperative path tracking control method is demonstrated by numerical simulation.

Research on Flight Control of Quad-rotor Based on Backstepping and Adaptive Control Technology

According to the uncertainty problem in the process of quad-rotor aircraft flight, As close to the actual flight environment, The nonlinear dynamic model of quad-rotor aircraft is established,On the basis of the backstepping, Analyzed the presence of interference control quantity expression and adaptive law.This paper puts forward a technique of backstepping and adaptive control technology,Through Matlab simulation and flight test of the designed adaptive inverse footwork the effectiveness of the proposed controller is verified, The simulation results show that the system has good robustness.

Adaptive Robust Backstepping Control of Permanent Magnet Synchronous Motor Chaotic System with Fully Unknown Parameters and External Disturbances

The chaotic behavior of permanent magnet synchronous motor is directly related to the parameters of chaotic system. The parameters of permanent magnet synchronous motor chaotic system are frequently unknown. Hence, chaotic control of permanent magnet synchronous motor with unknown parameters is of great significance. In order to make the subject more general and feasible, an adaptive robust backstepping control algorithm is proposed to address the issues of fully unknown parameters estimation and external disturbances inhibition on the basis of associating backstepping control with adaptive control. Firstly, the mathematical model of permanent magnet synchronous motor chaotic system with fully unknown parameters is constructed, and the external disturbances are introduced into the model. Secondly, an adaptive robust backstepping control technology is employed to design controller. In contrast with traditional backstepping control, the proposed controller is more concise in structure and avoids many restricted problems. The stability of the control approach is proved by Lyapunov stability theory. Finally, the effectiveness and correctness of the presented algorithm are verified through multiple simulation experiments, and the results show that the proposed scheme enables making permanent magnet synchronous motor operate away from chaotic state rapidly and ensures the tracking errors to converge to a small neighborhood within the origin rapidly under the full parameters uncertainties and external disturbances.