Narrow Results

Cerebellar Model Articulation Controller (CMAC) is a kind of adaptive ANN based on local learning, which has the characters of fast convergence speed, strong generation ability, simple structure. While its advantages over conventional control techniques have been recognized in the literature, it has primarily been in system identification and pattern recognition, but not in control application. A novel adaptive learning algorithm and concurrent control based on CMAC and PID is proposed in this paper. The proposed algorithm and controller are applied to two-order nonlinear system. The experimental and simulated results show that performance of the CMAC based controller using the proposed learning algorithm is more stable and effective than that of the conventional controllers.

Due to its varying time delay and parameters, brazing temperature control is the main difficulty in brazing operations. In order to optimize the brazing temperature, the brazing temperature model must first be established. Parameter identification and optimization are effective ways to obtain the precise temperature model of the brazing furnace. In this investigation, the online parameter identification on first order delay temperature model was proposed. Through identifying and calculating for the first order delay temperature model, the mode parameters and delay time were obtained. Next, PID parameters optimization for the traditional objective function was implemented using a genetic algorithm. The overshoot, static error index and rising time in the third stage of the heating requirements can then be controlled well, with the help of the modified objective function.

This paper introduces the PID controller based on the human simulation intelligent control algorithm and analyzes the human simulation intelligent PID control algorithm in the MATLAB simulation environment for comparison with the traditional PID control algorithm. An intelligent PID controller is designed through the simplification of the intelligent PID algorithm into a program run in single-ship. It is has improved control effects and is adaptable to standard serial communication protocol, with characteristics of cheap production and simple configuration.

Against such characteristics as uncertainty of controlled object in the main steam temperature control of thermal power plants, a novel PID control strategy with radial basis function (RBF) network tuning based on quantum-behaved particle swarm optimization (QPSO) algorithm is proposed. The QPSO algorithm is applied to optimize the initial parameters of RBF network, thus achieving dynamic control of the main steam temperature. The proposed controller has a self-learning ability, which can strengthen the system of uncertainties adaptability. Simulation results show that the control system performance is obviously better than the conventional cascade control.

Intelligent UAV(Unmanned Aerial Vehicle) as a new field of artificial intelligence and robotics technology, which has widely received attention by the domestic and foreign industries. In view of the problem of the single function and the poor stability of flight that is widely known, this paper researches on the flight attitude of UAV based on IDE Arduino development platform, and the flight stability of UAV which is optimized through the PID control algorithm and fuzzy control method. At the same time, combined with the open source of Arduino, all kinds of sensors are installed on the UAV to carry out the underlying call, and finally, to realize the intelligent and stable flight control.

A fuzzy-PID control strategy based on T-S fuzzy model is proposed by combining fuzzy control and Conventional PID control. PID controller is developed for each subsystem of T-S fuzzy model. In terms of fuzzy-control theory, each subsystem’s control law and membership function can be used to synthetically calculate the whole control system’s control law, which control the whole system. The fuzzy-PID control strategy is also applied to three-tank water level nonlinear system. The control results show the effectiveness and feasibility of the proposed method.

In order to solve the problem that the steel wire gets loose or broken in Multi-Wire-Saw when it works in a high-speed, this paper introduces a control method based on PLC and servo motor, uses the separated integral PID to control the speed of the steel wire when it’s taken on and off accurately. This method improves the stability of the system, even operating at high-speed multi-wire saw. The tension control system can also be used in papermaking, printing and packaging.

For the need of anti-wind and anti-vibration in transmission line construction and maintenance work, the design of anti-galloping fitting based on PID automatic controlling theory was introduced in this paper. Performance of this PID closed loop adjustment control was revealed as simulation results in the computer-aided software. Receiving displacement in the line from sensors in line as input signal, PID controller would compare the dynamic displacement and static one, and give position signal to the motor. Two kinds of the anti-galloping fitting had been introduced in this paper, which could make the PID principles described earlier more practical and trusted.

After more than ten years' development, the neural network PID control technology, combining intelligent control technology and traditional control theories, has got remarkable achievements both in theory and use. This paper designs the whole production line temperature computer control system; production line crystallization process temperature control adopts multilayer network approximate PID controller based on BP algorithm, which verifies the validity of the control method after simulation comparison; finally, this paper discusses the feasibility of using VB language to realize the control process in RSView32.

The Fusion Advanced Studies Torus (FAST) conceptual has been proposed as possible European ITER Satellite facility with the aim of preparing ITER operation scenarios and helping DEMO design and R&D. Insights into ITER regimes of operation in Deuterium plasmas can be obtained from investigations of nonlinear dynamics that are relevant for the understanding of alpha particle behaviours in burning plasmas by using fast ions accelerated by heating and current drive systems. In this paper the plasma scenarios that can be studied on FAST are presented, with emphasis on the aspect of its flexibility in terms of both performance and physics that can be investigated. Plasma position and shape control studies are also discussed.

The Proper Forcing Axiom is a powerful extension of the Baire Category Theorem which has proved highly effective in settling mathematical statements which are independent of ZFC. In contrast to the Continuum Hypothesis, it eliminates a large number of the pathological constructions which can be carried out using additional axioms of set theory.

The ALICE experiment is devoted to the study of heavy-ion collisions at LHC energies. ALICE is also studying proton-proton collisions both as a comparison with lead-lead collisions and in physics areas where ALICE is competitive with other LHC experiments. The ALICE-HMPID detector performs charged particle track-by-track identification (π and K in the momentum range of 1 < p < 3 GeV/c and p in 1.5 < p < 5 GeV/c) by means of measurement of Cherenkov angle and momentum information provided by the tracking devices. The current results on hadron transverse momentum spectra measured by the HMPID detector in pp collisions at , are shown.

The NA62 experiment is designed to measure the branching ratio of the decay with a 10% accuracy at the CERN SPS. To suppress the main background coming from the K⁺ → μ⁺ν decay, a Ring Imaging Cherenkov detector (RICH), able to separate π and μ in the momentum range between 15 and 35 GeV/c with a muon contamination in a pion sample < 10⁻² is needed. The RICH must also have an unprecedented time resolution (100 ps) to disentangle accidental time 115sociatioDll of beam particles with pions. The last updates of the detector layout are presented along with the results of the beam tests of the RICH prototype: the muon misidentification probability was found to be 0. 7% and the time resolution < 100 ps in all the momentum range.

The particle identification capability of the ALICE apparatus is unique among the LHC experiments as it exploits almost all known techniques. In this paper, the working principles of the relevant PID detectors in the central barrel will be discussed. A particular emphasis will be given to recent results on identified particle spectra and production yield ratios at mid-rapidity in pp, p–Pb and Pb–Pb collisions.

At present, solar collectors thermal performance testing system based on PID control algorithm was defective. In order to improve the system, a fuzzy predictive control algorithm was proposed. Firstly, the fuzzy control and predictive control were combined to adjust the actual system. Secondly, SIMULINK software was applied to establish a PID algorithm for the simulation model which was based on control algorithm and fuzzy prediction. The simulation showed that the fuzzy predictive control method was a feasible and effective approach that can improve the stability of the temperature and speed up the response speed. In the end, this novel method can improve the detection efficiency of the system.

Concerning the problems of the impact on the factors of installation about semiconductor refrigeration piece are rarely studied in China and abroad, a reasonable structure of test device is designed, using stepper motor to test the temperature of the cold surface under different stress of installation to get the best stress of installation for the semiconductor refrigeration piece. Experiments shows that the system is of good noise immunity, high controlling and measuring precision.

Firstly, the control method of elevator's synchronous motion is provided, the synchronous control structure of double servo motor based on PMAC is accomplished. Secondly, synchronous control program of elevator is implemented by using PMAC linear interpolation motion model and position error compensation method. Finally, the PID parameters of servo motor were adjusted. The experiment proves the control method has high stability and reliability.

It is difficult to establish an exact mathematical model for the induction motor and the robustness is poor of the vector control system using PI regulator. This paper adopts the linear active disturbance rejection controller (LADRC) to control inductor motor. LADRC doesn't need the exact mathematical model of motor and it can not only estimate but also compensate the general disturbance that includes the coupling items in model of motor and parameters perturbations by linear extended state observer (LESO), so the rotor flux and torque fully decouple. As a result, the performance is improved. To prove the above control scheme, the proposed control system has been simulated in MATLAB/SIMULINK, and the comparison was made with PID. Simulation results show that LADRC' has better performance and robustness than PID.