Advanced Engineering Forum Vols. 2-3

Abstract: This study is aimed at stabilizing a three dimensional biped passive walker in various environments and achieving climbing and turning control. The novel control method synchronizes a period of the changing motion of the stance leg in frontal plane (frontal motion) with a period of the swing leg by periodic input in order to stabilize the three dimensional passive walker. A mechanical oscillator is utilized to change the period of the frontal motion. The target path of the oscillator is automatically generated based on frequency entrainment in order to adjust the period of the frontal motion. In the climbing and turning control of the passive walker, the amplitude and the phase generating algorithm of the target path of the oscillator are improved. It is analytically demonstrated that the biped passive walker can be stabilized even in climbing and turning.

Abstract: The paper describes the composition and working principle of the mold oscillation control system. The mathematical model of hydraulic servo control system is established. The total system transfer function is established by MATLAB program. By using the SIMULINK module, we determined various components’ parameter values. We got different simulation curves and Bode plots by inputting non- sinusoidal function and carrying out the dynamic simulation to the mold oscillation mathematical model, we also analyzed stability of the whole system to verify the accuracy of system design.

Abstract: During the reactive sputtering process, due to the hysteresis effect, the sputtering state should be maintained in the transition region of the hysteresis curve which can used to obtain stoichiometric compound films at a high deposition rate. If sputtering state changes, it is impossible to make the sputtering state step back to the original point by manually control the process parameters, because the hysteresis is irreversible. Thus it requires a method of fast feedback to control the sputtering power and the reaction gas flow rate into the chamber. In this paper the PEM (plasma emission monitor) control system and the single neuron self-adaptive PID algorithm have been designed to maintain the sputtering state in proper condition, namely preventing the target from poisoned in the reactive sputtering. The signal acquisition and the controller design were the major parts of the PEM system. The signal acquisition was realized by the optical emission spectrometer. And the single neuron self-adaptive PID controller has been designed in the paper. Using the MATLAB software, the simulation experiments have been done. The output waveforms showed that using traditional non-adaptive PID control algorithm, the overshoot is over 6% and the regulation time is over 1.8s, but using single neuron self-adaptive PID algorithm the overshoot 0 and regulation time 0.5s. Monitoring the target spectral intensity at various reaction gas flow rate, several conclusions could be obtained. The overshoot 6% indicated that the reactive gas flow into the chamber was excessive, the target was poisoned and the sputtering state in chemical mode. And while the overshoot was zero which indicated that the target poisoned was avoided and the reaction ran in defined condition. The PEM using the single neuron self-adaptive PID algorithm responded faster than that using the traditional PID algorithm. The PEM system designed in the paper can effectively avoid the target poisoned and make the reactive sputtering maintain at an ideal state.

Abstract: In the rolling process, serious deviation will cause product quality drop and rolling equipment fault. This reserch propose tail deviation’s predictive control method of the tandem rolling strip based on manifold learning. Based on real deviation data in the rolling production site,tail deviation patterns are divided according to deviation’s value. Using manifold learning method to deviation data in middle rolling stage , tail deviation pattern and scope are obtained. According to regression model between the control variable and deviation, predictive control strategy of the tandem rolling strip may be implemented. Experiment shows this method may control tail deviation in preconcerted permission range.

Abstract: This research aims at the retention of the stability of arcs in twin-arc pulsed metal active gas welding process. That is, a correction-factor fuzzy logic controller (FLC) is designed to keep the stability of arcs of twin-arcs pulsed metal active gas welding (MAG) process. In the controller, the peak arc voltage of the master welding power is controlled by the pulse base time with means of feed back of arc voltage. The peak arc voltage of slave welding power is controlled by the wire feeding speed with means of feed back of peak arc voltage. The adjusting fuzzy control rule with correction factor is introduced to design for controlling rule and table, and the FLC is realized in a Look-Up-Table (LUT) method. With the controller, the arc length can be kept stable in welding process. Experimental results are provided to confirm the effectiveness of this approach.

Abstract: In this paper the control of the I-PENTAR, a wheeled inverted pendulum type robot being developed by the authors, for pushing and pulling a cart is examined. To control the movement of the object is being pushed or pulled, information regarding several external parameters, eg. Mass of the object and friction components, must be considered. In most cases these parameters are not known before hand or may change. One method of compensating for these unknown or changing external parameters is to represent them as an equivalent reaction force from the object. Our first subject of this research is to design a disturbance observer to estimate and compensate the equivalent force. Another situation is of pushing and pulling a cart with the inverted pendulum type robot traversing an inclined plane. As an initial step to solving this problem in this paper, a force application method using whole body motion of the inverted pendulum type robot is proposed. The whole body motion means changing the balance of the robot to attain a certain desired force. During application of this force the robot must remain in its stabilized or balanced state. For an inverted pendulum type robot, this instantly poses a major problem. To solve the problem, a reduced order disturbance observer is used in this paper to estimate the force applied by the robot. On the other hand, I-PENTAR is targeted for environments where it can interact with humans and so safety is a major concern. For example, in the event that an obstacle bumps the robot as it is pushing the cart, a large and sudden force estimator based on the disturbance observer is also built into the controller. Simulation and experiments using the reduced order disturbance observer and evaluation of the whole body motion force control are presented.

Abstract: The greenhouse control system for educational purpose is designed by personal computer. This system should observe and control the growth conditions for crops in both plastic film and glass greenhouses. In this contribution puts emphasis on construction of greenhouse control system by personal computer under the aim of creating safer, more effective and more economical services. This system is developed for the requirements of the intelligent greenhouse control system and is powered by solar energy. A photovoltaic system with sun tracking module is used for the greenhouse control system.

Abstract: In this paper, we consider a control problem of a ball and beam system with sensor noise on feedback sensor. If sensor noise exists in sensor's signal, it can make feedback signals deformed and then it can lead to control performance degradation or even system failure. Therefore, we need to design a robust controller to deal with the possible sensor noise in the feedback information. We develop an output feedback controller with a gain-scaling factor in order to minimize the effect of AC sensor noise in output feedback information. Our proposed controller is applied to a ball and beam system and verified by analysis and simulation. As a result, our controller reduces the effect of sensor noise to arbitrarily small by increasing a gain-scaling factor.

Abstract: As one kind of reinforcement learning method, Q learning algorithm has already been proved to achieve many significant results in traffic signal control area. However, when the state of Markov Decision Process is very big or continuous, the computation load and the memory load will become very big and can not be solved then. Therefore, this paper proposed a neural network based Q learning algorithm to solve this problem known as “Curse of Dimensionality”. This new method realized generalization of conventional Q learnig algorithm in huge and continuous state space as neural network is a very effective value function approximator. Experiment has been implemented upon an isolated intersection and simulation results show that the proposed method can improve the traffic efficiency significantly than the conventional Q learning algorithm.

Abstract: In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.