Wen Yu's Laboratory

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1. 3D crane system. It is a real-time MIMO nonlinear control system. It has 3 control DC motors and 5 position measuring wheel encoders (3 positions and 2 angles). The encoders measure movements with the high resolution equal to 4096 pulses per rotation (ppr). The hardware power interface amplifies the control signal which goes from the PC to the DC motors, and converts the encoders pulse signals to digital 16-bit form to be read by the computer. The control computer communicates with the hardware interface by a RT-DAC4 PCI board (incremental encoders inputs and PWM outputs). The computer is AMD 450MHz. .The operation envirment is: Windows 98, Maltab 5.3, Simulink 4.0, Real-Time Workshop 5.0, Real-time Windows Target 2.0 and Watcom 11.0.


2. Ball and beam system. It is a real-time SISO nonlinear control system. In this experiment, a ball is free to roll along the track of a beam. Transducers on the ball and beam continuously detect the ball position and the beam angle of the track. The control problem involves moving the ball from one position on the track to another by controlling the track angle. It has 1 output and 2 inputs. A/D and D/A are realized by a RT-DAC4 PCI board. The computer is Pentium III 500MHz. The operation envirment is: Windows XP, Maltab 6.5, Simulink 5.0, Real-Time Workshop 5.0, Real-Time Windows Target 2.2 and Visual C++ 6.0.


3. Synchronization of two ball and beam systems. Ball and beam system is one of the most popular and important laboratory models for teaching control system. There are two problems for ball and beam synchronized control: 1) many laboratories use simple controllers such as PD control, and theory analysis is based on linear models, 2) nonlinear controllers for ball and beam system have good theory results, but they are seldom used in real applications. We first use PD control with nonlinear exact compensation for the cross-coupling synchronization. Then a neural network is applied to approximate the nonlinear compensator. The synchronization control can be in parallel and serial forms


4. 3-D vision system. In general, recognition of 3D object requires two or more appropriately defined 2D images. In on-line application, these methods are often subject to one or more limitations. There is a difficulty in finding the correspondence between one image and the others. A trade-off between efficiency and accuracy is often necessary, so that sufficient accuracy can be achieved while avoiding large computational overhead. We show that having an well-known initial conditions of a scene it is possible to determine stereo correspondence from two images using a new geometric model, these algorithms process the images quickly and efficiently.


5. Magnetic Levitation System. Magnetic levitation has been successfully implemented for many applications. Recently, much effort has been directed toward the area of the disturbance suppression within the magnetic levitation systems. But the control results are not satisfied. Because they need disturbance model, and it is unknown. The main objects of this project are 1) modeling of magnetic levitation system, and 2) neural control for magnetic levitation system.


6. Active Structural Control with Stable Fuzzy PID Techniques. Active vibration control of building structure can reduce the vibration by 60%-80%. It is more effective than the widely implemented passive anti-seismic systems. Recently, some practical applications of active vibration control of buildings are reported. Also many advanced control and measurement techniques can be applied to active structural control, and impove the active vibration control. It gives detail discussions on how to use intelligent techniques to measure the displacements of the building, and to control the active devices. We first propose use offset cancellation and high-pass filtering techniques to solve common problems of the building displacement mesaurement via accelerometers. Then we analyze the most popular control algorithms in industrial, PD/PID controllers. After we combine industrial PID control with fuzzy compensation. The stability is proven with standard weights training algorithms. These conditions give explicit selection methods for the gains of the PD/PID control. Finally, fuzzy logic and sliding mode control are applied to the structural vibration control. Experimental studies on a two-story building prototype with the controllers are addressed.


7. Bidirectional Modeling and Structural Control for earthquake. It is on building structure modeling and control under bidirectional seismic waves. It focuses on different types of bidirectional control devices, control strategies, and bidirectional sensors used in structural control systems. It uses various issues like system identification techniques, the time-delay in the system, estimation of velocity and position from acceleration signals, and optimal placement of the sensors and control devices. The importance of control devices and its applications to minimize bidirectional vibrations is also needed



8. Modular Design and Control of an Upper Limb Exoskeleton. We use modular design method to construct an upper limb exoskeleton. This new design method is more simple and easy for exoskeletons than the other techniques, and it is facility to be extended into more joints robots. We also propose a novel admittance control, which works in task space. The admittance control has PID form, and does not need the inverse kinematic and the dynamic model of the exoskeleton. The experimental results show that both the design and the controller work well for the upper limb exoskeleton.


9. Impedance and Admittance Control Human-robotic systems include interaction between human operators and robots. They should be designed with careful consideration for the dynamic property and control ability of a human operator. This proposal performs manual tracking control tests on a human-robotic system using an impedance and admittance controlled robot, and investigates control characteristics of a human operator according to the robot impedance properties.


10. Set Membership Method for Simultaneous Localization and Mapping (SLAM) The extended Kalman filter (EKF) SLAM requires the uncertainty to be Gaussian noise. This assumption can be relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and online problems. In this project, we use ellipsoid algorithm for solving SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAMs, in noise condition, online realization, and large-scale problem. By bounded ellipsoid technique, we analyze the convergence and stability of the ellipsoid SLAM. Simulation and experimental results show that the proposed ellipsoid SLAM is effective for online and large-scale problems such as Victoria Park dataset.


11. Tacking Control of Human-Robotic Systems (Upper Limb Exoskeleton )



12. Bilateral symmetric rehabilitation with haptic robots. Human brain has self-organization capability after paralysis caused by stork. This needs neuro-rehabilitation for stroke-patients. Recently, robotic technology is successfully applied in the rehabilitation. Most of robot rehabilitation devices are in 2-dimension, and do not have feedback from the environment. The rehabilitation effectiveness is not so good. In this project, we design a 3-demension rehabilitation system, which has force feedback. The patients have one more training dimension and one more sense (haptic feeling). The neuro recovery time is less than the other robot rehabilitation methods.

13. Teleoperation


This lab was founded by CONACyT and CINVESTAV-IPN.