Proportional And Derivative Research Articles

자율주행 이동로봇의 실시간 장애물 회피 및 안드로이드 인터페이스 구현

In this paper we present an real-time obstacle avoidance technique of autonomous mobile robot with steering system and implementation of user interface for mobile devices with Android platform. The direction of autonomous robot is determined by virtual force field concept, which is based on the distance information acquired from 5 ultrasonic sensors. It is converted to virtual repulsive force around the autonomous robot which is inversely proportional to the distance. The steering system with PD(proportional and derivative) controller moves the mobile robot to the determined target direction. We also use PSD(position sensitive detector) sensors to supplement ultrasonic sensors around dead angle area. The mobile robot communicates with Android mobile device and PC via Ethernet. The video information from CMOS camera mounted on the mobile robot is transmitted to Android mobile device and PC. And the user can control the mobile robot manually by transmitting commands on the user interface to it via Ethernet.

Enhancing tilt range of electrostatic torsional micromirrors using robust adaptive critic-based neurofuzzy control

Electrostatic torsional micromirrors, as instances of Micro Electro Mechanical Systems (MEMS), have many optical network applications; such as optical wavelength-selective switches, optical cross-connects, etc. For all these applications, the micromirror needs to have minimal overshoot and settling time in order to minimize the time between two successive switching operations. Moreover, the controllability and stability of a torsional micromirror are major challenges due to high nonlinearities in its dynamic characteristics.In this paper, a robust adaptive critic-based neurofuzzy controller is proposed for electrostatic torsional micromirrors, which can improve the performance of the mirror tilting and enhance the robustness of the system to any stochastic perturbations. Furthermore, utilizing this adaptive neurofuzzy controller, which is based on a proportional and derivative (PD) critic, the micromirror “pull-in” phenomenon is crucially eliminated. Thus, the mirror tilting range is significantly expanded. Moreover, the stability of the closed-loop system is guaranteed via the Lyapunov theorem.The robust adaptive critic-based neurofuzzy controller is simulated for a 1-DOF electrostatic torsional micromirror and the results show the effectiveness of this approach for various tilt ranges and conditions. In addition, the robustness of this controller is examined in the presence of input noises and parameter uncertainties.

Native American Healing: A License to Practice?

This paper discusses a PD(Proportional and Derivative) feedback loop design method from single-shot input and output data based on FRIT(Fictitious Reference Iterative Tuning), and also discusses an estimation method for the process model and a design application for a MD-PID (Model Driven) control system and a TDOF(Two Degrees Of Freedom) PID control system. Numerical examples show the effectiveness of the approach.

From FRIT of a PD feedback loop to process modelling and control system design

This paper discusses a PD(Proportional and Derivative) feedback loop design method from single-shot input and output data based on FRIT(Fictitious Reference Iterative Tuning), and also discusses an estimation method for the process model and a design application for a MD-PID (Model Driven) control system and a TDOF(Two Degrees Of Freedom) PID control system. Numerical examples show the effectiveness of the approach.

Balancing of an Inverted Pendulum Using PD Controller

Balancing of an inverted pendulum robot by moving a cart along a horizontal track is a classical problem in the field of Control Theory and Engineering, for the beginners to understand its dynamics. Several physical models can also be simplified as elastic inverted pendulums like rockets and walking robots. Many researchers have been applying different control algorithm and design techniques such as PID Controller, State Space, Neural Network, Genetic Algorithm (GA) even Particle Swam Optimization (PSO), in both digital and analog domain using various sensors. However, this can also be done by using a single potentiometer as a sensor and Proportional Derivative Controller (PD) controller as the design algorithm. The comparison or difference between the reference and the potentiometer generates control signal to drive the system. In this case, it consists of a thin vertical rod attached at the bottom, referred to as pivot point mounted on a mobile toy car. The car, depending upon the direction of the deflection of the pendulum moves horizontally in order to bring the pendulum to absolute rest. The main idea behind this control process is the use of PD (Proportional and Derivative) controller to generate signal to control the speed and direction of the motor. The only sensor used in this project was a potentiometer (pot) which was attached with the pendulum rod. The variation in its resistance causes change in voltage and afterward, it was compared with the reference voltage to generate the appropriate control signal. PROTEUS software was used for circuit simulation, frequency responses of the system were analyzed in MATLAB with different values of KP and KD. Finally, to represent the system stability, root locus diagram was drawn using MATLAB.DOI: http://dx.doi.org/10.3329/dujs.v60i1.10348 Dhaka Univ. J. Sci. 60(1): 115-120 2012 (January)

Real-Time Fiber-Optic Intubation Simulator With Force Feedback

Fiber-optic intubation is an emergency procedure that can be performed to intubate a patient when the patient has serious difficulty in breathing normally. The existing simulators for fiber-optic intubation procedure provide haptic feedback to the user when there is a contact with the vocal cord section, but they do not capture the grazing effect of the endoscope along the inner walls of the airway. The grazing on the inner walls of the airway, if not well controlled, could lead to unnecessary trauma for the patient. Hence, there is a need to provide this force feedback in a fiber-optic intubation simulator. We have built a fiber-optic intubation simulator with force feedback. This system is composed of a software simulation coupled with a physics-based simulation that enhances the visual experience. The software simulation is connected to a haptic feedback device. The device provides force feedback when contact is made with any section of the airway. The force feedback varies based on the position of contact and intensity of contact. We use a proportional and derivative (PD) controller to obtain force feedback at the vocal cord section and a variable magnetic field to capture the grazing effect of the endoscope along the inner walls of the airway. The movements of the endoscope are captured using rotary encoders (that read the insertion and the tip bend) and a compass module (that reads the twist angle of the endoscope along the long axis). These movements are used to navigate the virtual airway using a virtual endoscope. When collisions are encountered, the physics library evaluates the position of contact and the force with which contact is made. Force feedback is generated due to the interaction of the solenoids with the permanent magnets at the tip of the endoscope. This information helps the software to actu- ate the right combination of solenoids. The simulator will help to train all aspects of fiber-optic intubation, namely 1) developing the necessary psychomotor skills to successfully navigate the airway with minimal or no damage to the airway or vocal cords; and 2) cognitive skills to perform the procedure fast and effectively.

Impulsive Mode Elimination for Descriptor Systems by a Structured P-D Feedback

The problem of impulsive mode elimination for descriptor systems via a structured output proportional and derivative (P-D) feedback is investigated in this technical note. The motivation of solving this problem arises from an observation that the impulse behavior for some descriptor systems can not be eliminated completely by a parameterized output P-D feedback, but it can be removed by a structured P-D feedback elegantly designed. In order to explain this phenomenon explicitly, a concept of the structured P-D feedback is first introduced, then an explicit necessary and sufficient condition is constructively derived for the closed loop systems to be regular and impulse-free by the structured P-D feedback. The main result is represented in terms of the original system parameters instead of decomposed subsystem parameters. Finally, an example is provided to illustrate the effectiveness of the proposed result.

Electrostatic Torsional Micromirror With Enhanced Tilting Angle Using Active Control Methods

Electrostatic microelectromechanical systems (MEMS)-based torsional micromirrors are a fundamental building block for many optical network applications, such as optical wavelength-selective switches, configurable optical add-drop multiplexers and optical cross-connects. Although the device architecture, materials and fabrication processes determine the micromirrors' functioning space, one major technical challenge to achieving their full performance potentials is the controllability and stability of the tilting angle. In this paper, an electrostatic micromirror is designed and fabricated using a standard MEMS silicon-on-insulator (SOI) process. Active control approaches including gain scheduling and nonlinear proportional and derivative (PD) control are proposed. Both approaches can improve the performance of the mirror tilting and enhance the robustness of the structures to any stochastic perturbations. Furthermore, the nonlinear PD control can eliminate the micromirror “pull-in” phenomenon, hence significantly expanding the mirror tilt range, and as a result achieving enhanced device performance and functionality. The nonlinear PD control method is experimentally implemented and the results demonstrate the effectiveness of the approach.

Can a Simple Control Scheme Work for a Formation Control of Multiple Autonomous Underwater Vehicles?

The proportional and derivative (PD) and proportional, integral, and derivative (PID) controllers have been used extensively in industry due to their simplicity and effectiveness. This paper aims to investigate whether simple PD and adaptive PD-based controllers work for a complex system consisting of a group of multiple autonomous underwater vehicles (AUVs). Simple control laws with exact and uncertain gravity compensation are proposed for shape control of multiple AUVs. The proposed adaptive PD-based controller, in the presence of gravity uncertainty, requires only the model of gravity and buoyancy regressor matrix and does not require any knowledge of the inertia matrix, Coriolis and centripetal force, hydrodynamic damping and the parameters of the gravity, and buoyancy forces of the AUVs. Hence, the proposed controllers have the advantages of simplicity and ease of implementation. A novel collision and obstacle avoidance strategy using multi-layer region control concept, which limit the unnecessary use of high control efforts that lead to oscillatory movements of AUVs, is discussed. Lyapunov-like functions are proposed for the stability analysis. Simulation studies on AUVs with 6 degrees-of-freedom are presented to demonstrate the effectiveness of the proposed controllers.

Saturated output feedback tracking control for robot manipulators via fuzzy self-tuning

This paper concerns the problem of output feedback tracking (OFT) control with bounded torque inputs of robot manipulators, and proposes a novel saturated OFT controller based on fuzzy self-tuning proportional and derivative (PD) gains. First, aiming to accomplish the whole closed-loop control with only position measurements, a linear filter is involved to generate a pseudo velocity error signal. Second, different from previous strategies, the arctangent function with error-gain is applied to ensure the boundedness of the torque control input, and an explicit system stability proof is made by using the theory of singularly perturbed systems. Moreover, a fuzzy self-tuning PD regulator, which guarantees the continuous stability of the overall closed-loop system, is added to obtain an adaptive performance in tackling the disturbances during tracking control. Simulation showed that the proposed controller gains more satisfactory tracking results than the others, with a better dynamic response performance and stronger anti-disturbance capability.

Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators

Industrial robot control covers nonlinearity, uncertainty and external perturbation considered in control laws design. Proportional and Derivative (PD) with gravity compensation control is well-known control used in manipulators to ensure global asymptotic stability for fixed symmetrical positive definite gain matrices. To enhance PD with gravity compensation controller performance, in this paper, we propose hybrid fuzzy PD control precompensation with gravity compensation, consisting of a fuzzy logic-based precompensator followed by hybrid fuzzy PD with gravity compensation controller. Hybrid fuzzy control is done by a Supervisory Hierarchical Fuzzy Controller (SHFC) for tuning conventional controller Proportional and Derivative gains based on actual tracking location and velocity error. Hierarchical hybrid fuzzy control consists of an intelligent upper supervisory fuzzy controller and a lower direct conventional PD controller. Numerical simulations using the dynamic model of a three DOF planar rigid robot manipulator with uncertainty show the effectiveness of the approach in trajectory tracking problems. Our results show that the proposal controller has performance superior to a conventional controller.

Neural-Mechanical Feedback Control Scheme Generates Physiological Ankle Torque Fluctuation During Quiet Stance

We have recently demonstrated in simulations and experiments that a proportional and derivative (PD) feedback controller can regulate the active ankle torque during quiet stance and stabilize the body despite a long sensory-motor time delay. The purpose of the present study was to: 1) model the active and passive ankle torque mechanisms and identify their contributions to the total ankle torque during standing and 2) investigate whether a neural-mechanical control scheme that implements the PD controller as the neural controller can successfully generate the total ankle torque as observed in healthy individuals during quiet stance. Fourteen young subjects were asked to stand still on a force platform to acquire data for model optimization and validation. During two trials of 30 s each, the fluctuation of the body angle, the electromyogram of the right soleus muscle, and the ankle torque were recorded. Using these data, the parameters of: 1) the active and passive torque mechanisms (Model I) and 2) the PD controller within the neural-mechanical control scheme (Model II) were optimized to achieve potential matching between the measured and predicted ankle torque. The performance of the two models was finally validated with a new set of data. Our results indicate that not only the passive, but also the active ankle torque mechanism contributes significantly to the total ankle torque and, hence, to body stabilization during quiet stance. In addition, we conclude that the proposed neural-mechanical control scheme successfully mimics the physiological control strategy during quiet stance and that a PD controller is a legitimate model for the strategy that the central nervous system applies to regulate the active ankle torque in spite of a long sensory-motor time delay.

Stable adaptive compensation with fuzzy CMAC for an overhead crane

In order to control mechanical systems, this paper proposes a novel fast control strategy. The controller includes a normal proportional and derivative (PD) regulator and a fuzzy cerebellar model articulation controller (CMAC). For an overhead crane, this control can realize both position tracking and anti-swing. Using a Lyapunov method and an input-to-state stability technique, the PD control with CMAC compensation is proven to be robustly stable with bounded uncertainties. Real-time experiments are presented comparing this new stable control strategy with regular crane controllers.

Simulation of the Growth Rate of Vertical Displacement Events and the Requirement of Active Feedback Power Supply in EAST

An axisymmetric rigid plasma RZIP model for the EAST electromagnetic system is developed. Based on this model, the open loop vertical growth rates for various EAST equilibrium configurations generated by EFIT are calculated and the closed loop stability is analyzed. The design of the PD (proportional and derivative) feedback controller and the requirement for the fast control power supply are also discussed.

Closed-Loop Control of Functional Electrical Stimulation-Assisted Arm-Free Standing in Individuals With Spinal Cord Injury: A Feasibility Study

Objectives. The purpose of the present study was to show that the design of a neuroprosthesis for unsupported (arm-free) standing is feasible. We review findings suggesting that a closed-loop controlled functional electrical stimulation (FES) system should be able to facilitate arm-free quiet standing in individuals with spinal cord injury (SCI). Particularly, this manuscript identifies: 1) a control strategy that accurately mimics the strategy healthy individuals apply to regulate the ankle joint position during quiet standing and 2) the degrees of freedom (DOF) of the redundant, closed-chain dynamic system of bipedal stance that have to be regulated to facilitate stable standing. Methods and Results. First, we utilized a single DOF model of quiet standing (inverted pendulum) to analytically identify a proportional and derivative (PD) feedback controller that regulates the ankle torque in a physiologic manner despite a long sensory-motor time delay. Second, these theoretic results were experimentally validated by implementing the proposed PD controller to stabilize an individual with SCI during quiet standing. Third, a realistic, three-dimensional dynamic model of quiet standing with 12 DOF was used to determine the optimal combination of the minimum number of DOF that need to be regulated with the PD controller to ensure stability during quiet standing. Finally, perturbation simulations confirmed that the kinematics of this system are similar to those of healthy individuals during perturbed standing. Conclusions. The presented results suggest that stable standing can be achieved in individuals with SCI by controlling only six DOF in the lower limbs using FES, and that a PD controller actuating these DOF can stabilize the system despite a long sensory-motor time delay. Our finding that not all DOF in the lower limbs need to be regulated is particularly relevant for individuals with complete SCI, because some of their muscles may be denervated or difficult to access.

Application of smart system to textile industry: Preliminary design of a smart hanger for garment inspection

A smart inspection system, comprising three components, namely a smart hanger, a stitching-workmanship defect classification unit as well as a shade variation detection unit, is introduced for the textile industry. The preliminary design and optimization results of the smart hanger which stretches garments to provide enough tension to facilitate the inspection are presented. The hanger, with a Proportional and Derivative (PD) controller, is modeled as a four-link robot consisting of three revolute joints and one prismatic joint. The design objectives include (1) maximizing the link portions within “effective regions” at the final state, (2) minimizing the force or torque required to finish the stretching process, and (3) minimizing the settling time of the stretching process. In addition to control gains, the lengths of the four links as well as the desired movements of the joints are taken as design variables. The required transient behavior of the hanger is defined by the constraints on settling time and maximum overshoot. In order to prevent the clothes from being damaged by the links during the stretching process, geometrical constraints are imposed on the motions of the links. Optimization results, obtained by using the multi-objective genetic algorithm (MOGA), are presented in the form of Pareto solutions. After analysis, optimal parameters are selected and computer simulations are performed to investigate the transient behavior of the hanger. Satisfactory results are obtained, which provide a good foundation for the on going development of the smart inspection system.

Iterative Learning Velocity and Tension Control for Single Span Axially Moving Materials

Precise tension and speed control of axially moving material systems enables high speed processing of paper, plastics, fibers, and films. A single span model is developed that includes distributed longitudinal vibration, a torque-controlled roller at the left boundary, and a speed-controlled roller at the right boundary. The speed trajectory of the right roller is assumed periodic but unknown. A proportional and derivative (PD) feedback and iterative learning control (ILC) feedforward control law is developed for the left roller torque based on the measured tension and speed at the left boundary. PD tension/speed control is proven to ensure boundedness of distributed displacement and tension. ILC is proven to provide the same theoretical result but greatly improved simulated response to an aggressive stop/start right roller speed trajectory.

Measures Of Postural Stability Are Associated With Gains And Noise In The Control System

Postural stability is reduced with age or neurological disorder and improved with certain types of training (e.g., Tai-chi) as evaluated by various measures using center of pressure (COP) during quiet standing. However, the implications of specific measures with respect to the underlying control mechanisms have remained unclear. PURPOSE: To investigate the influence of variation in the control system on the COP measures during quiet standing, using mathematical simulations. METHODS: A feedback model that represented the human body and the control system during quiet standing was built using an inverted pendulum, a proportional and derivative (PD) controller with a time delay (the neural controller) and another PD controller without a time delay (the mechanical controller). The angle of the pendulum was fed back to the controllers, and the output of the neural controller (corresponding to the motor command) was input into the neuro-muscular torque generator. The sum of the output of the neuro-muscular torque generator and of the mechanical controller represented the ankle torque. A driving noise was added to the motor command to simulate realistic body sway conditions. The gain combinations that robustly stabilized the entire system were used to simulate the COP fluctuations. The gains of the controllers and the noise amount were treated as variables. The statistical relationship between each measure and the controller gains or noise was assessed using the partial correlation analysis. Sixty thousand and five hundred combinations of the variables were tested in total. RESULTS: All gains correlated negatively with the time domain measures (r=-0.372 to-0.659) except the mean velocity, which correlated positively with each gain. The neural derivative gain correlated positively with the frequency domain measures (r =0.964 to 0.973). The proportional gains correlated with Hurst exponent positively for the short term region (r= 0.837 to 0.892) and negatively for the long term region (r=-0.828 to-0.883). The amount of noise correlated positively with time domain measures (r= 0.901 to 0.988) but not with frequency measures. CONCLUSIONS: Each COP measure is associated with the variation in the control system. As such, the COP measures have a potential for investigating or characterizing the control system of balance.

Implementation of a Physiologically Identified PD Feedback Controller for Regulating the Active Ankle Torque During Quiet Stance

Our studies have recently demonstrated that a proportional and derivative (PD) feedback controller, which takes advantage of the body's position and velocity information to regulate balance during quiet standing, can compensate for long neurological time delays and generate a control command that precedes body sway by 100-200 ms. Furthermore, PD gain pairs were identified that ensure a robust system behavior and at the same time generate dynamic responses as observed in quiet standing experiments with able-bodied subjects. The purpose of the present study was to experimentally verify that the PD controller identified in our previous study can: 1) regulate the active ankle torque to stabilize the body during quiet standing in spite of long neurological time delays and 2) generate system dynamics, i.e., a motor command and body sway fluctuation, that successfully mimic those of the physiologic system of quiet standing. Our real-time closed-loop feedback circuit consisted of a center of mass position sensor and a functional electrical stimulator that elicited contractions of the plantar flexors as determined by the aforementioned PD controller. The control system regulated upright stance of a subject who was partially de-afferented and de-efferented due to a neurological disorder called von Hippel-Lindau Syndrome (McCormick Grade III). While the subject was able to generate a motor command for the ankle joints, he could not regulate the resulting torque sufficiently due to a lack of sensory feedback and motor control. It is important to mention that a time delay was included in the closed-loop circuit of the PD controller to mimic the actual neurological time delay observed in able-bodied individuals. The experimental results of this case study suggest that the proposed PD controller in combination with a functional electrical stimulation system can regulate the active ankle torque during quiet stance and generate the same system dynamics as observed in healthy individuals. While these findings do not imply that the CNS actually applies a PD-like control strategy to regulate balance, they suggest that it is at least theoretically possible.

A Model-Free Cross-Coupled Control for Position Synchronization of Multi-Axis Motions: Theory and Experiments

In this brief, a model-free cross-coupled controller is proposed for position synchronization of multi-axis motions. The position synchronization error of each axis is defined as the differential position error between this axis and its two adjacent axes, which is then coupled with the position error to form a coupled position error. A proportional and derivative (PD)-type synchronization controller with feedback of this coupled position error is proposed and proven to guarantee asymptotic convergence to zero of both position and synchronization errors in a setpoint position control. A setpoint tracking controller is further developed by adding feedforward control terms and a saturation function to the PD synchronization controller. The proposed method is easy to implement in practice since it is model free and the control gains are time-invariant. Experiments are performed to verify effectiveness of the proposed approach