Selcuk Kizir

Fuzzy control of a real time inverted pendulum system

In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller. Swing-up and stabilization of the inverted pendulum were implemented directly in fuzzy logic controller. The fuzzy logic controller designed in the Matlab-Simulink environment was embedded in a dSPACE DS1103 DSP controller board. Swing-up algorithm brings the pendulum near to its inverted position in 10 seconds from downward position. In order to test the robustness of the fuzzy logic controller internal (changing model parameters) and external disturbances (applying external forces) were applied on the inverted pendulum. The inverted pendulum system was shown to be robust to the external and internal disturbances. The maximum errors of the pendulum angle to the impulse input were between 1.89° and 4.6449° in the robustness tests.

Tip trajectory control of a flexible-link manipulator using an intelligent proportional integral (iPI) controller

This paper presents the development, stability analysis and validation of an intelligent proportional integral (iPI) controller for the tip position control of a flexible-link manipulator. A stability analysis included in the paper shows that the iPI controller is equivalent to the proportional integral-squared controller. In order to verify the performance of the iPI controller, several experiments were conducted. In these experiments, step and square-wave inputs and two other trajectories were applied to the flexible-link manipulator. Also, the performance of the iPI controller was compared with those of classical PI and PID controllers. The results obtained from the comparison experiments showed that, the PI and PID controllers produced better performance in step and square-wave inputs, but the iPI controller yielded better trajectory tracking performance. All of the controllers were tested for disturbance and noise rejection capability. The iPI controller eliminated disturbance and noise better than the classical controllers. Considering all of the results, the iPI controller has great potential in trajectory tracking control of flexible-link manipulators.

Position Control and Trajectory Tracking of the Stewart Platform

Demand on high precision motion systems has been increasing in recent years. Since performance of today’s many mechanical systems requires high stiffness, fast motion and accurate positioning capability, parallel manipulators have gained popularity. Currently, parallel robots have been widely used several areas of industry such as manufacturing, medicine and defense. Some of these areas: precision laser cutting, micro machining, machine tool technology, flight simulators, helicopter runway, throwing platform of missiles, surgical operations. Some examples are shown in Figure 1. Unlike open-chain serial robots, parallel manipulators are composed of closed kinematic chain. There exist several parallel kinematic chains between base platform and end moving platform. Serial robots consist of a number of rigid links connected in serial so every actuator supports the weight of the successor links. This serial structure suffers from several disadvantages such as low precision, poor force exertion capability and low payload-to-weight-ratio. The parallel robot architecture eliminates these disadvantages. In this architecture, the load is shared by several parallel kinematic chains. This superior architecture provides high rigidity, high payload-to-weight-ratio, high positioning accuracy, low inertia of moving parts and a simpler solution of the inverse kinematics equations over the serial ones. Since high accuracy of parallel robots stems from load sharing of each actuator, there are no cumulative joint errors and deflections in the links. Under heavy loads, serial robots cannot perform precision positioning and oscillate at high-speeds. Positioning accuracy of parallel robots is high because the positioning error of the platform cannot exceed the average error of the legs positions. They can provide nanometer-level motion performance. But they have smaller workspace and singularities in their workspace. The most widely used structure of a parallel robot is the Stewart platform (SP). It is a six degrees of freedom (DOF) positioning system that consists of a top plate (moving platform), a base plate (fixed base), and six extensible legs connecting the top plate to the bottom plate. SP was invented as a flight simulator by Stewart in 1965 (Stewart, 1965). This platform contained three parallel linear actuators. Gough had previously suggested a tire test machine similar to Stewarts model (Bonev, 2003). In the test machine, six actuators were used as a mechanism driven in parallel. Gough, the first person, developed and utilized this type parallel structure. Therefore, SP is sometimes named as Stewart-Gough platform in the literature. Stewart’s and Gough’s original designs are shown in Figure 2.

Fuzzy logic control of single-link flexible joint manipulator

In this paper, a single-link flexible joint robot is designed, fabricated and controlled. Three different fuzzy logic controllers (FLCs) were used to remove link vibrations and to obtain accurate trajectory tracking of link end-point. The input variables of the first and the second FLCs are motor rotation angle error and its derivative, and end-effector deflection error and derivative of deflection error, respectively. The outputs of these controllers are inputs of the third FLC producing the control signal of the flexible joint system. All of the FLCs were embedded in ds1103 real time control board. In the step response experiments, the error of motor rotation angle was obtained less than 0.12 degree and there was no steady-state error in the end-effector deflection. In the different trajectory-tracking experiments with the same FLC structure, small errors and phase shift in the system variables were occurred. Also, parameters of flexible arm were changed to test robustness of the FLC. It is seen that FLC are very robust to internal and external disturbances. Considering the all results of the experiments, FLC shows efficient performance in flexible robot arm.

Intelligent proportional-integral (iPI) control of a single link flexible joint manipulator

This paper presents the design, stability analysis and experimental validation of a computationally non-intensive, model-free, intelligent proportional-integral (iPI) controller for flexible joint manipulators. In order to show the performance of the iPI controller, it is compared with classical proportional-integral and proportional-integral-derivative controllers. Based on this comparison, the iPI-controlled system achieved a better than 60% tracking accuracy for both kane trajectory and sine input tracking. The iPI controller also significantly reduced transient swings in the flexible joint of the manipulator, when tracking a train of pulses. Moreover, the iPI controlled system successfully eliminated both disturbances and noise effects from the dynamics of the manipulator.

Higher-order differential feedback control of a flexible-joint manipulator

This paper presents a new control scheme for a flexible-joint manipulator using a higher-order differential feedback controller (HODFC). Two higher-order differential operators were designed and used to perform observations of both the reference input and the output of the manipulator, together with the requisite state derivatives. An error-based state-space model was then derived from the observed states. A pole-placement procedure with filtering was then used to drive the system error to zero. Practical controller implementation was carried out using the dSPACE real-time prototyping system. For the comparative validation of the performance of the HODFC with respect to a classical proportional-integral and proportional-integral-derivative (PID) controller, several experiments were undertaken. In these experiments, the step input, sine waves, kane trajectories, and external disturbances were applied to the controlled flexible-joint manipulator. The results showed that the HODFC controller eliminated disturbances within one second of occurrence, and produced superior kane trajectory tracking. Moreover, based on the root-mean-square tracking error criterion, the HODFC was observed to track both the sine and kane function trajectories with one-fourth the tracking error obtained with classical PID control.

Vision based magnetic levitation system

In this study, control of a vision based magnetic levitation system was explored. The system which is known as magnetic levitation or magnetic suspension constitutes the fundamental of the high speed maglev trains. The system levitates a ferro-magnetic object in the space using electromagnetic force against to gravity. The system consists of a coil, a controller, a position sensor, a ferro-magnetic object and a camera. The object is levitated at a desired position relative to coil core. In general, the position of the object is measured by light based sensors. However, light based sensors have some disadvantages such as calibration requirement, non-linearity, not being robust, etc. Thus, instead of light based sensors, a new vision based position sensor was developed. Position data obtained by the image processing algorithm was sent to the controller which adjusts the coil current according to position error creating a force on the object.

Trajectory and Vibration Control of a Single-link Flexible Joint Manipulator Using a Distributed Higher Order Differential Feedback Controller

The trajectory tracking in the flexible-joint manipulator (FJM) system becomes complicated since the flexibility of the joint of the FJM superimposes vibrations and nonminimum phase characteristics. In this paper, a distributed higher-order differential feedback controller (DHODFC) using the link and joint position measurement was developed to reduce joint vibration in step input response and to improve tracking behavior in reference trajectory tracking control. In contrast to the classical higher-order differential (HOD), the dynamics of the joint and link are considered separately in DHODFC. In order to validate the performance of the DHODFC, step input, trajectory tracking, and disturbance rejection experiments are conducted. In order to illustrate the differences between classical HOD and DHODFC, the performance of these controllers is compared based on tracking errors and energy of control signal in the tracking experiments and fundamental dynamic characteristics in the step response experiments. DHODFC produces better tracking errors with almost same control effort in the reference tracking experiments and a faster settling time, less or no overshoot, and higher robustness in the step input experiments. Dynamic behavior of DHODFC is examined in continuous and discontinues inputs. The experimental results showed that the DHODFC is successful in the elimination of the nonminimum phase dynamics, reducing overshoots in the tracking of such discontinuous input trajectories as step and square waveforms and the rapid damping of joint vibrations. [DOI: 10.1115/1.4035873]

Real Time Control of a Flexible Joint Manipulator Using Interval Type-2 Fuzzy Logic Controller

Flexible manipulators have several benefits over the rigid manipulators such as light weight with higher payload, better maneuverability, higher operational speed, lower energy consumption. Along these advantages, however, the flexible manipulators cause vibrations and trajectory tracking control problems. In this study, a cascade interval type-2 fuzzy logic controller (IT2FL-C) was proposed for real time trajectory and vibration control of a flexible joint manipulator. The proposed controller was implemented in the system using dSpace DS1103 real-time control board. The cascade control structure includes three separate IT2FL-C. The IT2FL-Cs were designed on the IT2FL-C toolbox, which we developed, with interval triangular membership functions (MFs), Mamdanis fuzzy inference method and Karnik-Mendel (KM) type reduction (TR) algorithm. Several experiments conducted for observation of the proposed IT2FL-C’s performance. The step and sinusoidal trajectories were applied to the system changing link length with/without external payload. Additionally, performance of the proposed controllers was compared to conventional type-1 fuzzy logic controller (T1FL-C).