Andrzej Kot

Balance Platform Model Parameter Identification

In the first stage of the identification process was to build a model describing the system, using the measurement data recorded on input and output system [. The model was built without the knowledge of the mechanisms that occur in the process, only based on the relationship between the collected data. As an input parameter the defined type of motion was used, next converted to digital form by the real-time computer and sent to the axes control card. While the output signal was registered as a change of encoders position. Sampling time 20 ms was adopted. For each axis separately recorded measurements (signals were with different amplitudes and frequencies of motion tape device) [. In the next step the estimation was performed for the selection suitable algorithm, and the determination the parameters of model selected in the previous step [. The last step was to verify, to check the results of identification process. By comparing the signals obtained in response to a signal given the model of a registered object actual output signal, it is possible to visually estimate the accuracy of the identification and designation of the error. The last part of the article shows the results of various tests.

Balance Platform Vibration Control

In the presented paper the problem of balance platform control was considered. The object used during research is the original structure, designed by article authors. The work was divided into three parts: the identification process, control system design and laboratory tests. In the first stage of the identification process a model describing the system was build, using the measurement data recorded on input and output system. The model was built without the knowledge of the mechanisms that occur in the process; only based on the relationship between the measured data. Next the estimation was performed for selection of suitable algorithm, and determination of the parameters of model selected in the previous step. The last step was to verify and to check the results of identification process. By comparing the signals obtained in response to a signal given from the model of a registered object actual output signal, it is possible to visually estimate the accuracy of the identification and designation of the error. After identification process the control system was designed. In this application the PID controller was chosen. It was used to balance platform position and velocity control. The last part of the article shows the results of various laboratory tests and comparison of quality control.

Balance Maintaining by Human

Harmonious cooperation of the skeletal, muscular and nervous systems, forming a human motion organ, is responsible for all undertaken movement activities. Motion organ in the illustrated embodiment responsible not only for two basic motion activities, locomotion and manipulation, but also for maintaining the posture of the human body. Standing posture control makes a particular dimension of physical activity, because correct, stable posture determines the ability to perform most human movements. In the case of a man to maintain a balance in a standing position seems to be something obvious and does not require much effort, but with the advent of lesions or aging we begin to see how complex it is the process of balance control. The changes lead to impaired balance control which in turn can lead to the appearance of postural instability and in extreme circumstances, even to collapse. Maintaining a stable posture it is primarily associated with motor control provided by the human nervous system. The nervous system acts as an posture control system and most of all giving to a body well-defined silhouette. This control relies heavily on the integration of information from the human receptor system. Muscle, joint, tendon and skin receptors communicate first to the brain information about the movement and position of individual body parts and then feedback these signals to the muscles, causing reflex reactions allowing for correction of posture and thus return the center of gravity to a position that maintaining equilibrium. Subdivide those human body into segments linked closely with the system osteoarthritis limbs and trunk can create a system of interconnected pendulums with many degrees of freedom. In the case of standing it will be largely complicated inverted pendulums system by which activities phenomena associated with maintaining balance and locomotion can be modeled. If additionally in an upright position, taking into account the natural motion restrictions movements in all joints except the ankles will be blocked, the body will be a close approximation behave like a rigid body. So we can assume that for supporting the human body at the ankle, it will behave like an inverted pendulum. The article presents the ways of describing the equilibrium of man as an inverted pendulum.

Control Algorithms for Robot Manipulator

The subject of this work is to develop a control system for the two degree of freedom robot manipulator. Manipulators play an increasingly important role not only in flexible automation production systems but also in medicine and rehabilitation process [3]. High-speed and high-precision trajectory tracking are indispensable capabilities for versatile applications of manipulators. Even in well-known industrial applications manipulators are characterized by structural and / or unstructured uncertainty. Through structural uncertainty we miss a situation in which we have a dynamic model of the object, but because of the uncertainty unknown parameters such as load, inaccuracies in constant torque actuators etc. to create a properly working control system is a difficult issue. In contrast, unstructured uncertainty is related to the unknown of the dynamic model, which may be due to many reasons such as the presence of high-frequency modes of the manipulator, neglected time-delays, nonlinear friction etc. In this case, when the dynamic model of the system is not known a priori (or not available), the system must first be identified, then the control law is developed based on the estimated model [5, [6[7].These problems cause that it is very difficult to find good control system but simple. In this case, the different algorithms for control system of the manipulator was proposed. The first classical PD controller was tested. Next the system design for PD controller with compensation of gravitational forces.

Shape Prediction of Non-Ferrous Pipe Elements Processed by Electro-Dynamic Forming

The article presents analytical and calculation process of shape prediction of pipe elements formed by electrodynamic forming. In the first part of the work formulation of physical phenomena arising during this method of metal forming is presented. Next, basing at developed mathematical model, with use of numerical methods prediction of the final shape of the semi-finished product during free forming was performed. Results of this stage of tests were compared with results of measurements made during experimental test.

Phenomena Occurring during the Electro-Dynamic Forming of Non-Ferrous Pipe Elements

The paper presents description of physical phenomena arising during the process of electrodynamic forming by means of axisymetric inductors generating pulse magnetic field. Presented material shows the way for determination of pressures acting on non-ferrous pipe elements with an assumption of magnetic flux variation character in system. The paper describes also stages of energy conversion from electric energy of capacitors discharge into mechanical energy of pressure forming semi-finished product. The knowledge about presented phenomena allow to predict final shape of formed product during free forming by electrodynamic method.