scholarly journals On the Determination of the Feedback Gains of Multivariable PI Control Systems Using the Quadratic Cost Performance Index

1979 ◽  
Vol 15 (6) ◽  
pp. 739-745
Author(s):  
Satoru FUKATA ◽  
Akira MOHRI ◽  
Masaru TAKATA
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2013 ◽  
Vol 650 ◽  
pp. 493-497 ◽  
Author(s):  
Valerij I. Goncharov ◽  
Vadim A. Onufriev ◽  
Ilya O. Ilyin

Authors review methods of determining a plant’s mathematical model. Then, they show a numerical method of pulse automatic control systems’ (ACS) identification, focused on computer technology, the interpolation procedure and iterative methods of approximation to the desired solution. The basis of the approach is the method of inverse problems of dynamics and real interpolation method for calculating the linearized dynamical systems. An algorithm and the mobile device designed for the identification of facilities management in operational conditions are proposed. There is results’ application in the conclusion.


Author(s):  
David F. Thurston

The main objective in optimizing train control is to eliminate the waist associated with classical design where train separation is determined through the use of “worst case” assumptions that are invariant to the system. In fact, the worst case approach has been in place since the beginning of train control systems. Worst case takes the most conservative approach to the determination of train stopping distance, which is the basis for design of virtually all train control. This leads to stopping distances that could be far more that actually required under the circumstances at the time the train is attempting to brake. Modern train control systems are designed to separate trains in order to provide safety of operation while increasing throughput. Calculations for the minimum distance that separates trains have traditionally been based on the sum of a series of worst case scenarios. The implication was that no train could ever exceed this distance in stopping. This distance is called Safe Braking Distance (SBD). SBD has always been calculated by static parameters that were assumed to be invariant. This is, however, not the case. Parameters such as adhesion, acceleration, weight, and reaction vary over time, location or velocity. Since the worst case is always used in the calculation, inefficiencies result in this methodology which causes degradation in capacity and throughput. This is also true when mixed traffic with different stopping characteristics are present at the same time. The classic theory in train control utilizes a SBD model to describe the characteristics of a stopping train. Since knowledge of these conditions is not known, poor conditions are assumed. A new concept in train control utilizes statistical analysis and estimation to provide knowledge of the conditions. Trains operating along the line utilize these techniques to understand inputs into their SBD calculation. This provides for a SBD calculation on board the train that is the shortest possible that maintains the required level of safety. The new SBD is a prime determinant in systems capacity. Therefore by optimizing SBD as describes, system capacity is also optimized. The system continuously adjusts to changing conditions.


2020 ◽  
Vol 25 (3) ◽  
pp. 7-12
Author(s):  
Rud V.V. ◽  

This paper considers the problems of the integration of independent manipulator control systems. Areas of control of the manipulator are: recognition of objects and obstacles, identification of objects to be grasped, determination of reliable positions by the grasping device, planning of movement of the manipulator to certain positions with avoidance of obstacles, and recognition of slipping or determination of reliable grasping. This issue is a current problem primarily in industry, general-purpose robots, and experimental robots. This paper considers current publications that address these issues. Existing algorithms and approaches have been found in the management of both parts of the robot manipulator and solutions that combine several areas, or the integration of several existing approaches. There is a brief review of current literature and publications on the above algorithms and approaches. The advantages and disadvantages of the considered methods and approaches are determined. There are solutions that cover either some areas or only one of them, which does not meet the requirements of the problem. Using existing approaches, integration points of existing implementations are identified to get the best results. In the process, a system was developed that analyzes the environment, finds obstacles, objects for interaction, poses for grasping, plans the movement of the manipulator to a specific position, and ensures reliable grasping of the object. The next step was to test the system, test the performance, and adjust the parameters for the best results. The resulting system was developed by the research team of RT-Lions, Technik University, Reutlingen. The hardware research robot includes an Intel Realsense camera, a Sawyer Arm manipulator from Rethink Robotics, and an internally grabbing device.


2021 ◽  
Author(s):  
Georgi Kadikyanov ◽  
Zhivko Kolev ◽  
Seher Kadirova ◽  
Gergana Staneva ◽  
Daniel Lyubenov

2019 ◽  
Vol 260 ◽  
pp. 02008
Author(s):  
Primož Podržaj

In this paper, we describe the procedure for the implementation of the PID controller in the Festo CDPX operator unit. These units enable the execution of the control algorithm and human machine interface in a single unit. In our laboratory the unit is used to teach the students about the basics of control systems. For this purpose, one of the most common closed loop control systems for the education purposes was selected. It is a water level control system. In this paper the design of the whole system is presented. The need for a PI control algorithm is also explained. The programming of the operator unit CDPX, both in Festo CoDeSys and Designer Studio is explained. Such a simple system has turned out to be a great educational tool for Control Theory and Programmable Logic Controller related subjects.


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