Proportional control

About: Proportional control is a research topic. Over the lifetime, 3756 publications have been published within this topic receiving 49050 citations.

Remote control circuits for hydraulic motors

Abstract: A simplified remote control system for a plurality of hydraulic motors in which the transmitter and receiver controllers are simplified by providing for only a single proportional control member at each location with on-off type controls for all of the motors and in which the hydraulic circuit incorporates a proportional valve in series with a plurality of on-off valves or bidirectional valves in direct control of the motors and in parallel circuit to proportionally control flow from a hydraulic source to all of the bidirectional controllers or valves simultaneously. This will permit speed and directional control with speed of operation being effected for all motors operated simultaneously and at the same rate.

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

Abstract: The proportional integral and derivative (PID) controller is extensively applied in many applications. However, three parameters must be properly adjusted to ensure effective performance of the control system: the proportional gain (KP), integral gain (KI) and derivative gain (KD). Therefore, the aim of this paper is to optimize and improve the stability, convergence and performance in autotuning the PID parameter by using a deterministic Q-SLP algorithm. The proposed method is a combination of the swarm learning process (SLP) algorithm and Q-learning algorithm. The Q-learning algorithm is applied to optimize the weight updating of the SLP algorithm based on the new deterministic rule and closed-loop stabilization of the learning rate. To validate the global optimization of the deterministic rule, it is proven based on the Bellman equation, and the stability of the learning process is proven with respect to the Lyapunov stability theorem. Additionally, to demonstrate the superiority of the performance and convergence in autotuning the PID parameter, simulation results of the proposed method are compared with those based on the central position control (CPC) system using the traditional SLP algorithm, the whale optimization algorithm (WOA) and improved particle swarm optimization (IPSO). The comparison shows that the proposed method can provide results superior to those of the other algorithms with respect to both performance indices and convergence.

Resource management system and apparatus

Abstract: A computer implemented method for efficiently allocating resources for an enterprise server system through a proportional integral derivative scheme is provided. The method includes defining a set point parameter for a resource being allocated and defining a proportional gain parameter, a proportional integral (PI) gain parameter and a proportional integral derivative (PID) gain parameter in terms of the proportional gain parameter. The method further includes calculating an initial maximum allocation for the resource based on a product of the proportional gain parameter with a difference of an initial operating parameter and the set point parameter and adjusting the initial operating parameter to the initial maximum allocation. A next allocation of the resource is calculated based on a product of the proportional gain parameter with the difference of an initial operating parameter and the set point parameter and a difference of the set point with a current operating parameter. The initial maximum allocation is adjusted with a next allocation.