Adaptive interpolating control for constrained systems with parametric uncertainty and disturbances

Kravchenko

et al. 2022

EEJET

This paper has analyzed the functioning conditions for the technological system of secondary condensation (TSSC) in a typical ammonia synthesis unit of the AM-1360 series with the use of a system-control approach. The coordinates of control vectors and external disturbances have been determined. An algorithm has been developed for predicting the coordinates of the control vector for the subsystem of decision support under the conditions of external disturbances for such a complex inertial object with high metal consumption as TSSC. The method of mathematical modeling was used to determine, based on the developed algorithm, the patterns and quantitative dependences of the influence of external disturbances such as the temperature of primary condensation and the flow rate of circulation gas on the efficiency of TSSC heat exchange processes. The regularity of increase in the heat flows and coordinates of control vector with an increase in the temperature of primary condensation has been established. The parametric sensitivity of the coordinates of the control vector under the conditions of change in the temperature of the primary condensation has been determined, which, compared with the circulation gas flow rate, exceeds it by more than six times. The executed software implementation of the algorithm employing the MATLAB programming environment makes it possible, owing to the embedded client part (ORC client), free software access to the current data on the technological process. The functional structure of computer-integrated TSSC technology with the proposed correction subsystem under a supervisory control mode has been designed. Correction solutions involving the additional hardware and software based on the programmable logic controller VIPA and SCADA-system Zenon have been practically implemented. The implementation of the developed system ensures the stabilization of the secondary condensation temperature at the regulatory level of −5 °C, which reduces the consumption of natural gas by almost 1 million nm3 per year.

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Design of an intelligent system to control the technological system of ammonia production secondary condensation

Kravchenko

et al. 2022

EEJET

Intl J Robust & Nonlinear

“…On the other hand, the disadvantage of the above path tracking methods is that all methods believe the robot model and external environment are ideal 21‐23 . Aiming at uncertain disturbances of complex robot systems, common methods include sliding mode control (SMC), active disturbance rejection control (ADRC), symplectic pseudospectral RHC controller, and adaptive control 24‐26 . For example, a fuzzy dynamic SMC was proposed to solve disturbances caused by the load changes 27 .…”

Section: Introductionmentioning

confidence: 99%

Neural networks‐based sliding mode tracking control for the four wheel‐legged robot under uncertain interaction

Wang

2021

When considering the accuracy of tracking control, physical interaction such as structural uncertainties and external dynamics is the main challenge in actual engineering scenarios, especially for the complex robot system. In this article, a neural network‐based sliding mode tracking control scheme (SMCR) is presented for the developed four wheel‐legged robot (BIT‐NAZA) under the uncertain interaction. First, a non‐singular fast terminal function based on the kinematic model is proposed for path tracking, which improves the motion quality during the approach movement and the sliding mode movement. At the same time, it can reduce the influence of uncertain disturbances on the premise of ensuring the path tracking control accuracy via neural networks. Finally, some demonstrations using the autonomous platform of the BIT‐NAZA robot are employed to evaluate the robustness and effectiveness of the hybrid algorithm.

Asian Journal of Control

“…The developed approach identified the drawback of zero initial value for the disturbance while calculating the upper estimate of control algorithm convergence time and overcomes it by admitting a disturbance with unknown but bounded initial value. In Zhang et al, 13 the parametric uncertainties and additive disturbance in constrained linear systems were controlled by developing an adaptive interpolating controller. The approach updated the parametric uncertainty set at each time step to achieve robust stabilization for the uncertain system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive control using stochastic approach for unknown but bounded disturbances and its application in balancing control

Singh

Bhushan

2021

This paper presents a simultaneous perturbation stochastic approximation (SPSA) approach for unknown but bounded disturbances in a typical closed loop system. These random disturbances are represented by a sequence of uncertainties along with the measured system output. Further, the proposed approach constructs a sequence of estimates and formulates an optimization problem which is minimized to achieve the adaptive control. In addition, the convergence conditions and additional generalizations are proposed to enhance the operation of SPSA algorithms for trail perturbation properties. To address the major challenges with unknown disturbances on the closed loop system, a balancing control problem with two degree of freedom (2DoF) ball balancer system and proportional integral derivative (PID) controller is considered. The proposed SPSA method minimizes the optimization problem to obtain the gain values of the PID controller. Simulation and experimental analysis are carried out, and the results substantiate that the PID gains optimized using SPSA provide better control when compared to conventional control approach in terms of tracking response under random uncertainties. K E Y W O R D Sball balancer system, proportional integral derivative (PID), simultaneous perturbation and stochastic approximation, two degree of freedom (2DoF), uncertainties