scholarly journals MODELING AND SIMULATION OF QUAY CRANE CONTROL SYSTEM FOR PID CONTROLLER OPTIMAL PARAMETERS DETERMINATION / KRANTINĖS KRANO VALDYMO SISTEMOS KOMPIUTERINIS MODELIAVIMAS OPTIMALIOMS PID VALDIKLIO VERTĖMS NUSTATYTI

2016 ◽  
Vol 8 (5) ◽  
pp. 540-547
Author(s):  
Tomas Eglynas ◽  
Audrius Senulis ◽  
Marijonas Bogdevičius ◽  
Arūnas Andziulis ◽  
Mindaugas Jusis
Keyword(s):  
Mathematical Model ◽  
Parameter Estimation ◽  
Control System ◽  
Pid Controller ◽  
Closed Loop ◽  
Loop System ◽  
Control Algorithms ◽  
Closed Loop System ◽  
Matlab Simulink ◽  
Crane Control

The main control object of Quay crane, which is operating in seaport intermodal terminal cargo loading and unloading process, is the crane trolley. One of the main frequent problem, which occurs, is the swinging of the container. This swinging is caused not only by external forces but also by the movement of the trolley. The research results of recent years produced various types of control algorithms by the other researchers. The control algorithms are solving separate control problems of Quay crane in laboratory environment. However, there is still complex control algorithm design and the controller’s parameter estimation problems to be solved. This paper presents mathematical model of the Quay crane trolley mechanism with the suspended cargo. The mathematical model is implemented in Matlab Simulink environment and using Dormand-Prince solving method. The presented model of laboratory quay crane mathematical model is dedicated to parameter estimation of PID controller of closed loop system with the usage of S –form speed input profile. The article includes the dynamic model of the presented system, the description of closed loop system and modeling results. These results will be used as an initial information for the PID parameters estimation in real quay crane control system. The simu-lation of the model was performed using estimated values of controller. The sway influence of the cargo, the usage of the trolley speed input S-shaper and the PID controller was used to control the trolley speed. Jūriniame įvairiarūšiame terminale atliekant konteinerių krovos procesus, vienas iš krantinės kranų valdymo objektų yra vežimėlis. Viena iš problemų, su kuria susiduriama dažniausiai, yra konteinerio svyravimai, kuriuos, be išorinių veiksnių, taip pat sukelia ir vežimėlio judėji-mas. Remdamiesi paskutinių kelerių metų tyrimais, mokslininkai sukūrė įvairių valdymo algoritmų, kurie laboratorinėmis sąlygomis spren-džia atskiras krantinės kranų valdymo problemas. Tačiau kompleksinių ir efektyvių valdymo algoritmų ir jų valdymo sistemos parametrų nustatymo metodai vis dar kuriami ir tobulinami. Šiame darbe sudarytas krantinės krano vežimėlio su kabančiu kroviniu mechanizmo sis-temos matematinis modelis. Šis modelis realizuotas Matlab Simulink aplinkoje ir sprendžiamas taikant Dormand-Prince metodą. Sukurtas laboratorinio krantinės krano valdymo sistemos kompiuterinis modelis skirtas uždarosios valdymo sistemos PID valdiklio parametrams nustatyti, kai užduoties signalui taikomas S formos greičio kitimo profilis. Darbe pateiktas sistemos dinaminis modelis, aprašyta uždaroji valdymo sistema, pateikti kompiuterinio modeliavimo rezultatai, kuriuos planuojama panaudoti kaip pradinę informaciją realaus krano PID valdiklio parametrams derinti. Atlikta simuliacija naudojant nustatytas vertes ir įvertinti krovinio svyravimai taikant S formos greičio kitimo profilį kartu su PID valdikliu vežimėlio greičiui valdyti.

Comparative Analysis of DC Motor Control System

2016 ◽  
Vol 817 ◽  
pp. 111-121 ◽  
Author(s):  
Wojciech Mitkowski ◽  
Marta Zagórowska ◽  
Waldemar Bauer
Keyword(s):  
Control System ◽  
Comparative Analysis ◽  
Pid Controller ◽  
Closed Loop ◽  
Control Method ◽  
Closed Loop System ◽  
Motor Shaft ◽  
Dc System ◽  
Dc Motor Control ◽  
Motor Control System

In this work we will present a control method for DC system – the so-called practical PID controller, where the inertia of both the derivative and the actuator is included. The original element in this paper consists of a comparative analysis of various controller stabilizing the position of motor shaft. In a system with ideal gain, K>0 ensures asymptotic stability of the closed-loop system. Taking into account this inertia along with the inertia of the derivative, we obtain limited values 0<Kp<Kgr. A similar restrictions apply to a system with delay.

Control System Synthesis Based on Plant Test Data

1995 ◽  
Vol 117 (4) ◽  
pp. 484-489
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Control System ◽  
Test Data ◽  
Closed Loop ◽  
Explicit Knowledge ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
System Synthesis ◽  
Control System Synthesis

A correlation equation is established between open-loop test data and the desired closed-loop system characteristics permitting control system synthesis to be done on the basis of a numerical approach using experimental data. The method is applicable when the system is linear-time-invariant and open-loop stable. The major merits of the algorithm are two-fold: 1) Arbitrary placement of the closed-loop system equation is possible, and 2) explicit knowledge of an open-loop system model is not needed for the controller synthesis.

A Robust Design Optimization Framework for Systematic Model-Based Calibration of Engine Control Systems

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Hoseinali Borhan ◽  
Edmund Hodzen
Keyword(s):  
Control System ◽  
Design Optimization ◽  
Robust Design ◽  
Closed Loop ◽  
Optimization Technique ◽  
Loop System ◽  
Robust Design Optimization ◽  
Engine Control ◽  
Closed Loop System ◽  
Model Based

In this paper, a systematic model-based calibration framework basing on robust design optimization technique is developed for engine control system. In this framework, the control system is calibrated in an optimization fashion where both performance and robustness of the closed-loop system to uncertainties are optimized. The proposed calibration process has three steps: in the first step, the optimal performance of the system at the nominal conditions, where the effects of uncertainties are ignored, is computed by formulation of the controller calibration as an optimization problem. The capabilities of the controller are fully explored at nominal conditions. In the second step, the robustness and sensitivity of a selected control design to the system uncertainties are analyzed using Monte Carlo simulation. In the third step, robust design optimization is applied to optimize both performance and robustness of the closed-loop system to the uncertainties. The robustness capabilities of the controller are fully explored and the one that satisfies both performance and robustness requirements is selected. This process is implemented for the calibration of an advanced diesel air path control system with a variable geometry turbocharger (VGT) and dual loop exhaust gas recirculation (EGR) architecture.

scholarly journals Computation of time-delay for Delayed Network Controlled Temperature Control System

2021 ◽  
Vol 2070 (1) ◽  
pp. 012102
Author(s):  
V Venkatachalam ◽  
M Ramasubramanian ◽  
M Thirumarimurugan ◽  
D Prabhakaran
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Temperature Control ◽  
Closed Loop ◽  
Simulation Software ◽  
Loop System ◽  
Temperature Control System ◽  
Closed Loop System ◽  
The Stability ◽  
Time Invariant

Abstract This paper presents an Investigation on the stability of network controlled temperature control system having Time-Invariant feedback delays, by utilizing a direct method for TDS stability analysis. A PI controller based stability analysis for temperature control system with Time invariant feedback loop delay has been constructed in this paper. The stability problem has been formulated based on the transfer function model of the closed loop system with various time delays. For different subsets of the controller parameters, based on the stability criterion’s maximal permissible bound of the network link delay that the closed loop system can accommodate without losing the stability has been computed. The effectiveness of the obtained result was validated on a benchmark temperature control system using MATLAB simulation software.

scholarly journals Stability analysis of a phase-shifted full-bridge circuit for electric vehicles based on adaptive neural fuzzy PID control

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yan Liu ◽  
Yan Huang ◽  
He Zhang ◽  
Qiang Huang
Keyword(s):  
Mathematical Model ◽  
Stability Analysis ◽  
Electric Vehicles ◽  
Pid Control ◽  
Closed Loop ◽  
Loop System ◽  
Small Signal ◽  
Fuzzy Pid ◽  
Closed Loop System ◽  
Neural Fuzzy

AbstractIn the paper, adaptive neural fuzzy (ANF) PID control is applied on the stability analysis of phase-shifted full-bridge (PSFB) zero-voltage switch (ZVS) circuit, which is used in battery chargers of electric vehicles. At first, the small-signal mathematical model of the circuit is constructed. Then, by fuzzing the parameters of PID, a closed-loop system of the small-signal mathematical model is established. Further, after training samples collected from the fuzzy PID system by adaptive neural algorithm, an ANF PID controller is utilized to build a closed-loop system. Finally, the characteristics of stability, overshoot and response speed of the mathematical model and circuit model systems are analyzed. According to the simulation results of PSFB ZVS circuit, the three control strategies have certain optimizations in overshoot and adjustment time. Among them, the optimization effect of PID control in closed-loop system is the weakest. From the results of small-signal model and circuit model, the ANF PID system has highest optimization. Experiments demonstrate that the ANF PID system gives satisfactory control performance and meets the expectation of optimization design.

scholarly journals Efficient and Novel voltage control method using DC-DC Cuk Converter under Load Variation

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Syed Mujtaba Mahdi Mudassir ◽  
Faheem Ahmed Khan ◽  
Shaziya Sultana
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Sliding Mode ◽  
Loop System ◽  
Control Mode ◽  
System Response ◽  
Switching Function ◽  
Sliding Modes ◽  
Closed Loop System ◽  
Cuk Converter

A control system is a set of mechanical or electronic devices that regulates other devices or systems by way of control loops. Typically, control systems are computerized. The mode of operation in a Control System where controlling variables is a function of the system and the structure is changed knowingly according to set of rules, which are already declared: for example a sensor based  system, is called as sliding control mode where the feedback control system response is limited and revolves around surface in the space to a point of equilibrium. In this mode of schemes, a switching variable dictates which form of control is to be used at a given instant, depending on the position of the state from the surface. First a set of points for which the switching function is null is used called as sliding surface. Sliding Mode Control (SMC) is a very robust technique which can handle sudden and large changes in dynamics of the system which can be applied to many areas like controlling of motor, aircraft and spacecraft, process control and power systems. SMC is one of the best tool in the industry to design controllers for the systems which has variable values, and provides robust properties against matched uncertainties, However,this use of SMC can only be achieved after the occurrence of the sliding mode. Before the occurrence of the switching function as null i.e. during the reaching phase, the system is affected by even matched ones. Several first order SMC applications for linear and nonlinear systems can be found in the literature [1]. Hence to eliminate the reaching phase and to make sure the ruggedness of the system throughout the entire closed-loop system response Integral Sliding Modes are used. In this paper a design procedure for sliding mode controllers for better control of voltage is applied, and then the ideas implemented are extended to all integral sliding modes in order to ensure optimum operation of entire system response[2]. Necessary conditions for the existence of sliding modes are also given. The closed-loop system is also proved to be exponentially stable. Simulation and experimental tests using the prototype of controlled DC-DC  CUK converter were performed to validate the proposed control approach.

Immersion- and invariance-based adaptive missile control using filtered signals

2012 ◽  
Vol 226 (6) ◽  
pp. 646-663 ◽  
Author(s):  
K W Lee ◽  
S N Singh
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Angle Of Attack ◽  
Loop System ◽  
Certainty Equivalent ◽  
Analytical Relation ◽  
Parametric Uncertainties ◽  
State Variables ◽  
Closed Loop System ◽  
Immersion And Invariance

The article presents a new non-certainty-equivalent adaptive (NCEA) longitudinal autopilot for the control of a missile based on the immersion and invariance theory. The interest here is to control the angle of attack of the missile in the presence of large parametric uncertainties. For the derivation of the control law, a backstepping design procedure is used. At each step of the design, certain filtered signals are generated for the synthesis of a stabilizing control signal and a parameter estimator. Using Lyapunov stability analysis, it is shown that in the closed-loop system, trajectory control of the angle of attack is accomplished, and the trajectories of the system are attracted to certain manifold in the space of state variables and parameter errors. For stability in the closed-loop system, an explicit analytical relation involving the controller gains is obtained. It may be pointed out that recently an adaptive autopilot based on the immersion and inversion theory has been designed, but it has stringent requirements because for its synthesis, the derivatives of the Mach number and angle of attack must be known, and a large number of parameters must be updated. The derived control system of this article is synthesized using only the state variables, and its identifier is of lower order. A traditional certainty-equivalent adaptive autopilot is also presented for comparison. Simulation results are obtained which show that the designed NCEA control system can accomplish angle of attack control despite large parametric uncertainties; and it can give better tracking performance than the traditional controller.

Robust generalized dynamic inversion based control of autonomous underwater vehicles

2017 ◽  
Vol 232 (4) ◽  
pp. 434-447 ◽  
Author(s):  
Uzair Ansari ◽  
Abdulrahman H Bajodah
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Closed Loop ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Dynamic Inversion ◽  
Control Law ◽  
Closed Loop System

A novel two-loop structured robust generalized dynamic inversion–based control system is proposed for autonomous underwater vehicles. The outer (position) loop of the generalized dynamic inversion control system utilizes proportional-derivative control of the autonomous underwater vehicle’s inertial position errors from the desired inertial position trajectories, and it provides the reference yaw and pitch attitude angle commands to the inner loop. The inner (attitude) loop utilizes generalized dynamic inversion control of a prescribed asymptotically stable dynamics of the attitude angle errors from their reference values, and it provides the required control surface deflections such that the desired inertial position trajectories of the vehicle are tracked. The dynamic inversion singularity is avoided by augmenting a dynamic scaling factor within the Moore–Penrose generalized inverse in the particular part of the generalized dynamic inversion control law. The involved null control vector in the auxiliary part of the generalized dynamic inversion control law is constructed to be linear in the pitch and yaw angular velocities, and the proportionality gain matrix is designed to guarantee global closed-loop asymptotic stability of the vehicle’s angular velocity dynamics. An additional sliding mode control element is included in the particular part of the generalized dynamic inversion control system, and it works to robustify the closed-loop system against tracking performance deterioration due to generalized inversion scaling, such that semi-global practically stable attitude tracking is guaranteed. A detailed six degrees-of-freedom mathematical model of the Monterey Bay Aquarium Research Institute autonomous underwater vehicle is used to evaluate the control system design, and numerical simulations are conducted to demonstrate closed-loop system performance under various types of autonomous underwater vehicle maneuvers, under both nominal and perturbed autonomous underwater vehicle system’s mathematical model parameters.

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