Fractional filter IMC-PID controller design for an unstable inverted pendulum system

2017 ◽  
Author(s):  
R. Ranganayakulu ◽  
G. Uday Bhaskar Babu ◽  
A. Seshagiri Rao
Keyword(s):  
Pid Controller ◽  
Inverted Pendulum ◽  
Controller Design ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Pid Controller Design ◽  
Fractional Filter

Optimisation of a PID Controller for an Inverted Pendulum Using the Bees Algorithm

2015 ◽  
Vol 789-790 ◽  
pp. 1039-1044 ◽  
Author(s):  
Muhammed Arif Sen ◽  
Mete Kalyoncu
Keyword(s):  
Pid Controller ◽  
Inverted Pendulum ◽  
Controller Design ◽  
Stable State ◽  
Bees Algorithm ◽  
Pid Controllers ◽  
Pendulum System ◽  
Tuning Method ◽  
Inverted Pendulum System ◽  
Optimal Gains

The inverted pendulum system is a challenging control problem in the control theory, which continually moves away from a stable state. The paper presents the design of a Proportional-Integral-Derivative (PID) controller for a single-input multi-output (SIMO) inverted pendulum system and using the Bees Algorithm (BA) to obtain optimal gains for PID controllers. The Bees Algorithm optimizes the gains so that the controller can move the cart to a desired position with the minimum amount of the change in the pendulum’s angle from the vertically upright position during the movement. The tuning aim is to minimize the control responses of the cart’s position and the pendulum’s angle in time domain. MATLAB/Simulink simulation has been performed to demonstrate that the effects on the system performance of PID controllers with optimal gains. The obtained results show that the tuning method by using the Bees Algorithm produced PID controllers successfully within the controller design criteria. Following a description of the inverted pendulum system and the Bees Algorithm, the paper gives the obtained simulation results for the system demonstrating the efficiency of the design.

Robust Stabilizing Controller Design for Inverted Pendulum System

2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Hazem I. Ali
Keyword(s):  
Steady State ◽  
Time Domain ◽  
State Feedback ◽  
Inverted Pendulum ◽  
Controller Design ◽  
H Infinity ◽  
Pendulum System ◽  
Stabilizing Controller ◽  
Inverted Pendulum System ◽  
System Uncertainties

In this paper the design of robust stabilizing state feedback controller for inverted pendulum system is presented. The Ant Colony Optimization (ACO) method is used to tune the state feedback gains subject to different proposed cost functions comprise of H-infinity constraints and time domain specifications. The steady state and dynamic characteristics of the proposed controller are investigated by simulations and experiments. The results show the effectiveness of the proposed controller which offers a satisfactory robustness and a desirable time response specifications. Finally, the robustness of the controller is tested in the presence of system uncertainties and disturbance.

scholarly journals Integrated SolidWorks and Simscape platform for the design and control of an inverted pendulum system

2020 ◽  
Vol 71 (2) ◽  
pp. 122-126
Author(s):  
Ahmed Alkamachi
Keyword(s):  
Inverted Pendulum ◽  
Controller Design ◽  
State Feedback Control ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Control Scheme ◽  
Implicit System ◽  
Physical Elements ◽  
And Control ◽  
The Mathematical Model

AbstractA single inverted pendulum on a cart (SIPC) is designed and modeled physically using SolidWorks. The model is then exported to the Simulink environment to form a Simscape model for simulation and test purposes. This type of modeling uses a physical grid tactic to model mechanical structures. It requires connection of the physical elements with physical signal converter to define the implicit system dynamics to be modeled. The integration between the SolidWorks and Simscape eliminates the need of deriving the mathematical model and provides a platform for the rapid controller design for the system. State feedback control scheme is proposed, designed, and tuned aiming to maintain the pendulum in the upright place while tracking the desired cart position. Several simulation cases are studied to prove the controller abilities. In order to examine the controller robustness, disturbance rejection and noise attenuation capabilities are also discovered.

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