The objective of this paper is to compare the time specification performance between two conventional controllers for an inverted pendulum system. The goal is to determine which control strategy delivers better performance with respect to pendulum's angle and cart's position. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. Two controllers are presented such as Linear-Quadratic-Regulator (LQR) andProportional-Integral-Derivatives (PID) controllers for controlling the linearized system of inverted pendulum model. Simulation study has been done in Matlab simulink environment shows that both controllers are capable to control multi output inverted pendulum system successfully. The result shows that LQR produced better response compared to PID control strategies and is presented in time domain.

The raised complicatedness of the dynamics of a robot manipulator considering joint elasticity makes conventional model‐based control strategies complex and hard to synthesize. This paper presents investigations into the development of hybrid intelligent control schemes for the trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, a collocated proportional‐derivative (PD)‐type Fuzzy Logic Controller (FLC) is first developed for the tip angular position control of a flexible joint manipulator. This is then extended to incorporate a non‐collocated Fuzzy Logic Controller, a non‐collocated proportional‐ integral‐derivative (PID) and an input‐shaping scheme for the vibration reduction of the flexible joint system. The positive zero‐vibration‐derivative‐derivative (ZVDD) shaper is designed based on the properties of the system. The implementation results of the response of the flexible joint manipulator with the controllers are presented in time and frequency domains. The performances of the hybrid control schemes are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed

This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method.

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