2022
DOI: 10.1371/journal.pone.0266728
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Performance comparison of structured H ∞ based looptune and LQR for a 4-DOF robotic manipulator

Abstract: We explore looptune, a MATLAB-based structured H ∞ synthesis technique in the context of robotics. Position control of a 4 Degree of Freedom (DOF) serial robotic manipulator developed using Simulink is the problem under consideration. Three full state feedback control systems were developed, analyzed and compared for both steady-state and transient performance using the Linear Quadratic Regulator (LQR) and looptune. Initially, a single gain feedback controller was synthesized using LQR. This system was then mo… Show more

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Cited by 6 publications
(3 citation statements)
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“…However, they rely upon empiricallydefined rules or large sets of training data which are not only hard to acquire but also put an excessive computational expense on the embedded processor [9]. The Linear-Quadratic-Regulator (LQR) is a state-space controller that minimizes a quadratic performance index of the system's state-variations and control-input to deliver the optimal control decisions [10]. Despite its benefits, the LQR is incapable to address identification errors, model variations, and environmental indeterminacies [11,12].…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, they rely upon empiricallydefined rules or large sets of training data which are not only hard to acquire but also put an excessive computational expense on the embedded processor [9]. The Linear-Quadratic-Regulator (LQR) is a state-space controller that minimizes a quadratic performance index of the system's state-variations and control-input to deliver the optimal control decisions [10]. Despite its benefits, the LQR is incapable to address identification errors, model variations, and environmental indeterminacies [11,12].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Currently, there are numerous research efforts focused on robust H1 control of robots. For instances [17], proposed an H1 control approach for a 6-degree-of-freedom (DOF) manipulator, and the proposed control law is effective for optimizing settling time, overshoot and steady state error for each joints [18], proposed a MATLAB-based structured H1 control approach for the position control of a 4-DOF serial arm studied by Simulink [19], has proposed an H1 control approach for the multi-DOF arm with flexible and stable joints [20], has proposed an asynchronous H1 continuous control approach for the mode-dependent switched mobile robot system [21], has proposed an H1 control of a flexible and stable cable-driven parallel robot [22], has proposed an H1 feedback control approach for the underwater vehicle systems with various communication topology and external disturbances. However, it is noted that the H1 controllers are typically designed and solved offline, meaning that the control design process occurs before the actual deployment of the system [23].…”
Section: Introductionmentioning
confidence: 99%
“…A control algorithm that combines Fast integral Sliding-mode Control (FIT-SMC) with a Robust Exact Differentiator Observer (RED) and Feedforward Neural Network-based Estimator (FFNN) is presented in [28]. In [29], the control techniques of the Linear Quadratic Regulator (LQR) and Integral Proportional (PI) and Integral (I) are applied and compared for the position control of a serial robotic manipulator with 4 Degrees of Freedom (DOF). In [30] considers a non-singular terminal slip-mode controller using an optimization technique using a hybrid metaheuristic method for a robotic manipulator with three degrees of freedom.…”
Section: Introductionmentioning
confidence: 99%