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Robotic manipulators are used in wide range of industrial applications. These are highly complex, multi-input multi-output and coupled systems requiring efficient control mechanism. This complexity is further enhanced as the number of links is increased. PID control is the most widely employed control scheme in the manufacturing industry but conventional tuning approaches for tuning PID gains do not...
This paper presents a Teacher Learning Based Optimization (TLBO) approach to tune the backstepping controller for effective control of a single-link flexible-joint manipulator. To assess the relative performance of TLBO, comparative studies have been carried out with the two other popular optimization techniques namely genetic algorithm and cuckoo search algorithm. The integral absolute error was...
This paper presents a Cuckoo Search Algorithm (CSA) based tuning scheme to improve the performance of a tunneling accelerometer. CSA has been employed to tune the parameters of the used PD controller, in closed loop with the sensor, for minimum settling time. A comparative study has also been conducted between the sensor responses obtained from the CSA and Genetic Algorithm (GA) tuned controllers...
This paper presents a comparative study of Backstepping controllers based on Barrier Lyapunov Function (BLF) and Quadratic Lyapunov Function (QLF) for stabilising the vertical displacement of a quarter car active suspension system. Hard constraints of the suspension system such as suspension travel, dynamic tyre load and actuator saturation are maintained in presence of uncertain sprung mass. Two...
Proportional — Integral — Derivative (PID) controller performs well for linear systems. For systems with nonlinearity, controller parameters need to be tuned every time for new operating point to obtain ‘local gain parameters’. These local gain parameters are not sufficient to get satisfactory performance at other operating points. In this paper a novel approach ‘Aggregate Fitness Function’ is presented...
Traditional tuning techniques for classical Proportional-Integral-Derivative (PID) controller suffer from many disadvantages like non-customized performance measure and insufficient process information. For the past two decades nature inspired optimization algorithms are efficiently being implemented for tuning of PID controllers. In this paper, four optimization methods namely Genetic Algorithm (GA),...
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