In this paper, a combination of a multi-layer quantum neural network (QNN) with the particle
swarm optimization (PSO) algorithm is used with the aim of controlling a continuous stirred …

A particle swarm optimization algorithm and neural network like self-tuning PID controller for
CSTR system is presented. The scheme of the discrete-time PID control structure is based …

In this study, a control system was designed to control the robot's movement (The Mitsubishi
RM-501 robot manipulator) based on the quantum neural network (QNN). A proposed …

Due to outstanding learning capabilities, neural networks have attracted a great deal of
research interests and various structures for them have been presented. Quantum neural …

The conventional parameter optimisation of PID controller is easy to produce surge and big
overshoot, and therefore heuristics such as genetic algorithm (GA), particle swarm …

This paper proposes a particle swarm optimization (PSO) tuned novel proportional integral
derivative (PID) like neural network (PSO-PID-NN), to control the temperature of a nonlinear …

After having enjoyed an increasingly great popularity in Japan during the last two decades,
Fuzzy Logic Control (FLC) systems have been investigated in many technical and industrial …

The temperature system of the Continuous Stirred Tank Reactor (CSTR) has the
characteristics of strong nonlinearity and uncertain parameters. The linear PID controller …

In this paper, an adaptive proportional-integral-derivative (PID) controller based on a
quantum neural network (APIDC-QNN) is introduced. In the proposed neural network …

This paper presents the optimal design of PID controller based on a particle swarm
optimization (PSO) approach for continuous stirred tank reactor (CSTR). The mathematical …