A neuro-adaptive control system was designed to control the knee joint flexo-extension movements in accordance with desired trajectories, through electrical stimulation of quadriceps muscles. This control system consist in an Artificial Neural Network (ANN) used as inverse model and an adaptive ANN trained on PID output which performs a feedback adjustment of control signal. The neuro-adaptive ...

This paper proposes a fuzzy PID control method for deburring industrial robots. The adaptive fuzzy PID controller relates to the trajectory and joint angular parameters of the end-effector on a robot. The PID controller parameters update online at each sampling time to guarantee trajectory accuracy of the end-effector. The simulation of the fuzzy PID control is provided based on the 6-DOF debur...

This paper presents a novel adaptive fuzzy controller approach of brushless DC motors (BLDCM) without hall sensors. The fuzzy controller adopts fuzzy logic to retune the PID parameters online. Based on the mathematical model of BLDCM introduced, a novel adaptive fuzzy control strategies have been designed in MATLAB/SIMULINK. The results have been recorded under various operating conditions. The...

This paper presents the development and implementation of a hybrid controller to automatically levitate and precisely regulate the position of a suspended rotor in Active Magnetic Bearing system. The inherent nonlinearity and open-loop instability of AMBs present challenges for design a controller and the problem can be formulated as a dynamic, multivariable optimization problem. A single neuro...

Numerical Control, NC, machine tool feed servo systems are time-varying, but with the poor anti-interference of conventional PID control it is difficult to achieve satisfactory setting effect. Thus this paper puts forward an online adaptive fuzzy PID setting strategy. Further, in order to improve the control performance of fuzzy PID controllers, we use a genetic algorithm to set the initial PID...

The concentration of dissolved oxygen (DO) in the aeration tank(s) of an activated sludge system is one of the most important process control parameters. The DO concentration in the aeration tank(s) is maintained at a desired level by using a Proportional-Integral-Derivative (PID) controller. Since the traditional PID parameter adjustment is not adaptive, the unknown disturbances make it diffic...

This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID c...

PID control is widely used in air conditioning system. The algorithm is simple but has a long response time, and the adjustment is not flexible. In this paper, we propose a method of optimizing PID controller parameters based on adaptive genetic algorithm. Specifically, the fitness function with penalty terms is added to the classical genetic algorithm and adaptive crossover and mutation factor...

We introduce a novel and robust active queue management (AQM) scheme based on a Proportional-IntegralDerivative (PID) controller, called Neuron PID, that uses an adaptive neuron to tune its parameters. We demonstrate by simulations that Neuron PID stabilizes the router queue length regardless of the round trip delay better than other well-known AQM algorithms.