The handling of various input constraints in the self-tuning generalized predictive control (STGPC) problem of ARIMAX/ARMAX systems is considered. The methods based on the Lagrange multipliers and Lemke’s algorithm are used to solve the constrained optimization problem. A self-tuning controller is implemented in an indirect way, and the considered constraints imposed on the control input signal...

The problem of manipulator control is a highly complex problem of controlling a system which is multi-input, multioutput, non-linear and time variant. In this paper some adaptive fuzzy, and a new hybrid fuzzy control algorithm have been comparatively evaluated through simulations, for manipulator control. The adaptive fuzzy controllers consist of self-organizing, self-tuning, and coarse/fine ad...

Parallel robots exhibit good performance in terms of rigidity, accuracy, and dynamic characteristics. However, parallel robots have complex configurations and their dynamic model is highly nonlinear, and conventional PID controllers are not sufficiently robust for their motion control. In this paper, we have investigated the intelligent control of a hydraulically driven parallel robot based on ...

in this study, a new approach for control (treatment) of aids based on patient entry drug. one of the main problems related to aids, is lack of control, lack of identification and early treatment of this disease. today physicians more than anything, control the disease relying on their experience and knowledge and time-consuming and complex experiments, nevertheless, human errors are inevitable...

Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial basis function neural network (RBF) with G...

This article presentes a PID controller for two area power system equipped with both automatic generation control and automatic voltage regulator loops. The research has been done to control two area power systems with PSO optimized self-tuning PID controller. The comparison between different controllers and the suggested PSO based controller illustrates that the proposed controller can generat...

This chapter presents the design, development and implementation of a novel proposed online-tuning Gain Scheduling Dynamic Neural PID (DNN-PID) Controller using neural network suitable for real-time manipulator control applications. The unique feature of the novel DNN-PID controller is that it has highly simple and dynamic self-organizing structure, fast online-tuning speed, good generalization...

This paper gives a study of how to carry out a combined refrigerant volume control using an electronic expansion valve (EEV) and the specific measures to apply selftuning fuzzy algorithm to refrigeration control system. The simulation analysis on the superheat fuzzy controller was completed by Simulink. Different scale factors and weight factors were employed during the process, and their effec...

The performance optimization of induction motor speed control system is studied and self-tuning PID controller based on diagonal recurrent neural network (DRNN) is presented in this paper. Neural network control does not require the precise mathematical model of the system, and it only needs to train neural network online or offline, then use the training results to design the control system. I...

model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...