A variety of control systems have been proposed for aircraft autopilot systems. Traditional approaches such as proportional controller and conventional PID (CPID) controller are widely used. PID controller has a good static performance especially for linear and time-invariant systems, but a weak dynamic performance and discouraging function on nonlinear, time-varying, and uncertain systems. Fuz...

water conveyance systems (wcss) are costly infrastructures in terms of materials, construction, maintenance and energy requirements. much attention has been given to the application of optimization methods to minimize the costs associated with such infrastructures. historically, traditional optimization techniques have been used, such as linear and non-linear programming. in this paper, applica...

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...

In the context of fuzzy control, antecedent parameters are used to provide a segmentation of the state space so that different regions can be modeled appropriately. In Adaptive Critic methodologies, two modules (the critic and the controller) must properly segment the state space to insure good performance. In this paper, we explore the effects of tuning antecedent parameters that are shared be...

in this paper, the development and optimization of power distribution control strategy (pdcs) have been performed for a hybrid energy storage systems (hess) of a series hybrid electric bus (sheb). a common pdcs is based on the use of ultra-capacitor (uc) pack. a new simple pdcs is developed as a battery based one. for the battery based pdcs, four parameters are introduced for tuning the pdcs pe...

The activity of single neurons in the monkey motor cortex was studied during semi-naturalistic, unstructured arm movements made spontaneously by the monkey and measured with a high resolution three-dimensional tracking system. We asked how much of the total neuronal variance could be explained by various models of neuronal tuning to movement. On average, tuning to the speed of the hand accounte...

Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...

A new auto-tuning approach for centralized MIMO PID controllers and unknown process models is presented. Classical multivariable PID controller tuning methods are combined with iterative feedback tuning (IFT) to develop an auto-tuning method with a bounded number of tuning parameters. The method is demonstrated and validated with a steam generator example. Very good simulation results are obtai...

There are several tuning methods available for PI controllers. The Magnitude Optimum Multiple Integration (MOMI) tuning method results in a very good closed-loop response for a large class of process models. The method calculates the PI controller parameters from the process model or from the open-loop or the closed-loop time response of the process. Recently, the MOMI tuning method has been ex...

In this paper we present a conceptual framework for parameter tuning, provide a survey of tuning methods, and discuss related methodological issues. The framework is based on a three-tier hierarchy of a problem, an evolutionary algorithm (EA), and a tuner. Furthermore, we distinguish problem instances, parameters, and EA performance measures as major factors, and discuss how tuning can be direc...