A position control of a class of servomotors is addressed in this paper via a novel adaptive fuzzy PI sliding mode control. The premise and the consequence parts of the fuzzy rules are tuned with adaptive schemes. To attenuate chattering effectively, the discontinuous control is approximated by an adaptive PI control structure. Moreover, the bound of the discontinuous control term is assumed to be unknown, and an adaptive mechanism is used to estimate this bound. All adaptive laws are derived via Lyapunov synthesis method, thereby guaranteeing the closed-loop stability. The proposed approach has the added advantage that, for external disturbances, it only requires a bound to exist, without needing to know the magnitude of this bound. The proposed controller is applied to control a model of uncertain induction servomotor subject to significant disturbances and a model of DC servomotor with unknown parameters and uncertainty in load condition. The analysis of simulations reveals the effectiveness of the proposed method in controlling servomotors in terms of significant reduction in chattering while maintaining asymptotic convergence.

This paper proposes an adaptive fault tolerant attitude controller, based on variable structure control, to address tracking control problem of spacecraft in the presence of unknown actuator failure, control input saturation and external disturbances. In contrast to traditional robust fault tolerant attitude controllers, the proposed controller is capable of controlling the transient response of the closed loop system by means of a dedicated parameter. Also this method does not require exact knowledge of the actuator faults and is implemented with uncertain value of fault information. By adjusting a simple parameter dynamically and using Lyapunov direct method and the properties of quaternion representation, the ultimate boundedness of attitude and angular velocity errors in presence of external disturbances is proven. Numerical simulations used to prove the success of proposed controller in achieving high attitude performance in the presence of external disturbances, inexact knowledge of fault information, actuator failures and control input saturation.

In this paper, a new approach for network planning in unbundled power systems is presented. The approach takes into account the desires of demand customers, power producers, system operator, network owner(s), and regulator in network planning. Competition, reliability, flexibility of operation, transmission expansion cost, and environmental impacts are used as planning criteria. In order to consider the importance degrees of stakeholders and planning criteria in network planning, first importance degrees of stakeholders and planning criteria are determined by a presented new method. Then, importance degrees of stakeholders and planning criteria are aggregated with appropriateness degrees of expansion plans to compute a fuzzy index for measuring the goodness of expansion plans. The final plan is selected using the presented fuzzy risk assessment method. The approach is applied to an eight-bus test system

This paper presents a novel fuzzy model and a fuzzy logic controller for an isolated signalized intersection. The controller controls the traffic light timings and phase sequence to ensure smooth flow of traffic with minimal waiting time and length of queue. Usually fuzzy traffic controllers are optimized to maximize traffic flows/minimize traffic waiting time under typical traffic conditions. Consequentially, these are not the optimal traffic controllers under exceptional traffic cases such as roadblocks and road accidents. We apply state-space equations to formulate the average waiting time vehicles in traffic network at fixed time control. also, We propose a novel fuzzy model and new fuzzy traffic controller that can optimally control traffic flows under both normal and exceptional traffic conditions. Results show that the performance of the proposed traffic controller at novel fuzzy model is better that of conventional fuzzy traffic controllers under normal and abnormal traffic conditions.

In this paper, qualitative and quantitative differences between nonlinear and linear modal simulations in stressed power systems are presented. For the first time in the literature, time-domain nonlinear simulation is used to validate the accuracy of the second order modal model, obtained by using modal series. Furthermore three new selective indices are defined and used to explain and predict the differences between nonlinear and linear modal simulations. These indices also explain the under or over damping results being experienced when a linear system theory designed controller is applied to a nonlinear system.