مجله کنترل
سال هشتم شماره 2 (تابستان 1393)

In this paper، we introduce the proportional-integral kalman filter for discrete time systems with unknown input. The Proportional-Integral observers (PIOs) have good performance in deal with uncertainty in model، while those cannot handle the effect of determinstic unknown inputs. On the other hand، the Unknown Input Kalman filter (UIKF) is sensitive to uncertianty، while it provides unbiased minimum-variance estimation in the presence of unknown input. Here، we introduce Unknown Input Proportional Integral Kalman filter (UIPIKF) as an unbiased minimum-variance estimator in the presence of uncertainty and unknown input in the model. Using a numerical example، the effectivness of the filrer is demonstrated.

Visual servoing system is a system to control a robot by visual feedback so that robot drives from any arbitrary start position to the target positions. Various ways، including control by using model of the robot، designing controller directly، and using Jacobian matrix have been studied. Since there is not access to model of robot and obtaining a model of robot would be difficult and time consuming، in many cases، the control law is obtained using Jacobian matrix. In this paper، inverse of Jacobian matrix is approximated using artificial neural networks. The approximated neural models are used in control law directly. For each degree of freedom of the robot manipulator، a two-layer feedforward neural network is considered. The distance between end-effector and target along the x-axis and y-axis، and the shoulder joint coordinates along the x-axis and y-axis are the inputs of each of the networks and the outputs are the fraction of the related robot joint changes to the image features changes (the elements of the inverse of Jacobian matrix). The proposed method has been implemented on a real robot manipulator. The experimental results show that the proposed control system can move the end-effector to different target positions in workspace with good accuracy.

Desirable performance of Anti-lock braking system for any kind of road with its specific qualities in a certain amount of slip occurs، Thus regulation the optimum wheel slip leading to better performance and the car without locking the wheels stopped in a short time after braking. Anti-lock braking system is a nonlinear system with uncertainties، based on the quality of the road which makes it difficult to control wheel slip. The purpose of this paper is designing the sliding mode controller for independent control of vehicle wheels slip or in other words regulate the wheel slip to the reference slip. In this paper، we have presented a model of car with four wheels and the purpose is independent control of each wheel slip. In the evaluation phase of designed controllers، CARSIM simulator has been used which is one of the most prestigious simulator and used the real model of the car. The simulation results show better performance of the controller designed with the method of sliding mode control compared to the conventional methods.

This paper proposes the design of a nonlinear optimal controller for a submarine with nonlinear model with six degrees of freedom (6-DOF). The control aims includes achieving system stability، reaching the submarine to a desirable point at the end of the maneuver، and choosing the optimal path that are accessible by solution of optimal cost function. The novelty of this paper is the systematic step selection in the gradient descent algorithm that has increased the rate of convergence beyond two times rather than fixed step algorithm. Finally، via some simulations، the robust performance of the designed controller for moving in different depths with considering of parametric uncertainty has been confirmed.

In this article a horizontal guidance algorithm for an unmanned air vehicle is proposed، based on trajectory waypoints and legs between them. Design is done in two phases. For straight legs، a line following algorithm is designed، with consideration of autopilot dynamics، and for turn from active leg to next one، a turn guidance algorithm is proposed. Turn guidance algorithm is designed in two steps. At the first step، a desired trajectory is selected and then an algorithm is proposed to shape the trajectory according to the desired trajectory. Also with consideration of maximum lateral acceleration of the UAV and no jumping in lateral acceleration command at the beginning of turning phase، start and end point of the turn is determined to minimize the turn trajectory from legs.

In this paper، a nonlinear and robust guidance system against target maneuvers has been designed. For this purpose، first a new high order sliding mode algorithm is proposed. The designed guidance law with this algorithm generates a smooth acceleration command that guarantees collision with target. In this algorithm، unlike previous high order sliding mode theories، the stability of close loop system in the presence of uncertainty is guaranteed، therefore the observer is not required for estimation of target maneuvers in the proposed guidance law. For designing two point guidance law using this algorithm، a sliding variable has been introduced using relative lateral velocity. Designed guidance law generates acceleration commands that guarantee convergence of sliding variable. Simulation results show the better performance of proposed guidance law in comparison with other guidance laws.