مجله کنترل
سال چهاردهم شماره 1 (بهار 1399)

In this paper, an algorithm is proposed to improve the design of constrained PID controller based on convex-concave optimization. This design method is based on the optimization of a performance cost function, taking into account the stability and efficiency constraints with frequency domain analysis in which the concepts of sensitivity and complementary sensitivity has been used. It is shown, using a counter example that the previous methods are not effective for some systems, the optimization problem becomes unbounded and interrupts. To solve this problem, attentions are paid to conditions that the optimization problem fails to have any response, and then previous limitations are eliminated by representing a new designing method. The performance of the proposed method is shown by applying it to the counter example. In the end, the controller is designed for an unstable system.

In this paper, the event-triggered strategy in the case of finite-horizon model predictive control (MPC) is studied and its advantages over the input to state stability (ISS) Lyapunov based triggering rule is discussed. In the MPC triggering rule, all the state trajectories in the receding horizon are considered to obtain the triggering rule. Clearly, the finite horizon MPC is sub-optimal with respect to the infinite-horizon case. This sub-optimality is considered as a coefficient to implement the MPC triggering rule and to increase the inter-execution time. However, to design a proper processing board to control this coefficient suitably, it is necessary to specify lower and upper bounds for it. The contribution of this paper is to determine an effective upper bound for this coefficient. By incorporating the sub-optimal lower bound instead of being 1, the conservatism decreases. This coefficient can be used as a tunable parameter in integrated or network control systems to compromise between the performance and inter-execution time. Simulation results depict the applicability of the proposed method and validate the theoretical results.

in this paper a new algorithm has been proposed to predict unplanned islanding. To predict unplanned islanding, rotor angle and speed time series have been used. Times of fault occurrence and clearance are estimated using monitoring system response based on the variation of phasor measure data. The estimated times of fault occurrence and clearance are used to determine suitable calculation window for uncontrolled islanding prediction. The proposed algorithm is applied to IEEE 39 bus test system. The result shows that the objective function can be used to estimate fault occurring and clearance time to predict unplanned islanding.

Three phase induction motors have many applications in industries. Consequently, detecting and estimating the fault and compensate it in a way that the faulty induction motor satisfies the predefined goals are important issues. One of the most common faults in induction motors is the short circuit of the stator winding. In this paper, an active fault-tolerant control system is designed and presented to compensate the effect of the short circuit fault in the stator of a three-phase induction motor. The introduced fault tolerant control system consists of an exponential unknown input observer to detect and estimate the fault. Also, based on the estimation results, control signals are made by employing a sliding mode controller to compensate the short circuit of the stator winding. The efficiency of the proposed system includes, fault detector, fault estimator and controller, is shown using simulation results.

The design of integrated guidance and control system for flying objects is one of the research fields in the aerospace that is considered by researchers in recent years. Due to the nonlinearity of the kinematic and dynamic equations of the homing interceptors in the terminal phase and also existence of uncertainties such as target maneuvers, external disturbances and variations in aerodynamic coefficients, siding mode control theory is a suitable method for designing integrated guidance and control system. One of the most problem of sliding mode is the presence of high frequency oscillations in the control signal that is called chattering, which makes it impossible to implement this controller. A method for smoothing the control signal in a sliding mode is to use a disturbance observer. In this paper, the control signal is completely smooth, with having the disturbances estimation and using a different scheme compared with standard sliding mode. Also, the finite time convergence is guaranteed in the presence of uncertainty. The proposed guidance and control system are evaluated in computer simulation.

Based on learning control methods and computational intelligence, control of quantum systems is an attractive field of study in control engineering. What is important is to establish control approach ensuring that the control process converges to achieve a given control objective and at the same time it is simple and clear. In this paper, a learning control method based on genetic quantum controller approach is presented. For tracking a time variant function trajectory, in a closed quantum system, the presented controller is used. For this purpose a constrained optimization problem, based on minimization of difference between a given trajectory and system states subject to an iteration relation of the dynamical solution be satisfied, is designed. According to high convergence rate in quantum genetic algorithm, a quantum genetic algorithm for solving the optimization problem is used. A stochastic measure for observation the initial population is used. Efficient an optimal tracking, with at least tracking errors and at least learned chattering are advantages of the presented method. A couple of examples for demonstrating the advantages are simulated. Simulation results reflect the good performance of the proposed method for controlling the quantum systems.

In this paper, a complete dynamical model is presented for an uncertain -DOF robot manipulator containing description of sector and dead-zone nonlinearities. Next, robust finite-time tracking problem of desired trajectories is declared and formulated for the aforementioned robot manipulator. By defining innovative nonlinear sliding manifolds and developing the nonsingular terminal sliding mode control, several types of input torques are designed to exactly reach configuration variables of robot's joints to desired paths within the finite times in the presence of uncertainties, sector and dead-zone nonlinearities. By utilizing some applicable lemmas and well-known inequalities, for each class of the proposed input torques, the global finite-time stability of the closed-loop robot system is proven analytically. Also, several new formulas are extracted for determining the convergence finite times of the closed-loop system. These formulas demonstrate that mentioned times are dependent on robot's initial conditions and optional parameters of the suggested torques. Finally, by using MATLAB software, all classes of the designed torques are numerically simulated onto the SCARA industrial robot manipulator and obtained results show the acceptable performance of the suggested control scheme.

In this paper, kinematic and dynamic equations of a 6-DOF (Degree Of Freedom) autonomous underwater vehicle (6-DOF AUV) are introduced and described completely. By developing the nonsingular terminal sliding mode control method, three separate groups of control inputs are proposed for the autonomous underwater vehicle subjected to uncertainties including parametric uncertainties, unmodeled dynamics, and unknown disturbances from ocean. All classes of suggested inputs are able to steer the mentioned underwater vehicle to the desired path within finite times. For all of them, innovative nonlinear sliding surfaces are defined possessing several optional parameters. The global finite-time stability is proven for the closed-loop system of the aforementioned underwater vehicle injected by each class of proposed inputs. More, three applicable inequalities are derived to determine the convergence finite times related to suggested inputs. Obtained inequalities reveal that the mentioned finite times are dependent on initial conditions and optional parameters of control inputs. Finally, three suggested inputs are separately simulated on the Naval Postgraduate School Autonomous Underwater Vehicle II (NPS AUV II). Simulation results illustrate that all proposed inputs can fulfill the trajectory tracking objective for the NPS AUV II properly.