مجله کنترل
سال شانزدهم شماره 4 (زمستان 1401)

In this paper, by utilizing the finite-time robust nonlinear control approach, the maximum power point tracking problem is discussed and investigated for a closed-loop photovoltaic system. First, a comprehensive dynamical model for the photovoltaic system is introduced and elaborated. Next, to achieve the maximum power point, reference values for current and voltage of the photovoltaic module are determined by mathematical analysis. By defining tracking errors and two auxiliary variables, it is mathematically demonstrated that the maximum power point tracking problem of an uncertain photovoltaic system is equivalent to the global finite-time stabilization problem of an equilibrium point associated with an uncertain second order nonlinear system. By developing the terminal sliding mode control and defining several innovative sliding manifolds, three different types of finite-time robust nonlinear controllers are designed and proposed to accomplish the maximum power point tracking goal for the closed-loop photovoltaic system. By applying several lemmas, it is proven that all proposed controllers are able to guarantee the mentioned stability of the closed-loop photovoltaic system in the presence of uncertainties. In proposed control schemes, the convergence finite time depends on the values of arbitrary constants and, in consequence, by choosing proper values for these constants, the aforementioned finite time would be reduced significantly. Eventually, three proposed control schemes are numerically simulated onto the photovoltaic system and simulation results illustrate that the suggested controllers properly fulfill and provide the maximum power point tracking objective.

Drum water level control loop is one of the most important control loops in any steam power plant. In case of unacceptable performance of this loop, we have reduction of power plant efficiency, failure of equipment or maybe power plant shut down. Since in this loop, we use the feed water control valve as final control element, is very important to have minimum swing as possible in order to increase of the life cycle control valve. In this paper, to achieve this objective, a new adaptive control algorithm is proposed which have good life cycle control valve, to reduce the disturbance effect due to steam demand variation, to consider drum thermodynamic nonlinear characteristics and to robust to dynamical parameters variation. In order to evaluate the performance of proposed algorithm in real industrial situation, this algorithm is applied to Qom combined cycle power plant boiler No 11 drum water level dynamical model. The simulation results using this algorithm and power plant classical controller, sliding mode control, Auto-tune fraction order PID show the proposed algorithm regarding the life cycle of feed water control valve and control loop performance in different conditions has better performance compared to these algorithms.

The model-based controllers need a mathematical model of the system, whereas the data-driven controllers operate based on measuring the input-output data. Nowadays, considering complexity of the industrial systems and unavailability of an accurate mathematical model of the system, scientists try to reduce dependency of the controllers on the mathematical model. In this paper, an adaptive sliding-mode data-driven controller for a class of unknown multi-input multi-output nonlinear discrete-time systems is proposed. Because the chattering phenomenon is the main challenge of the sliding-mode controllers, an adaptive sliding-mode controller is used to solve this problem. In addition, to solve the dependencies of the controller on the mathematical model, the proposed adaptive sliding-mode controller is combined with a data-driven controller. Next, the new adaptive laws for the switching gain and the Pseudo Jacobian Matrix (PJM) are calculated. In addition, the closed-loop stability based on the Lyapunov theory is investigated. To show performance of the controller, the proposed method is applied to a three-tank system. The proposed controller has some advantages in comparison with similar methods in references, such as reducing the conservatism and complexity in the controller design and simplifying the closed-loop stability analysis. The simulated results show that the proposed method better tracks the reference signals and improves rejection of the external disturbances. Furthermore, the chattering phenomenon is considerably reduced.

The sense of approximate reasoning within fuzzy logic, in contrast to precise reasoning within classical logic, provided an intuitive way of handling many of the world’s difficult problems. But can fuzzy logic, by itself, handle the sort of uncertainty that we find in the class of open world problems? Recently, Zadeh introduced an extension of fuzzy logic that means being flexible while looking for new solutions. The concept of f-transformation is one of the fundamental concepts in extended fuzzy logic, it is important to define f-transformed set up to develop extended fuzzy logic. This f-transformed set is named as f-set. On the other hand, in order to translate the hierarchy into an approximated argument process in extended fuzzy logic, it is necessary to rank the f-sets. In fact, f-sets, in most cases, may overlap in two their parallel spaces of possibility and validity, while their ranking is done in possibility space. This property of f-sets raises further questions: how would f-sets be ranked when their fuzzy validity set of one covers another? These and other questions surrounding the ranking of f-set numbers raise challenging issues. To meet these challenges and to have a proper ranking and to interact with the two parallel spaces of validity and possibility, we have incorporated the concept of equilibrium in the form of validity constrained optimality in ranking for the first time. The proposed ranking approach is applied to examples taken from previous comparative studies from the literature and compared with their results. In addition, to illustrate efficiency, the proposed approach has been evaluated through the help of disease diagnosis, which is one of the scientific today requests by a case study of aphasia diagnosis.

In this paper, the performance improvement problem of a reference trajectory tracking for a car-like mobile robot with nonholonomic constraints in the presence of external disturbances, nonlinearities and uncertain parameters is investigated. For this purpose, at first the dynamic and kinematic equations of the car-like mobile robot are expressed and then the look-ahead control method in two dimensional is used for the tracking of the car-like mobile robot. The purposed controller will be designed by using the dynamic surface control method with the reinforcement learning based on the actor-critic neural network and an adaptive robust controller is proposed to compensate the effects of external disturbances. Moreover, the prescribed performance control method will be utilized to improve the transient state and steady state. An actor neural network is used to estimate unknown nonlinearities and uncertainties and a critic neural network is employed to evaluate system performance. In the sequel, the direct Lyapunov method will be used to prove the closed-loop control system stability and uniform ultimate boundedness of tracking errors. Finally, the effectiveness and efficiency of the proposed control scheme are confirmed by using MATLAB software.

Unfalsified adaptive control strategy is a data-driven approach in robust adaptive control that selects the stabilizing controller from an the available control bank based on the input-output system’s data. Selection is done without activating the controllers by using the virtual reference signal and a cost function. Stability of the closed loop system is guaranteed. In this paper, inspired by the unfalsified control approach, the goal is to select a controller from the available pre-designed controller bank that has the highest level of disturbance attenuation. The selection is based on the system’s data by using a cost function without disturbance measurement. By introducing a new concept called virtual disturbance, the performance of controllers is evaluated without activation. The convergence of the algorithm and the disturbance attenuation level of the proposed method have been proven in a theorem. Simulation results show performance of the proposed method on a wind turbine for various wind speed disturbances.

This paper propounds a distributed observer design for a class of nonlinear systems with time delays and applying uncertainty in an undirected network. In particular, each distributed observer has availability, to partial output as it communicates with its neighboring observers through consensus protocols defined on the undirected network. The network includes M local observers where adjacent observers transmit and receive data through a delayed telecommunication graph network with uncertainty. The design method is based on Lipschitz condition of nonlinear terms. Appropriate selection of Lyapunov functions is created, and the Jensen inequality applied in undirected network. Also, by the design algorithm, the necessary and sufficient conditions for the design of parameters are defined so as to stabilize the error dynamics. Finally, numerical simulations are provided to contrast the effectiveness of the proposed method.