Sharif Digital Repository

Integrated guidance and control of an elastic flight vehicle based on constrained robust model predictive control is proposed. The design is based on a partial state feedback control law that minimizes a cost function within the framework of linear matrix inequalities. It is shown that the solution of the defined optimization problem stabilizes the nonlinear plant. Nonlinear kinematics and dynamics are taken into account, and internal stability of the closed-loop nonlinear system is guaranteed. The performance and effectiveness of the proposed integrated guidance and control against non-maneuvering and weaving targets are evaluated using computer simulations  

Utilizing model predictive controllers (MPC) as an active queue management scheme is investigated in this paper. Model based prediction of future output and determining optimized value of the control signal have made MPC as an advanced control strategy in various modern control systems. In this paper a new approach is proposed to alleviate the computational complexity of MPC in order to implement in fast dynamics systems like computer networks. Neural network approximation of MPC as an active queue management (AQM) method implemented here not only has less computational burden with respect to the common MPC approaches, but also results in better performance compare to the well-known AQM... 

This paper addresses a nonlinear model predictive controller design for a single-phase PFC rectifier exploiting the Sheppard-Taylor converter. After approximation of the tracking error in the receding horizon by its Taylor-series expansion to any specified order, an analytic solution to the MPC is developed and a closed-form nonlinear predictive controller is introduced. The proposed nonlinear model predictive control (NMPC) derived using approximation can stabilize the original nonlinear systems if certain conditions, which can be met by properly choosing predictive times and the order for Taylor expansion, are satisfied. The main advantage of this digital control method is that unity power... 

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. the nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in... 

In this paper, different model predictive control synthesis frameworks are examined for DCDC quasi-resonant converters in order to achieve stability and desired performance. The performances of model predictive control strategies which make use of different forms of linearized models are compared. These linear models are ranging from a simple fixed model, linearized about a reference steady state to a weighted sum of different local models called multi model predictive control. A more complicated choice is represented by the extended dynamic matrix control in which the control input is determined based on the local linear model approximation of the system that is updated during each sampling... 

Ultrasonic motors (USM) possess heavy nonlinear, and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. These properties have made the position/velocity control of USM a difficult and challenging task. In this paper, a generalized model predictive (GPC) controller for precise USM position control is suggested. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection. Since the motor and the controller both are of type one, the applied saturation would cause in wind up phenomenon. This drawback is removed by implementing the Quadratic GPC controller. © 2004 IEEE  

In this paper an extended approach to the nonlinear DMC algorithm is proposed, which can handle constrained and MIMO systems under some defined conditions. This extension also admits higher control, M, and prediction, P, horizons that are required to increase the performance of the controller in most practical applications. Simulation results of the proposed method in the control of a stirred tank reactor with 2 inputs and 2 outputs nonlinear model are presented to illustrate effectiveness of the method and its justification. © 2003 IEEE  

The objective of this paper is to expand the concept of hybrid modeling and control in power electronics area. A new precise and non-averaged model of a DC-DC boost converter is developed on the basis of Mixed Logical Dynamical (MLD) systems, and the approach is extended by a new version of such systems which is called as Extended Mixed Logical Dynamical (EMLD) systems in this paper. A Model Predictive Controller (MPC) based on the Mixed Integer Quadratic Programming (MIQP) is designed for the MLD and EMLD models of the DC-DC boost converter considering all possible dynamics in Continuous and Discontinuous Conduction Modes of operations (CCM-DCM). The simulation results show the satisfactory... 

Objective: The objective of this paper is to develop a hierarchical two-level power system load frequency control. Design: At the button level, standard PI controllers are utilized to control area's frequency and tie-line power interchanges. At the higher layer, model predictive control (MPC) is employed as a supervisory controller to determine the optimal set-point for the PI controllers in the lower layer. The proposed supervisory predictive controller computes the optimal set-points such that to coordinate decentralized local controllers. Blocking and coincidence point technology is employed to alleviate the computational effort of the MPC. In order to achieve the best closed loop... 

In this paper, a wide area measurement, centralized, load frequency control using model predictive control (MPC) is presented for multi-area power systems. A multivariable constrained MPC was used to calculate optimal control actions including generation rate constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional MPC was employed. Time-based simulation studies were performed on a three-area power system, and the results were then compared with decentralized MPC and classical PI controller. The results show that the proposed MPC scheme offers significantly better performance against load... 

Servo drive systems require a fast dynamic response for position control applications. Conventional cascade control structure has sluggish response due to bandwidth limitations on speed and current control loop. To achieve a fast output response, model reference adaptive control methods can be used to remove the dynamics of inner control loops. In this paper, feed-forward signals are generated using model predictive control which is combined with the conventional cascade structure. Using this approach, a fast transient response and satisfactory tracking ability can be achieved. The proposed control configuration is verified by the simulation results  

Integrated guidance and control of an elastic flight vehicle based on constrained robust model predictive control is proposed. The design is based on a partial state feedback control law that minimizes a cost function within the framework of linear matrix inequalities. It is shown that the solution of the defined optimization problem stabilizes the nonlinear plant. Nonlinear kinematics and dynamics are taken into account, and internal stability of the closed-loop nonlinear system is guaranteed. The performance and effectiveness of the proposed integrated guidance and control against non-maneuvering and weaving targets are evaluated using computer simulations  

This paper proposes a hierarchical outage management scheme to enhance the resilience of a smart distribution system comprised of multi-microgrids against unexpected disaster events. In this regard, after identifying the main features and requirements for a resilient outage management scheme, an appropriate framework is devised and the roles and tasks of different management entities in a multi-microgrids system are introduced. Based on this framework, the microgrids schedule their available resources in the first stage using a novel model predictive control-based algorithm. In the second stage, distribution system operator coordinates the possible power transfers among the microgrids and... 

This paper investigates the operation of a smart distribution system comprised of multiple microgrids during emergency conditions. It proposes a two-stage hierarchical scheme for outage management in such a system to enhance the security of supply during contingencies. This goal is achieved through sharing the available generation and storage capacities among different microgrids. In doing so, a well-organized framework is devised in order to introduce the roles and tasks of each player in operation stage of a multi-microgrids system. Based on this framework, the general optimization model that needs to be evaluated at each stage of the proposed outage management scheme is formulated. In... 

This paper presents a robust model predictive control algorithm with a time-varying terminal constraint set for systems with model uncertainty and input constraints. In this algorithm, the nonlinear system is approximated by a linear model where the approximation error is considered as an unstructured uncertainty that can be represented by a Lipschitz nonlinear function. A continuum of terminal constraint sets is constructed off-line, and robust stability is achieved on-line by using a variable control horizon. This approach significantly reduces the computational complexity. The proposed robust model predictive controller with a terminal constraint set is used in tracking set-points for... 

An approximated quadratic programming optimization is proposed to determine a model predictive controller to guarantee end-to-end delay in the DiffServ architecture. The proposed algorithm, called the suboptimal model predictive control scheduler (SMPCS), regulates the service rates of aggregated traffic classes dynamically, such that some constraints on proportional or absolute delay can be guaranteed. This paper investigates SMPCS complexity and its implementation problems in high-speed routers. The main problem of model predictive control (and one which has limited its use to slow processes) is its complexity. Optimization is the most computationally complex part in a model predictive... 

Modular multilevel converter (MMC) is among the promising topologies used in high-voltage/power purposes, especially for high-voltage direct-current (HVDC) transmission systems. In this paper, a modified model predictive control (MPC) strategy for an MMC-HVDC system is presented. In the proposed MPC strategy, output current, circulating current and capacitors voltage are controlled separately. In order to reduce the computational burden of the controller, the output current is controlled directly without any optimization. For suppression of the circulating current, capacitors voltage variations are employed to settle the converter arms voltages to their reference values. In addition, the... 

Design, implementation and experimental evaluation of a classic PID, and a modern Generalized Predictive Control (GPC) for an off-pump heart tracking system were carried out. Following the design and simulation analysis of the controllers, experimental evaluation was conducted on the slave robot of SINA tele-operational surgical system. Results revealed that considering the volatile high-frequency/speed pattern of heart motion, the agility of the controlled system is the most influential factor on its performance. With this in mind, unlike the Ziegler-Nichols-based tuned PID with emphasis on steady-state condition, the PID control with more transient behavior showed a superior performance.... 

This paper develops a general framework for reliability assessment of multi-microgrid (MMG) distribution systems. It also investigates reliability impacts of coordinated outage management strategies in a MMG distribution network. According to the proposed reliability evaluation framework, which is based on sequential Monte Carlo simulation method, distribution system is divided into smaller sections/microgrids based on protection system configuration and operating measures are efficiently simulated considering different operation modes. In order to demonstrate the role of outage management strategy in reliability performance of MMG distribution systems, at first, the required features of an...