Sharif Digital Repository

This paper proposes a tracking control strategy for nonlinear systems without needing a prior knowledge of the reference trajectory. The proposed method consists of a set of local controllers with appropriate overlaps in their stability regions and an on-line switching strategy which implements these controllers and uses some augmented intermediate controllers to ensure steering the system states to the desired set points without needing to redesign the controller for each value of set point changes. The proposed approach provides smooth transient responses despite switching among the local controllers. It should be mentioned that the stability regions of the proposed controllers could be... 

A stable robust adaptive impedance control strategy is introduced here as a model-based low-level control scheme for active ankle prostheses. The effects of amputee-prosthesis and prosthesis-environment interactions are included in the controller design. An interesting feature of the proposed controller is that only shank and ankle angles and angular velocities, and ground reaction forces are required to implement the control law. In other words, no feedback from amputee-prosthesis interaction forces and moment, global or local positions, and accelerations of amputated place is required. Using a Lyapunov analysis, exponential convergence characteristics of the proposed controller are proven.... 

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear... 

This article deals with the problem of robust low-order controller design for systems with multimodel representations. Such models are frequently used for the description of nonlinear and complex industrial power systems over an operating profile. We first develop a generalized complex extension of convex direction based on the interpolation and edge theorems. Subsequently, for plant models with parametric-type uncertainty, new vertex results related to robustness margins and system performance are derived. Based on this, new tools to design robust low-order controllers for such systems are presented. © 1982-2012 IEEE  

The eigenvalue perturbation theorem is used to propose a convex fragility criterion with application to control system design. The criterion can be considered as a non-normality measure of the controller state-space matrix. Non-normality of a matrix is defined as its distance to the nearest real normal matrix within a convex normal subspace. Based on the criterion, an H∞ method for the order reduction of linear time-invariant (LTI) controllers is developed which leads to non-fragile reduced order controllers. 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission  

Manipulation of a quantum system requires the knowledge of how it evolves. To impose that the dynamics of a system becomes a particular target operation (for any preparation of the system), it may be more useful to have an equation of motion for the dynamics itself, rather than the state. Here we develop a Markovian master equation for the process matrix of an open system interacting with a reservoir, which resembles the Lindblad Markovian master equation. We employ this equation to introduce a scheme for optimal local coherent process control at target times and extend the Krotov technique to obtain optimal control. We illustrate utility of this framework through several quantum... 

This article addresses an adaptive backstepping control design for uncertain fractional-order nonlinear systems in the strict-feedback form subject to unknown input quantization, unknown state-dependent control directions, and unknown actuator failure. The system order can be commensurate or noncommensurate. The total number of failures is allowed to be infinite. The Nussbaum function is used to deal with the problem of unknown control directions. Compared with the existing results, the control gains can be functions of states and the knowledge of quantization parameters and characteristics of the actuator failure are unknown. By applying the backstepping control approach based on the... 

In this paper, an adaptive multi-model controller based on CMAC neural networks (AMNNC) is developed for uncertain nonlinear MIMO systems. AMNNC is a kind of adaptive feedback linearizing controller where nonlinearity terms are approximated with multiple neural networks. The weighted sum of the multiple neural networks is used to approximate the system nonlinearity for a given task. The proposed control scheme is applied to control a robotic manipulator, where some varying tasks are repeated but information on the load is not defined; it is unknown and varying. It is shown how the proposed controller is effective because of its capability to memorize the control skill for each task using... 

In this paper a decentralized control scheme for multiple cooperative manipulators is developed to achieve the desired performance in motion and force tracking, in the presence of uncertainties in dynamic equations of the robots. To eliminate the effects of uncertainties in the closed-loop performance, a new adaptive control algorithm is proposed. Based on the Lyapunov stability method, it is proved that all the error signals in the closed-loop system which is compose of a robot, an observer and a controller asymptotically converge to zero. Also to avoid the difficulties of using velocity sensors within the cooperative system, an output feedback control scheme with a linear observer is used.... 

Application of a flux search controller in direct torque control of induction motor drives produces divergence problem and steady state flux ripple, because of the disturbance in the control loop. In this paper, an investigation about the origin of this noise has been performed. It is shown that the variation of voltage harmonics is the main reason of disturbance in the flux control loop. The minimum allowable value of flux step has been determined based on this analysis to prevent the divergence problem. Feasibility of noise cancellation has been discussed. Experimental results are presented to justify the theoretical analysis. © 2005 IEEE  

We introduce a novel probabilistic framework to achieve robust non-fragile tuning methods in control of processes with parametric uncertainties. We consider probability distributions to model the process parameters' uncertainties. First, we propose the tuning framework in a general setting. Then, as an illustration, we apply it to PD control of IPD-modeled processes. It is noteworthy that the proposed tuning method is robust against the considered parametric uncertainties. Also, to empower the proposed robust tuning method in the viewpoint of non-fragility, we utilize a centroid approach. Selecting the form of the probabilistic framework, we empirically observe some of the popular tuning... 

This paper presents a robust decentralized proportional-integral (PI) control design as a solution of the load frequency control (LFC) in a multi-area power system. In the proposed methodology, the system robustness margin and transient performance are optimized simultaneously to achieve the optimum PI controller parameters. The Kharitonov's theorem is used to determine the robustness margin, i.e., the maximal uncertainty bounds under which the stable performance of the power system is guaranteed. The integral time square error (ITSE) is applied to quantify the transient performance of the LFC system. In order to tune the PI gains, the control objective function is optimized using the... 

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... 

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  

In this paper, an indirect adaptive fuzzy sliding mode controller for a 3-dimensional inverted pendulum as a fully actuated MIMO system is developed. This inverted pendulum, has four degrees of freedom and equations of the system are nonlinear and non-minimum phase. Thus, control of this system is a challenging issue. Accordingly, in this work, general basis of sliding mode control method with reaching rules is expressed for this system, then the fuzzy control theory is combined, and modeling uncertainties of the system are estimated by universal fuzzy approximation theory. Controller parameters are updated by a defined adaptation law to decrease the tracking error of the inverted pendulum.... 

In this paper, a restricted structure of PID controller is proposed for automobile gas turbine by considering a LQG cost function. So PID Controller coefficients are calculated by minimizing this cost function. One of the most important characteristics of this approach, its ability to design various structure PID controllers by solving optimization problem only for one time, moreover it can approximate main optimization problem by a repetitive Quadratic optimization Problem (QP). This approach is convex optimization and has an analytic solution; therefore its calculations are not complicated. In defined cost function, there are two weighting functions, control error and control action; they... 

In this paper, an adaptive control scheme, based on fuzzy logic systems, for pH control is addressed. For implementation of the proposed scheme no composition measurement is required. Stability of the closed-loop system is established and it is shown that the solution of the closed-loop system is uniformly ultimately bounded and under a certain condition, asymptotical stability is achieved. Effectiveness of the proposed controller is tested through simulation and experimental studies. Results indicate that the proposed controller has good performances in set-point tracking and load rejection and much better than that of a tuned PI controller. © 2009 Elsevier Ltd. All rights reserved  

Design and control of micro robots have been one of the interesting fields in robotics in recent years. One class of these micro robots is the legged robots. Various designs of legged robots have been proposed in the literature. All designs rely on friction for locomotion. In this paper dynamic model of a planar two-legged micro robot is presented using Luger friction model, and an adaptive neural controller used to control the robot to improve robustness and velocity of the robot. As mentioned earlier, friction plays an important role in locomotion of the legged robots. However, especially in legged micro robots, it is difficult to model the frictional force correctly since environmental... 

In this study, a hierarchical optimal robust controller is presented for the power system load-frequency control problem. In this approach, the multi-area power system is first decomposed into several sub-systems (areas). Then by using a two-level control strategy, the overall optimal solution is obtained. At the first level, the optimal control of each area is obtained with respect to local information and also considering interactions coming from other areas. At the second level, by using a coordination strategy, the local controllers will converge to global solution and optimal robust controller is achieved. This approach is applicable to both single-area and multi-area interconnected... 

In recent years, design and tuning of fractional-order controllers for use in motion control have attracted much attention. This paper deals with one of the interesting methods that have been recently proposed for tuning fractional-order proportional and derivative (FOPD) motion controllers. The FOPD controller tuned based on the considered method results in simultaneously meeting the desired phase margin, the desired gain crossover frequency, and the flatness of the phase Bode plot at such a frequency. Since, in this tuning method, the derivative parameter and order are determined in a graphical way, in the first view, it is not clear for which pairs of phase margin and gain crossover...