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این مقاله به مدل‎سازی و کنترل خطی و غیرخطی پرواز مسیکوپتر می‌پردازد. ابتدا مدل غیرخطی چندورودی-چندخروجی پرنده با در نظر گرفتن دینامیک عملگرها و اثرات ژایروسکوپیک پره و بدنه استخراج شده و سپس از سه روش کنترلی خطی برای رسیدن به پاسخ‌های سریع با مشخصات عملکردی مناسب استفاده می‌شود و از نظر تلاش کنترلی تولیدی برای این وسیله پرنده مقایسه می‌شوند. کنترل بهینه با توجه به ملاحظات مصرف انرژی نسبت به سایر روش های کنترلی مناسب تر می باشد. مسیکوپترها همواره تحت تاثیر عدم قطعیت‌ها قرار می‌گیرند و روش‌های کنترلی کلاسیک برای مقابله با این نامعینی‌ها و پایدارسازی دینامیک ذاتاً ناپایدار پرنده ضعیف می‌باشند. برای جبران عدم قطعیت‌های پارامتری موجود در دینامیک مسیکوپتر از سه روش کنترلی غیرخطی تطبیقی مدل مرجع برای سه حالت متفاوت مبتنی بر معادلات خطی تک‌ورودی-تک‌خروجی و معادلات خطی چندورودی-چندخروجی و معادلات غیرخطی چندورودی‌-چندخروجی استفاده می‌شود. روش‌های کنترلی تطبیقی با داشتن مکانیزم‌های تخمین سبب ارتقاء عملکرد سیستم در طول پرواز در شرایط مختلف و پایدارسازی وضعیت و کنترل حالت‌های سیستم می‌شوند. پایداری توسط معیار پایدرای لیاپانوف به اثبات رسیده است. نتایج شبیه‌سازی مبین موفقیت‌آمیز بودن روش کنترلی تطبیقی برای جبران عدم قطعیت‌های پارامتری و همگرایی مجانبی خطای تعقیب می‌باشد.

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In this paper, an Extended Kalman Filter (EKF) and a model-dependent nonlinear controller over network using the separation principle for Low Earth Orbit (LEO) satellite Attitude Determination and Control Subsystem (ADCS) have been designed. In this context, according to the satellites development trend, ADCS architecture for a broad class of LEO satellites is proposed to stabilize and achieve mission objectives such as precision attitude determination and pointing. This architecture is a Networked Control System (NCS) used to establish connection and communication among control components including sensors, actuators and onboard processors, as well as to share data with other subsystems. Then, by modeling all components of the system, and considering the network effects as a bounded disturbance, the control system is designed to compensate of these effects. For this purpose, estimation and control algorithms including EKF and a model-dependent nonlinear controller is designed such that in addition to achieve desired system performance, the stability of each of them is guaranteed. Afterwards, the nonlinear dynamics model of the satellite in terms of quaternion parameters and angular velocities is presented, and by expression of the separation principle for nonlinear observer and controller design, their convergence and exponential stability conditions based on linearized model of satellite are derived. Proof of theorem shows that the closed-loop system continuously maintained satellite attitude in the specified accuracy range. Finally, simulation results obtained from applying the designed observer and controller on the active satellite in orbit demonstrates the efficiency of the proposed design.

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Anti-lock braking system (ABS) prevents the wheels from being locked in hard braking conditions and reduces the vehicle stopping distance to the minimum value by regulating the tire longitudinal slip at its optimum value. This paper presents a two-layer controller for ABS of trucks which is adaptable with different road conditions. In the upper layer, a fuzzy controller is designed to calculate the optimum longitudinal slip of each wheel for which the maximum braking force is achieved in different conditions. In the lower layer, a nonlinear controller is analytically designed based on the predictive method to track the optimum wheel slips calculated from the upper layer. In order to increase the robustness of the controller in the presence of system uncertainties, the integral feedback technique is also appended to the predictive method. All simulation studies are conducted using the professional software of Truck Sim to evaluate the performance of the controlled system in a real condition. The results show the effectiveness of the proposed control system in improving the braking performance of trucks in different road conditions.

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In this paper, the adaptive second order sliding mode (SOSM) controller is designed for two input - two output (TITO) uncertain nonlinear systems and the robustness properties are ensured in the presence of uncertainties and bounded external disturbances. The objective is to design a controller that ensure stability and path tracking despite the effects of coupling. To this end, the system model is divided into two subsystems, and the coupling effects between such subsystems are considered as uncertainties. The sliding mode approach with PI sliding surface is used to remove the offset and converge the steady state error to zero. To avoid chattering phenomenon, Second order sliding mode method is proposed. Using adaptive switching gain, a new method is presented which unlike other methods, does not require the upper bound of the system uncertainties in the design procedure. Robustness properties against system uncertainties and external disturbances is shown by the Lyapunov stability theorem. Finally, the proposed method is used to control azimuth and elevation angle of as a laboratory helicopter with two degrees of freedom. Simulation results show performance of the algorithm in the presence of perturbations.

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In this paper, tracking control synthesis problem for nonlinear polynomial discrete-time systems are studied. Proposed controller drives the plant such that the state vector of the plant follows those of a stable reference model. The objective is to design a controller such that the energy gains from the exogenous signals that are the reference signal and the state vector of the reference model, to the tracking error to be less or equal to prescribe thresholds. The main difficulty in the problem of designing tracking nonlinear discrete-time control law for the polynomial discrete time systems is that in general this problem may not be formulated as a convex problem. With proper selection of Lyapunov function and based on Lyapunov theory and by using sum of square approach, sufficient conditions for existence of controller are presented in terms of a feasibility SOS programming problem that can be solved using numerical solvers such as SOSTOOLS. Finally, the performance of proposed approach will be shown using the simulation of several examples.

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This paper presents the control of a quadrotor using nonlinear approaches based on the experimentally measured sensors data. The main goal is the control and closed loop simulation of a quadrotor using feedback linearization and sliding mode algorithms. First, a nonlinear model of quadrotor is derived using Newton-Euler equations. To have a more realistic simulation the sensors noise performance were measured using a setup. sensors data was measured under on engines. Since the experimental data for sensor had error and noise, a Kalman filter was used to reduce sensors noise effect. Results demonstrate good performance for Kalman filter and controllers. Results showed that feedback linearization and sliding mode controllers performance was good but angles changes were smoother on feedback linearization controller. With increasing uncertainty, feedback linearization performance was away desired mode from this aspect The time to reach the goal situation while increasing uncertainty was no significant impact on the performance of sliding mode controller.Thus feedback linearization controller added PID is Appropriate to Maintain the quadrotor attitude while sliding mode controller has better performance to angles change and transient situations.

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In this paper, an optimization-based nonlinear control strategy is applied to air path control of a turbocharged diesel engine. For this aim, the air-fuel ratio (AFR) and the pressure of exhaust manifold are controlled by calculating the air mass flow rates of turbocharger and exhaust gas recirculation. Controlling AFR which affects engine power, fuel consumption and exhaust emissions, is carried out by calculating the air mass flow rate with the assumption of known fuel path. For air path modelling, the mean value model which is a suitable method with low computational time is used to achieve the air path equations. Air mass flow is calculated by the developed control laws and applied by the turbocharger and exhaust gas recirculation. In the proposed control method, the nonlinear system response is firstly predicted by Taylor series expansion and then the optimal control law is developed by minimizing the difference between the desired response and the actual response. To compare the performance of the proposed optimal controller, a sliding mode controller has been also designed. The simulation results show that the rate of air mass and the pressure of exhaust manifold are close to their desired values and consequently the AFR is well controlled. Therefore, the designed controller with optimal inputs can successfully cope with the nonlinearities existing in engine dynamics model.

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In this study, control design of a T shaped mass connected to the clamped-clamped microbeam excited by electrostatic actuation is investigated. The actuation force is generated by applying an electric voltage between the horizontal part of T shaped mass and an opposite electrode plate. In this model, the micro-beam is modeled by Euler-Bernoulli theory as a continuous beam. The T-shaped assembly connected to the the microbeam is assumed as a rigid body and nonlinear effect of electrostatic force is considered. Equations of motion and associated boundary condition are derived using the Lagrange’s principle. The differential equation of nonlinear vibration around the static position is discretized using Galerkin method.. The discretized equations are solved by the perturbation theory. To improve the dynamics behavior of systems, nonlinear control feedback has been presented. The controller regulates the pass band of microcantilever and analytically approximate the nonlinear resonance frequency and amplitudes of the periodic solutions when the microcantilever is subjected to one point and fully distributed feedback forces. The results of paper may be used for improving the design of mass sensors based on nonlinear jump phenomena.