Nasim Ullah

High performance direct torque control of electrical aerodynamics load simulator using adaptive fuzzy backstepping control

Electrical load simulator is hardware in the loop simulator used to exert real-time aerodynamics loads on the servo actuation system of a flight vehicle under test according to flight conditions. This article investigates direct torque control of electrical load simulator system using adaptive fuzzy backstepping method. To analyze the effect of extra torque disturbance on electrical load simulator system, detailed mathematical formulations are derived. Considering practical aspects of the proposed method, state vector is estimated using a state predictor, and parameters of the system are estimated using algebraic method. Fuzzy logic system is used to estimate extra torque disturbance acting on electrical load simulator system, but the approximation error may not converge to zero, which may affect control performance. Similarly, the parameters of the system may vary with time; thus the lumped disturbance due to time variation of parameters and fuzzy approximation error is compensated using adaptive control law derived based on estimated error dynamics between actual plant and state predictor. Moreover, to improve transient response, a novel saturation function-based transient performance controller is introduced. The performance of the proposed control is verified using extensive numerical simulations.

Quantized adaptive decentralized control for interconnected nonlinear systems with actuator faults

This paper studies quantized adaptive decentralized output feedback control technique for a class of interconnected nonlinear systems with quantized input and possible number of actuator failures up to infinity. A modified backstepping approach is proposed by the use of high-gain k-filters, hyperbolic tangent function property and bound-estimation approach to compensate for the effect of possible number of actuator failures up to infinity and input quantization. It is proved both mathematically and by simulation that, all the signals of the closed-loop system are globally bounded despite of input quantization and possible number of actuator failures up to infinity.

Fractional order fuzzy terminal sliding mode control of aerodynamics load simulator

Fractional order adaptive fuzzy continuous non-singular terminal sliding mode control is proposed for electrical aerodynamics load simulator system which is subjected to extra torque disturbance and parametric uncertainties. A fractional order sliding surface is constructed and a continuous non-singular terminal sliding mode control law is derived to ensure faster convergence and precise control without singularity problem. Fractional order adaptive fuzzy logic system is used to estimate the unknown extra torque disturbance. Moreover, nonlinear friction is compensated using LuGre model. Practically, electrical aerodynamics load simulator system is affected by additional un-modeled dynamics due to uncertainty in system parameters and friction model combined with fuzzy approximation error. The un-modeled dynamics are compensated using fractional order adaptive law which is derived using Lyapunov function. The validity and effectiveness of proposed control scheme are verified using numerical simulations.

Adaptive nonlinear feedback control of chaos in permanent-magnet synchronous motor system with parametric uncertainty:

The permanent-magnet synchronous motor (PMSM) system, which is a nonlinear dynamic system, will exhibit a variety of chaotic or limit-cycle phenomenon under some choices in system parameters and external disturbances and its chaotic characteristics will become obvious. Based on the mathematical model of the PMSM system, the property of equilibrium points is analyzed and the relationship between Hopf bifurcation and the system parameters associated with control parameters is illustrated. In addition, bifurcation diagram, Lyapunov exponent map, and phase plane diagram are also presented in this paper. An adaptive nonlinear feedback controller, which could estimate the system parameters online, is then designed to eliminate the chaos and drive the speed of PMSM to a desired value in presence of system parametric uncertainty. Numerical simulation proves that the proposed control method has a better controlling effect than the general nonlinear feedback controller.

Design & thermal modeling of solar panel module with embedded reconfigurable Air-Coil for micro-satellites

Spacecrafts need to maneuver their solar panels towards the sun and antennas towards the ground station for maximum solar power harvesting and communication with the ground station. For tracking purpose, usually magnetorquer rods, reaction wheels and permanent magnets are used, but they are heavier, expensive, and occupy extra space on the spacecraft. Keeping in mind the dimension, budget and mass constraints of small satellites, a system compatible with small satellite is worth consideration. Consequently, this paper focuses on designing and analyzing a solar panel module with embedded Air-Coil. Such an Air-Coil is an innovative idea for the replacement of heavier, bulky and expensive attitude control systems. The proposed Air-Coil is integrated in the internal layers of an eight layers solar panel PCB module. Complete degradation analyses of the solar panel have been done to ensure that it will meet the satellite power requirements at BOL (beginning of life) and EOL (end of life). The proposed embedded Air-Coil has been analyzed for the generated magnetic moment, resultant torque, power consumption and temperature increase of the complete solar panel unit. A steady state thermal model is proposed to measure the thermal resistance between top and bottom layers of the solar panel module, which gives an idea about the heat trapped inside the solar panel module. The designed embedded Air-Coil is fully reconfigurable where coil in each layer can be operated as a separate coil. The four coils in different layers can be attached or detached through switches in different configurations i.e. single coil, four in series, four in parallel, and their hybrid combinations. The analyses of power consumption, heat dissipation, temperature rise, magnetic moment and torque generation by different configurations of the designed Air-Coil have been performed. The generated magnetic moment is very high i.e. around 12Am2, which is enough to rotate a microsatellite by 90° in 200s. The efficacy of the proposed module is significantly higher than the already available systems with respect to mass, price, power dissipation, heat generation, and dimension.

Adaptive output-feedback control for a class of nonlinear systems with actuator failures and input quantisation

ABSTRACT In this paper, an adaptive output feedback control technique is proposed for a class of nonlinear systems with unknown parameters, unknown nonlinear functions, quantised input and possible actuator failures up to infinity. A modified backstepping approach is proposed by the use of high-gain K-filters, hyperbolic tangent function property and bound-estimation approach to compensate for the effect of possible number of actuator failures up to infinity, input quantisation and unknown nonlinear functions. It is proved both mathematically and by simulation that with the proposed controller, all the signals of the closed-loop system are globally bounded despite of input quantisation, unknown nonlinear functions and possible number of actuator failures up to infinity.

PERFORMANCE ENHANCEMENT OF FACE RECOGNITION SYSTEM USING PRINCIPAL COMPONENT ANALYSIS MERGED WITH DISCRETE WAVELET TRANSFORMS

Performance of face recognition system can be enhanced by proposed technique titled as PCA merged with Discrete Wavelet Transform (DWT) instead of using the conventional PCA technique. In this technique to reduce the computational complexity of traditional PCA the size of the image is first reduced by taking the DWT of it. After applying the DWT the facial features of the image are extracted by calculating the Eigenface of the image with size already reduced by taking DWT. As a result of this process the size of database will reduce to one-fourth of the conventional PCA in which the facial features are extracted directly from the image by calculating the Eigenface. The size of the train database is reduced with the proposed technique which reduces the processing time of the face recognition without losing the accuracy. Performance of face recognition system is enhanced in terms of low processing time as shown by comparing the experimental results of conventional PCA and the proposed technique in this paper

Adaptive Variable Universe of Discourse Fuzzy Sliding Mode Control

This paper proposes adaptive variable universe of discourse fuzzy sliding mode control for efficient compensation of unbounded disturbances and reduced chattering. Classical sliding mode control is robust to bounded uncertainties and disturbances. The disadvantages of classical sliding mode control are high frequency chattering and poor performance in case of unbounded disturbances. Chattering phenomena is minimized using adaptive fuzzy sliding mode control but fuzzy fixed universe of discourse makes it in-efficient for time varying unbounded disturbances and uncertainties. This article investigates a variable universe of discourse fuzzy logic system for unbounded disturbances. Fuzzy universe of discourse for membership functions of input and output parameters is tuned online using an adaptive empirical law derived from the error dynamics. Performance of proposed control is verified using extensive simulations.

Higher order error dynamics based backstepping controller design for electrical load simulator

This paper proposes higher order error dynamics based back stepping controller design to compensate extra torque disturbance of electrical load simulator (ELS). Lugre friction model based observer is used to compensate nonlinear friction. ELS system and friction modeling error as well as uncertain parameters may lead to tracking errors. Using adaptive back stepping control techniques, transient response is guaranteed at the cost of chattering in control signal which may affect the control performance as well as adaptive loops used to estimate the uncertain parameters. A higher order error dynamics based back stepping torque controller is derived from the parametric equation of ELS and its stability is proved using Lyapunov method. The validity of proposed controller is verified using computer simulations.

Torque controller design for electrical load simulator with estimation and compensation of parametric uncertainty

This paper proposes adaptive robust controller for electrical load simulator with estimation of parameters uncertainties and updating the model parameters to minimize model error Fuzzy logic is used to estimate the total disturbance which is function of extra torque and mechanical parameters variation. Estimation algorithm for parameters variation is derived from voltage and torque balance equations of electrical load simulator with suitable adaptive learning rate. A robust torque controller is derived from torque state equation of electrical load simulator and its stability is guaranteed using Lyapunov stability analysis. The validity of proposed controller is verified using computer simulations.