110 research outputs found

    Design New Online Tuning Intelligent Chattering Free Fuzzy Compensator

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    Adaptive Fuzzy Sliding Mode Control for a Class of Nonlinear System

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    For a class of nonlinear system with parameter perturbation and external disturbance, adaptive fuzzy control can be used to approach the system unknown functions to reduce the control input and the steady-state error. And an adaptive switch control gain whose adaptive law is decreasing function is designed to weaken the system chattering, the switch gain of estimate will increase on the basis of the original without decreasing with the elimination of interference. If system is interferenced many times. Against the shortcomings, this paper proposes an improved adaptive law that can weaken the system chattering effectively while maintaining the strong robustness. The simulation results by tests show that this method is correct and effective

    Design of Sliding Mode PID Controller with Improved reaching laws for Nonlinear Systems

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    In this thesis, advanced design technique in sliding mode control (SMC) is presented with focus on PID (Proportional-Integral-Derivative) type Sliding surfaces based Sliding mode control with improved power rate exponential reaching law for Non-linear systems using Modified Particle Swarm Optimization (MPSO). To handle large non-linearities directly, sliding mode controller based on PID-type sliding surface has been designed in this work, where Integral term ensures fast finite convergence time. The controller parameter for various modified structures can be estimated using Modified PSO, which is used as an offline optimization technique. Various reaching law were implemented leading to the proposed improved exponential power rate reaching law, which also improves the finite convergence time. To implement the proposed algorithm, nonlinear mathematical model has to be decrypted without linearizing, and used for the simulation purposes. Their performance is studied using simulations to prove the proposed behavior. The problem of chattering has been overcome by using boundary method and also second order sliding mode method. PI-type sliding surface based second order sliding mode controller with PD surface based SMC compensation is also proposed and implemented. The proposed algorithms have been analyzed using Lyapunov stability criteria. The robustness of the method is provided using simulation results including disturbance and 10% variation in system parameters. Finally process control based hardware is implemented (conical tank system)

    Design Intelligent Model base Online Tuning Methodology for Nonlinear System

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    Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

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    Multi-Inputs-Multi-Outputs (MIMO) systems are recognized mainly in industrial applications with both input and state couplings, and uncertainties. The essential principle to deal with such difficulties is to eliminate the input couplings, then estimate the remaining issues in real-time, followed by an elimination process from the input channels. These difficulties are resolved in this research paper, where a decentralized control scheme is suggested using an Improved Active Disturbance Rejection Control (IADRC) configuration. A theoretical analysis using a state-space eigenvalue test followed by numerical simulations on a general uncertain nonlinear highly coupled MIMO system validated the effectiveness of the proposed control scheme in controlling such MIMO systems. Time-domain comparisons with the Conventional Active Disturbance Rejection Control (CADRC)-based decentralizing control scheme are also included

    Disturbance observer based adaptive sliding mode control for continuous stirred tank reactor

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    The continuous stirred tank reactor (CSTR) typifies an important class of process control systems. Is is a nonlinear system and is sensitive to both external disturbances and system uncertainty. Given these challenges, a nonsingular terminal sliding mode observer is proposed to estimate any external disturbance. Then, a continuous adaptive sliding mode control method is combined with the proposed disturbance observer. This is found to reduce chattering and improve control accuracy when compared with other methods. A full Lyapunov stability proof of the resulting closed-loop system is performed and the effectiveness of the proposed approach is demonstrated by simulation experiments

    Sliding mode robot controller parameter tuning with genetic algorithms and fuzzy logic

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    Sliding Mode Controllers (SMC) possess robustness properties under parameter uncertainties. Usually, a Lyapunov based controller design with a switching control signal constitutes the backbone of robustness. However, the ideally zero switching time of the controller output cannot be achieved in digital implementation. This causes a phenomenon called chattering – high frequency oscillations observed in systems state variables. Chattering also shows itself as high amplitude oscillatory behavior in the control signal. A chattering actuator output is not favorable for many plants, including robot manipulators driven by actuator torques. This problem is traditionally solved by smoothing the switching control output, deviating from the original mathematical foundations robustness. Over-smoothing causes performance deterioration, while too limited smoothing action may lead to the wear of the mechanical system components. This motivates the exploration of automatic tuning approaches which consider chattering and performance simultaneously. This thesis proposes two SMC smoothing and parameter tuning methods with soft computing (SC) methodologies. The first method is based on Genetic Algorithms (GA). SMC controller parameters, including the ones governing the smoothing action are tuned off-line by evolutionary computing. A measure is employed to assess the instantaneous level of chattering. The integral of this value combined with performance indicators including the rise time and steady state error in a step reference scenario are used as the fitness function. The method is tested on the model of a direct drive (DD) SCARA type robot, via simulations. The GA-tuned SMC is, however, tailored for a fixed reference signal and fixed payload. Different references and payload values may pronounce the chattering effects or lead to performance loss due to over-smoothing. The second SMC parameter tuning method proposed employs a fuzzy logic system to enlarge the applicability range of the controller. The chattering measure and the sliding variable are used as the inputs of this system, which tunes the controller output smoothing mechanism on-line, as opposed to the off-line GA technique. Again, simulations with the direct-drive robot model are employed to test the control and tuning method
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