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This study presents a novel control framework integrating feedforward (FF) and feedback (FB) strategies for the management of nonlinear systems. The intelligent control component employs a wavelet neural network (WNN) to construct the FF controller. Additionally, the FB loop incorporates H-infinity control, renowned for its robustness and resilience. The controller parameters are optimized using Particle Swarm Optimization (PSO). The proposed control framework's efficacy is evaluated through its application to knee joint motion, assessing both control accuracy and robustness against external disturbances. [ABSTRACT FROM AUTHOR]

The control of systems like: bipedal locomotion robots, space launch vehicle, offshore wind turbines, and active vibration control systems in buildings and bridges, have to ensure, besides stability and accuracy, the system's insensitivity to parameters' uncertainties, unmodeled dynamics, external disturbances, and measurements noise. In such systems analysis and controller design, a triple inverted pendulum can be used as a benchmark to mimic systems characteristics and effect of different sources of uncertainty. μ-synthesis is a robust control method which seeks a controller that minimizes the robust H-infinity performance of the closed-loop system through D-K iteration. The D-K iteration is not guaranteed to converge to a global, or even local minimum. Hence this paper proposes the enhancement of controller design by applying gazelle optimization technique to shape the fictitious output by determining the parameters of the performance weighting matrix. The incorporation of optimization with controller design allows avoiding getting unnecessarily conservative system at the expense of performance. The developed control system is simulated using Matlab R2023b for different scenarios of system uncertainty. The results show that the requirements of robustness and performance can be balanced through the right choice of cost function. The robust performance measure obtained is 0.6432 which leads to good response for both stabilization and tracking in the presence of uncertainty. The results also show that even the baseline μ-synthesis design achieves higher robust stability margin about 2.818, the proposed optimized method stabilizes the system with overshoot been reduced by 67.65% and steady state error reduced by 5.69% without sacrificing robustness. [ABSTRACT FROM AUTHOR]

In this study, a nonlinear robust state feedback based on H-infinity controller for nonlinear systems is constructed. On the basis of a proposed cost function, the black hole optimization (BHO) method is employed as a successful optimization approach to discover the optimum parameters with relation to the proposed controller. Solving the H-infinity algebraic Riccati equation yields the recommended controller gain matrix. To demonstrate the efficacy of the suggested controller, two categories of nonlinear systems are provided as case studies. Lastly, the simulation findings reveal that the proposed nonlinear controller is capable and enhances the performance and stability of the nonlinear systems. [ABSTRACT FROM AUTHOR]

Real world systems are inherently nonlinear in nature. Over the last few decades, nonlinear systems are regarded as the most significant issue in control theory. In this work, a nonlinear full state feedback H-infinity controller is proposed for nonlinear systems. The black hole optimization method (BHO) is used as an effective optimization technique to find the optimal parameters for the proposed controller based on the proposed cost function. The suggested controller gain matrix is computed by solving the H-infinity algebraic Riccati equation. As case studies, two types of nonlinear systems are demonstrated to demonstrate the utility of the proposed controller. Finally, simulation findings show that the suggested nonlinear controller improves the stability and performance of nonlinear systems by compensating them and compelling their states to track the reference input asymptotically with a workable and feasible control action. [ABSTRACT FROM AUTHOR]

In this paper, the design of two degree of freedom controller for ball and beam system is proposed. The Quantitative Feedback Theory (QFT) constraints are used to design two PID controllers to stabilize and compensate the nonlinear system with robust stability, robust performance and more desirable time response specifications. A multi objective cost function is proposed in this work to represent the function of QFT. The Black Hole Optimization (BHO) technique is a useful method to automate the design procedure of the proposed controller. The results of simulation indicate that the suggested optimal quantitative PID controller can give a desirable performance in comparison to other controllers designed in previous work. [ABSTRACT FROM AUTHOR]