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The research and development of hybrid electric vehicles has become a significant goal for large automotive manufacturers. The hybrid electric vehicle integrates a conventional engine and one or more electric motors powered by a battery, offering better fuel economy and lowering exhaust emissions. This paper develops an optimal energy management algorithm based on Model Predictive Control that can produce optimal control parameters for power distribution between the battery unit and generator. The energy management strategy adapts this optimal power distribution by adjusting the objective function equivalent parameter of the controller according to changes in driving conditions. Dynamic programming is utilized offline to find the reference state of charge of the battery and used as the reference trajectory of our proposed strategy. Simulation results using different driving cycles show that the proposed method has better power distribution compared with two other strategies. The final state of charge reached a higher level, and the energy-saving percentage rose compared to the conventional algorithm. [ABSTRACT FROM AUTHOR]

An Adaptive Nonlinear PID (ANLPID) controller for six Degrees of Freedom (6-DOF) Underwater Robotic Vehicle (URV) model is proposed to solve the path tracking problem. The path tracking problem is mainly caused by external environmental disturbances and the unknown uncertainties of the URV model. The ANLPID controller is used to estimate both the external disturbances and the unknown URV uncertainties. The performance of the ANLPID controller was evaluated by comparing the ANLPID controller with other existing works that are Nonlinear PID (NLPID) controller and Nonlinear Fractional PID (NLFOPID) controller. The system stability is proved by utilizing the Lyapunov function. At the end, the results obtained show the proficiency of the ANLPID controller, where the ANLPID controller improved the performance of the URV by 41.4185 % compared to the NLPID controller and by 54.6479 % compared to the NLFOPID controller. [ABSTRACT FROM AUTHOR]

The Swarm Intelligence Optimization Methods were widely used in science. Animals' swarming behaviour mainly inspires these methods. Conventional optimization for Harris Hawks (HHO) is a recent technique based on the hunting strategy of harris hawks. The parallelism technique was used in this study to try to improve the original version of the algorithm. The improved algorithm sets the parameters of two controllers designed to improve the 4-link flexible joint manipulator's dynamic performance. The integral sliding mode controller controls the flexible joints, and the adaptive output feedback tracking controller controls the rigid links. When the improved algorithm is tested on benchmark functions and compared to other optimization strategies. the results show that the improved algorithm is faster and more precise. The simulation results indicate the improved algorithm's capabilities, with an enhancement percentage of 76.72 percent for the first link and 70.91 percent for the first joint compared to the standard approach. [ABSTRACT FROM AUTHOR]

Power Electronics DC-DC converter plays an important role in different applications, for example, electric vehicles, wind generation and PV systems. This paper addresses the design of DC-DC X-converter with optimal LQR controller combined with integral gain action. Therefore, the proposed controlling scheme for DC-DC converter is very important to make the system stable under different conditions. In order to achieve high performance for DC-DC converter system, the current controller was made first as an inner loop and then an output voltage controller was designed as an outer loop. The behavior of an LQR controller design with integral action is characterized by two parameters: state and control weighting matrices. The problem of finding the semi-optimum weighting matrices has been formulated as an optimization problem. Standard Shuffled Frog-Leaping (SSFL) optimization algorithm is introduced to optimize the selection of the controller's weighting matrices. Furthermore, an Enhanced SFL Optimization Algorithm (ESFLA) is proposed to improve the stability performance of the considered system. The performances of both SSFLA and ESFLA are evaluated in terms of speed of convergence to the global optimum and algorithm accuracy, based on a set of ten benchmark test functions. The simulation results demonstrate that the DC-DC X-converter based on LQR with integral gain tuned by ESFLA outperforms other designs incorporating SSFLA in terms of control effort, stability performance as well as transient response specifications. [ABSTRACT FROM AUTHOR]