Research On Generalized Predictive Control And Energy Consumption Of Autonomous Underwater Vehicle

As consciousness to the exploitation and the utilization of the ocean is being strengthened, underwater vehicles in complex environment are being more widely preoccupied the attentions of people. But intelligent control technology is key and important basis to the underwater vehicle to complete tasks independently. In addition, energy which is carried on the autonomous underwater vehicle (AUV) for submergence is limited, so research of how to utilize the energy effectively comes to be one of the most important issues. Therefore, intelligent control and consumption issues have both the important theoretical and practical values in promoting the intelligent levels of underwater vehicle.Based on the analysis of the generalized predictive control algorithm, the nonlinear dynamic system model and its transformation conditions for linear time-variability, the indirect adaptive generalized predictive control algorithms having function of the parameters identification, and the direct adaptive generalized predictive control algorithms are integrated and applied to the motion control of underwater vehicle. Then, simulation of the control process is proposed.The multi-objective optimization and the control of AUV concerning the energy consumption are discussed in this paper. In order to reduce the output fluctuation and overshoot of the system, the variations of outputs are integrated into the traditional target functions as an aim of system optimization. And then, the generalized predictive control algorithm of reducing fluctuation is proposed. Similarly, the generalized predictive control algorithm of inhibiting the control quantity and its increment is presented so as to inhibit the oversized output fluctuation. The fierce change of control increment is limited by adjusting the control weighted coefficients, and the effect that the control weighted coefficients imposed on the control change is analyzed and for which the simulation is carried out. It's an attempt to apply the multivariable generalized predictive control to motions of underwater vehicles. As certain coupling relations bearing different degree of freedoms, decoupling control and energy consumption should be taken into account. In this case, centralized control algorithm of multivariate generalized predictive and decoupling control algorithm of inhibiting output fluctuations are proposed.The experimental carrier, "beaver" underwater vehicle, is the independent development product from the Underwater Vehicle Intelligent Control laboratory of Harbin Engineering University. It is applied to underwater vehicle experiments of forward speed and yaw speed as an experimental platform. Then, experimental results are processed and in comparisons to the effects of PID control, concerning the single variable generalized predictive control algorithm which is aimed to reduce energy consumption, centralized-control multivariate generalized predictive algorithm, and decoupling control algorithm. Therefore, it proves that the generalized predictive control algorithm that reduced AUV energy consumption is effective and reasonable.