49 results about "Robust control system" patented technology

A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a motorcycle is described. In one embodiment, a simulation model of the motorcycle and rider control is used. In one embodiment, the simulation model includes a feedforward rider model. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and / or output variables; the type of fuzzy inference; and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual plant model of the controlled plant. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.

The invention provides a real-time variable pitch robust control system and a method for a wind turbine based on reinforcement learning. The system comprises a wind speed collection system, a fan information collection module, an enhanced signal generation module, a variable pitch robust control module and a control signal generation module, wherein the wind speed acquisition system is used for collecting the wind speed value in a wind field; the fan information collection module is used for collecting the angular speed of a wind wheel; the enhanced signal generation module can generate an enhanced signal according to the collected wind wheel angular speed and rated wind wheel angular speed; the variable pitch robust control module comprises an action network and an evaluation network, theaction network generates an action value according to the wind speed value in the wind field and the wind wheel angular speed and outputs the action value to the evaluation network, the evaluation network performs learning and training according to the enforced signal and the action value and generates a cumulative return value which is output to the action network, and the action network performs learning and training according to the cumulative return value to update and output the action value; the control signal generation module is connected with the action network to generate the received action value and a corresponding control signal; the wind turbine can adjust the pitch angle according to the control signal, the adjustment of the angular speed of the wind wheel is achieved, andthe smooth output power of a fan is ensured.

The invention discloses a micro-grid system voltage stability control method based on robust control. The control structure of an intelligent micro-grid system is composed of a system control layer, a concentrated control layer and a local control layer, and energy optimization and voltage and frequency stability control of the micro-grid system are realized through multi-layer coordination control. According to the micro-grid system voltage stability control method based on robust control, a comprehensive load module of an induction motor is established, wherein dynamic loads are connected with static loads in parallel. On the premise that the constraint conditions of system performance and robust stability are met, a micro-grid voltage stability robust controller is designed by the adoption of a method of solving the problem of mixed sensitivity so as to improve the micro-grid voltage stability. The micro-grid system voltage stability control method based on robust control can be adapted to wide-range change of load parameters, has high robustness for the situations that due to the factors such as changes of running conditions, influences of external environment and frequency switching of the loads, perturbation is generated in model parameters of a micro-grid and uncertainty exists in the topologic part and the unmolded part and can better restrain parameter drift and noise interference, and meanwhile, the controller is simple in structure and easy to realize.