Research On Some Problems Of Flexible Joint Robot Based On Independent Photovoltaic Power System

The flexible joint robot powered by stand-alone PV system ("the FJR powered by PV system" for short), combining photovoltaic technology and robotics technology, is a new type of autonomous robot, which can work independently in no man’s land with the energy supply provided by solar radiation for a long time. The utilization of solar power greatly expands the working range and the duty circle of FJR, especially in the harsh environment where human are inconvenient to go. For example, it plays an important role in the polar region or cosmic space scientific exploration. When it works in the unattended extreme environment, reliable energy supply is the precondition of scientific experiments, and the stability control of FJR is the basic assurance to finish the work tasks successfully.The quality of the photovoltaic energy supply affects indirectly the stability control of FJR, so the performance of the key photovoltaic components should be tested strictly and correctly before application. Meanwhile accurate weak signal extraction of FJR can be used to identify the stiffness parameters, which is very important for the trajectory tracking control of FJR. In addition, it is great valve on the research about the fuzzy control method of FJR, which helps to solve the system uncertainty caused by the non-linear characteristics of PV power. Focusing on the FJR powered by PV system, this dissertation studies some key techniques about the test method of energy supply and control method of FJR, of which the main research achievement is as follows:Aiming at the photovoltaic components performance test of the FJR powered by PV system, the working principle and mathematical model of the photovoltaic cells are analyzed. A test method fitting different types of photovoltaic cells are presented, and the test system is designed. A direct sunlight calibration method of photovoltaic reference solar cells is proposed, and the experiment is conducted in Tibet. A test method of the irradiance non-uniformity and instability of solar simulator is presented, and the verification experiment is finished. The above researches lay the foundation for the simulation test method research of the FJR powered by PV system.Focusing on the performance evaluation about energy supply of the FJR powered by PV system, a simulation test method of the FJR powered by PV system is proposed, and a series of simulation sequence testing in different irradiance conditions is carried out. A programmable DC electronic load is used to simulate power loss of the working flexible joint robot, and a programmable DC power supply is to simulate the power performance of the photovoltaic modules. The process of the power supply of the FJR powered by PV system in different solar irradiances conditions is simulated in the experiment, which evaluates the overall performance and provide a reference for the research about the fuzzy control method of FJR to solve the system uncertainty caused by the non-linear characteristics of PV power.To solve the problem of the stiffness parameters identifying of the FJR powered by PV system working in the extreme strong noise environment, a weak signal extraction approach of FJR combining stochastic resonance with chaotic oscillator is presented. The nonlinear stochastic resonance method is used to analyze the collected signal; the fourth-order Runge-kutta method is used to solve the langevin equation of system model; and then the free vibration signal mixed in the strong noise is extracted successfully. The false frequencies in odd multiple frequencies are filtered via identifying the large periodic motion state of the chaotic phase trajectory changed by weak signal, which owns the same frequency with the reference frequency of duffing chaotic oscillator. On the basis, stiffness parameters of FJR is identified, which lay the foundation for the trajectory tracking control research of FJR.To solve the system uncertainty caused by the non-linear characteristics of PV power, an uncertainty fuzzy robust control method for FJR is proposed. Considering the bounded range of parameter uncertainties, the fuzzy state feedback controller is designed according to the Parallel Distributed Compensation Principle (PDC). Fuzzy Lyapunov function is used to analyze the stability condition of the closed-loop fuzzy control system, and MATLAB simulation experiment is completed to prove the method. Meanwhile, focusing on the problem about inaccurate measurement of the change rate of angle position, a fuzzy control method based on observer for FJR is presented. The state observer of the T-S fuzzy model of FJR is established, and the fuzzy state feedback controller is designed. Fuzzy Lyapunov function is used to derive the stability condition of the closed-loop fuzzy control system. The fuzzy state feedback controller parameters and the observer gain parameters are solved by Linear Matrix Inequality (LMI), and the feasibility of the method is proved by the MATLAB simulation experiment. And then, aiming at the problem about the trajectory tracking control of FJR, a trajectory tracking controller based on parameter identification of FJR is designed. The fractional step method is used to avoid the angular acceleration measurement and derivation operation. The two fuzzy system is applied to approximate the nonlinear uncertainties of subsystem respectively. The effects of parameter identification error is eliminated and the simulation experiment is finished.Finally, aiming at the problem about the modeling error and the fragility of the controller caused by the non-linear characteristics of PV power, a fuzzy passive control approach for FJR is presented. The T-S fuzzy model of FJR is established; the fuzzy passive controller is designed; the closed-loop stability conditions of the control system is analyzed; and the approach is verified via MATLAB simulation experiment. On this basis, a fuzzy passive non-fragile control approach for FJR is presented. When constructing the fuzzy passive non-fragile controller the gain additive perturbation is considered; the closed-loop stability conditions of the control system is analyzed by Lyapunov function; the controller gain matrix and the positive definite matrix, which satisfy the closed-loop stability condition, is solved by the Linear Matrix Inequality (LMI). Finally, the feasibility of the method is proved via the MATLAB simulation experiment.