Study On Linear Quadratic Optimal Controller Based On Cat Swarm Optimization Algorithm

The linear quadratic optimal control is the most important part of the optimal control theory. They started this research in early 1950’s and have made great development and achievements. Especially the research based on state feedback has been quite mature. Therefore, solving some problems with the quadratic viewpoint also made great achievements, such as nonlinear systems, time-delay linear systems, disturbed linear systems and network systems. But in the practical engineering, the state variables are often difficult to measure for most system, we must rely on state estimation or reconstruction if we want to use the state variables as feedback, this will greatly increase the control cost of the system. Therefore, from the perspective of engineering research, it is more practical significance research using the output as feedback control. At present, the research of quadratic complex problem based on output feedback is still not very mature.Linear quadratic problem is dependent on the mathematical model of the system, if model mismatch in the process of control, the performance will be greatly decreased. For complex systems, it is difficult to establish accurate model and needed to determine the approximate model of the system using system identification theory, this will inevitably cause deviation. In addition, the choice of the weighting matrix Q and R will also affect the control performance.In the analysis of the linear quadratic problem, the state regulator problem only considers the cost of the state and the control,the output regulator problem and the optimal tracking problem only consider the cost of output and control. In this paper, we consider the effect of the control, the state and the output on the system, and improve the performance function of the linear quadratic problem, and we propose a novel linear quadratic optimal control combined with output regulation. In theory, the new method can achieve the synthesis optimization of the cost of the control, state and output. In addition, aiming at the shortcoming, this paper introduce a correct idea. We use PID control as the outer ring compensation control weaken the dependence on the system model. For the undetermined parameters in control system, we introduce the swarm intelligence optimization idea. In this paper, aiming at the disadvantages on the basis of the principles of cat swarm optimization algorithm, we get an improved the cat swarm optimization algorithm with better performance by introducing a mutation operator and adaptive inertia weight. Combining these points, linear quadratic optimal control based on cat swarm optimization algorithm is proposed. On the detailed analysis of the feasibility, structure and process of the algorithm, we apply it to the simulation research of linear inverted pendulum, the results prove that the proposed method is effective and has better control performance.