How to autotune PID gains in control algorithm using particle swarm optimization (PSO) or genetic algorithm (GA) to minimize the trajectory tracking errors for the following purpose??
- Wheel or track-wheel mobile robot trajectory tracking control/path planning
- Robot serial manipulator trajectory tracking control
- Quadrotor system trajectory tracking control
therefore, in the above cases, the manual tuning of the gain parameters can be avoided.
this link may be help you
https://github.com/shkamaru/Quadcopter-with-FLC
To tune your algorithm, I suggest you follow Chapter Advanced Methods of PID Controller Tuning for Specified Performance
https://www.mdpi.com/2075-1702/3/3/208/htm
Dear Ravindra Singh Bisht,
For tuning the PID gains using PSO and GA, please refer to the following insightful links:
https://www.hindawi.com/journals/isrn/2013/543607/
https://ieeexplore.ieee.org/document/5572133
https://in.mathworks.com/matlabcentral/fileexchange/20252-tunning-of-pid-controller-using-particle-swarm-optimization
https://ieeexplore.ieee.org/document/783590
https://ieeexplore.ieee.org/document/5138538/
Please find the attached paper for comparative analysis on tuning methods based on DE and GA.
Dear Bisht Sir,
For tuning PID gains using any optimization criterion, the major thing that you require is the formulation of the cost function. This cost function is a measure of the performance of the controller. It is generally based on performance parameters such as maximum overshoot, settling time etc. Here is one paper that was given to us by Prof. Pillai as a lab assignment for tuning PID using PSO. This will be helpful to you.
Article A Particle Swarm Optimization Approach for Optimum Design of...
After designing the cost function you can use an optimization algorithm to minimize this cost function. For any query, you can give me a call.
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