‧內建PID回授控制、 PG速度回授控制 ‧四組加減速時間選擇與獨加減速S曲線選擇 ‧內含風機水汞專用程序運轉控制與節能運轉 ‧內建RS-485通訊(RJ11埠) ‧馬達參數Auto-tuning與泛用向量控制 ‧睡眠/甦醒功能. 內建 PID Auto Tuning 功能， 提供完整類比控制解決方案 內建1 組RS-232 和2 組RS-485 通訊埠 程式容量：16 k steps 資料暫存器：10 k words PLC 處理速度: 基本指令最快執行速度為0.35 μs V2.0 以上版本支. 智能Pm参数自整定技术在伺服系统中的应用 林青松。等 智能PID参数自整定技术在伺服系统中的应用 AppIication Of InteIligent PID Parameters Auto—tuning Technology in SerVO System 林舌松 钒玉鲜 王穹晓 （河南科技大学电子信息工程学院，河南洛阳471003） 摘要：针对常规PID控制参数整定困难，且受时变、非线性等因.

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How PID Autotuning Works

To use PID autotuning, configure and deploy one of the PID autotuner blocks, Closed-Loop PID Autotuner or Open-Loop PID Autotuner.

Autotuning Process

The PID autotuner blocks work by performing a frequency-response estimation experiment. The blocks inject test signals into your plant and tune PID gains based on an estimated frequency response.

The following schematic diagram illustrates generally how a PID autotuner block fits into a control system.

Until the autotuning process begins, the autotuner block relays the control signal directly from u to the plant input at u+Δu. In that state, the module has no effect on the performance of your system.

When the autotuning process begins, the block injects a test signal at u out to collect plant input-output data and estimate frequency response in real time.

• If you use the Open-Loop PID Autotuner block, the block opens the feedback loop between u and u+Δu for the duration of the estimation experiment. It injects into u+Δu a superposition of sinusoidal signals at frequencies [1/3, 1, 3, 10]ω_c, where ω_c is your specified target bandwidth for tuning. For nonintegrating plants, the block can also inject a step signal to estimate the plant DC gain. All test signals are injected on top of the nominal plant input, which is the value of the signal at u when the experiment begins.

• If you use the Closed-Loop PID Autotuner block, the plant remains under control of the PID controller with its current gains during the experiment. Closed-loop tuning uses sinusoidal test signals at the frequencies [1/10,1/3, 1, 3, 10]ω_c.

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When the experiment ends, the block uses the estimated frequency response to compute PID gains. The tuning algorithm aims to balance performance and robustness while achieving the control bandwidth and phase margin that you specify. You can configure logic to transfer the tuned gains from the block to your PID controller, allowing you to validate closed-loop performance in real time.

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Workflow for PID Autotuning

The following steps provide a general overview of the workflow for PID autotuning.

1. Dev c++ iostream no such directory. Incorporate a PID autotuner block into your system, as shown in the schematic diagram.

2. Configure the start/stop signal that controls when the tuning experiment begins and ends. You can use this signal to initiate the PID autotuning process at any time. When you stop the experiment, the block returns tuned PID gains.

3. Specify controller parameters such as controller type and the target bandwidth for tuning.

4. Configure experiment parameters such as the amplitudes of the perturbations injected during the frequency-response experiment.

5. Start the autotuning process using the start/stop signal, and allow it to run long enough to complete the frequency-response estimation experiment.

6. Stop the autotuning process. When the experiment stops, the autotuner computes and returns tuned PID gains.

7. Transfer the tuned gains from the block to your PID controller. You can then validate the performance of the tuned controller in Simulink^® or in real time.

Genetic algorithms for auto-tuning mobile robot motion control. For detailed information on performing each of these steps, see:

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See Also

Closed-Loop PID AutotunerOpen-Loop PID Autotuner

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